18, it is possible to mode ≥ n0, n1, n2, which are the number of matrixes for each set of matrixes S0, S1, S2, respectively). Further, the sets may have different numbers of matrixes each (for example, it may be that S0 has 16 matrixes S1 has eight matrixes, and S2 has six matrixes). The mode and transposed information are not necessarily stored and/or transmitted as one combined mode index ‘mode’: in some examples there is the possibility of signalling explicitly as a transposed flag and the matrix index (0-15 for S0, 0-7 for S1 and 0-5 for S2). In some cases, the combination of the transposed flag and matrix index may be interpreted as a set index. For example, there may be one bit operating as transposed flag, and some bits indicating the matrix index, collectively indicated as “set index”. 5.5 Generation of the reduced prediction signal by matrix vector multiplication Here, features are provided regarding step 812. Out of the reduced input vector bdryred (boundary vector 17P) one may generate a reduced prediction signal predred. The latter signal may be a signal on the downsampled block of width Wred and height Hred. Here, Wred and Hred may be defined as: Wred = 4, Hred = 4; if max(W,H ) < 8, Wred = min(W, 8) , Hred = min (H, 8) ; else. The reduced prediction signal predred may be computed by calculating a matrix vector-product and adding an offset: predred = A • bdryred + b. Here, A is a matrix (e.g. prediction matrix 17M) that may have Wred * Hred rows and 4 columns if W=H=4 and 8 columns in all other cases and b is a vector that may be of size Wred * Hred. If W = H = 4, then A may have 4 columns and 16 rows and thus 4 multiplications per sample may be needed in that case to compute predred. In all other cases, A may have 8 columns and one may verify that in these cases one has 8 * wred * Hred < 4 * W * H, i.e. also in these cases, at most 4 multiplications per sample are needed to compute predred. The matrix A and the vector b may be taken from one of the sets S0, S1,S2 as follows. One defines an index idx = idx(W, H ) by setting idx(W, H) = 0, if W = H = 4, idx(W, H) = 1, if max(W, H) = 8 and idx(W, H) - 2 in all other cases. Moreover, one may put m = mode, if mode < 18 and m = mode - 17, else. Then, if idx ≤ 1 or idx = 2 and min (W, H) > 4, one may put and b = In the case that idx= 2 and min(W,H ) = 4, one lets A be the matrix that arises by leaving out every row of that, in the case W=4, corresponds to an odd x-coordinate in the downsampled block, or, in the case H=4, corresponds to an odd y-coordinate in the downsampled block. If mode ≥ 18, one replaces the reduced prediction signal by its transposed signal. In alternative examples, different strategies may be carried out. For example, instead of reducing the size of a larger matrix (“leave out”), a smaller matrix of S1 (idx=1) with Wred=4 and Hred=4 is used. I.e., such blocks are now assigned to Si instead of S2. Other strategies may be carried out. In other examples, the mode index ‘mode’ is not necessarily in the range 0 to 35 (other ranges may be defined). Further, it is not necessary that each of the three sets S0, S1, S2 has 18 matrices (hence, instead of expressions like mode < 18, it is possible to mode < n0, n1, n2, which are the number of matrixes for each set of matrixes S0, S1, S2, respectively). Further, the sets may have different numbers of matrixes each (for example, it may be that S0 has 16 matrixes S1 has eight matrixes, and S2 has six matrixes). 5.6 Linear interpolation to generate the final prediction signal Here, features are provided regarding step 812. Interpolation of the subsampled prediction signal, on large blocks a second version of the averaged boundary may be needed. Namely, if min(W, H) > 8 and W ≥ H, one writes W= 8 * 2l, and for 0 ≤ i < 8 defines If min(W, H) > 8 and H > W, one defines analogously. In addition or alternative, it is possible to have a “hard downsampling”, in which the is equal to Also, can be defined analogously. At the sample positions that were left out in the generation of predred, the final prediction signal may arise by linear interpolation from predred (e.g., step 813 in examples of Figs. 7.2-7.4 and 8.2). This linear interpolation may be unnecessary, in some examples, if W = H = 4 (e.g., example of Figs. 7.1 and 8.1). The linear interpolation may be given as follows (other examples are notwithstanding possible). It is assumed that W ³ H. Then, if H > Hred, a vertical upsampling of predred may be performed. In that case, predred may be extended by one line to the top as follows. If W = 8, predred may have width Wred = 4 and may be extended to the top by the averaged boundary signal e.g. as defined above. If W > 8, predred is of width Wred = 8 and it is extended to the top by the averaged boundary signal e.g. as defined above. One may write predred [x][-1] for the first line of predred. Then the signal on a block of width Wred and height 2 * Hred may be given as where 0 < x < Wred and 0 < y < Hred. The latter process may be carried out k times until 2k * Hred = H. Thus, if H= 8 or H= 16, it may be carried out at most once. If H= 32, it may be carried out twice. If H= 64, it may be carried out three times. Next, a horizontal upsampling operation may be applied to the result of the vertical upsampling. The latter upsampling operation may use the full boundary left of the prediction signal. Finally, if H > W, one may proceed analogously by first upsampling in the horizontal direction (if required) and then in the vertical direction. This is an example of an interpolation using reduced boundary samples for the first interpolation (horizontally or vertically) and original boundary samples for the second interpolation (vertically or horizontally). Depending on the block size, only the second or no interpolation is required. If both horizontal and vertical interpolation is required, the order depends on the width and height of the block. However, different techniques may be implemented: for example, original boundary samples may be used for both the first and the second interpolation and the order may be fixed, e.g. first horizontal then vertical (in other cases, first vertical then horizontal). Hence, the interpolation order (horizontal/vertical) and the use of reduced/original boundary samples may be varied. 5.7 Illustration ofan example of the entire ALWIPprocess The entire process of averaging, matrix-vector-multiplication and linear interpolation is illustrated for different shapes in Figs. 7.1-7.4. Note, that the remaining shapes are treated as in one of the depicted cases. Given a 4 x 4 block, ALWIP may take two averages along each axis of the boundary by using the technique of Fig. 7.1. The resulting four input samples enter the matrix-vector- multiplication. The matrices are taken from the set S0. After adding an offset, this may yield the 16 final prediction samples. Linear interpolation is not necessary for generating the prediction signal. Thus, a total of (4 * 16)/(4 * 4) = 4 multiplications per sample are performed. See, for example, Figs. 7.1 and 8.1. Given an 8 x 8 block, ALWIP may take four averages along each axis of the boundary. The resulting eight input samples enter the matrix-vector-multiplication, by using the technique of Fig. 7.2. The matrices are taken from the set St. This yields 16 samples on the odd positions of the prediction block. Thus, a total of (8 * 16)/(8 * 8) = 2 multiplications per sample are performed. After adding an offset, these samples may be interpolated e.g. vertically by using the top boundary and e.g. horizontally by using the left boundary, for example. See, for example, Figs. 7.2 and 8.2. Given an 8 x 4 block, ALWIP may take four averages along the horizontal axis of the boundary and the four original boundary values on the left boundary, by using the technique of Fig. 7.3. The resulting eight input samples enter the matrix-vector-multiplication. The matrices are taken from the set S1. This yields 16 samples on the odd horizontal and each vertical positions of the prediction block. Thus, a total of (8 * 16)/(8 * 4) = 4 multiplications per sample are performed. After adding an offset, these samples are interpolated horizontally by using the left boundary, for example. See, for example, Figs. 7.3 and 8.2. The transposed case is treated accordingly. Given a 16 x 16 block, ALWIP may take four averages along each axis of the boundary. The resulting eight input samples enter the matrix-vector-multiplication, by using the technique of Fig. 7.2. The matrices are taken from the set S2. This yields 64 samples on the odd positions of the prediction block. Thus, a total of (8 * 64)/(16 * 16) = 2 multiplications per sample are performed. After adding an offset, these samples are interpolated vertically by using the top boundary and horizontally by using the left boundary, for example. See, for example, Figs. 7.2 and 8.2. See, for example, Figs. 7.4 and 8.2. For larger shapes, the procedure may be essentially the same and it is easy to check that the number of multiplications per sample is less than two. For Wx8 blocks, only horizontal interpolation is necessary as the samples are given at the odd horizontal and each vertical positions. Thus, at most (8 * 64)/(16 * 8) = 4 multiplications per sample are performed in these cases. Finally for W×4 blocks with W>8, let Ak be the matrix that arises by leaving out every row that correspond to an odd entry along the horizontal axis of the downsampled block. Thus, the output size may be 32 and again, only horizontal interpolation remains to be performed. At most (8 * 32)/(16 * 4) = 4 multiplications per sample may be performed. The transposed cases may be treated accordingly. 5.8 Number of parameters needed and complexity assessment The parameters needed for all possible proposed intra prediction modes may be comprised by the matrices and offset vectors belonging to the sets S0, S1,S2. All matrix-coefficients and offset vectors may be stored as 10-bit values. Thus, according to the above description, a total number of 14400 parameters, each in 10-bit precision, may be needed for the proposed method. This corresponds to 0,018 Megabyte of memory. It is pointed out that currently, a CTU of size 128 x 128 in the standard 4:2:0 chroma-subsampling consists of 24576 values, each in 10 bit. Thus, the memory requirement of the proposed intra-prediction tool does not exceed the memory requirement of the current picture referencing tool that was adopted at the last meeting. Also, it is pointed out that the conventional intra prediction modes require four multiplications per sample due to the PDPC tool or the 4-tap interpolation filters for the angular prediction modes with fractional angle positions. Thus, in terms of operational complexity the proposed method does not exceed the conventional intra prediction modes. 5.9 Signalization of the proposed intra prediction modes For luma blocks, 35 ALWIP modes are proposed, for example (other numbers of modes may be used). For each Coding Unit (CU) in intra mode, a flag indicating if an ALWIP mode is to be applied on the corresponding Prediction Unit (PU) or not is sent in the bitstream. The signalization of the latter index may be harmonized with MRL in the same way as for the first CE test. If an ALWIP mode is to be applied, the index predmode of the ALWIP mode may be signaled using an MPM-list with 3 MPMS. Here, the derivation of the MPMs may be performed using the intra-modes of the above and the left PU as follows. There may be tables, e.g. three fixed tables map_angular_to_alwipidx, idx e {0,1,2} that may assign to each conventional intra prediction mode predmodeAngular an ALWIP mode predmodeALWIP = map_angular_to_alwipidx[predmodeAngular ]. For each PU of width W and height H one defines and index idx(PU) = idx(W, H) ∈ {0,1,2} that indicates from which of the three sets the ALWIP-parameters are to be taken as in section 4 above. If the above Prediction Unit PUabove is available, belongs to the same CTU as the current PU and is in intra mode, if idx(PU) = idx(PUabove ) and if ALWIP is applied on PUabove with ALWIP-mode one puts If the above PU is available, belongs to the same CTU as the current PU and is in intra mode and if a conventional intra prediction mode is applied on the above PU, one puts In all other cases, one puts which means that this mode is unavailable. In the same way but without the restriction that the left PU needs to belong to the same CTU as the current PU, one derives a mode Finally, three fixed default lists listldx, idx ∈ {0,1,2} are provided, each of which contains three distinct ALWIP modes. Out of the default list Ustidx(PU) and the modes and one constructs three distinct MPMs by substituting -1 by default values as well as eliminating repetitions. 5.10 Adapted MPM-list derivation for conventional luma and chroma intra-prediction modes The proposed ALWIP-modes may be harmonized with the MPM-based coding of the conventional intra-prediction modes as follows. The luma and chroma MPM-list derivation processes for the conventional intra-prediction modes may use fixed tables map_lwip_to_angularidx, idx ∈ {0,1,2}, mapping an ALWIP-mode predmodeLWIP on a given PU to one of the conventional intra-prediction modes predmodeAngular = map_lwip_to_angularidx(PU)[predmodeLWIP ]. For the luma MPM-list derivation, whenever a neighboring luma block is encountered which uses an ALWIP-mode predmodeLWIP, this block may be treated as if it was using the conventional intra-prediction mode predmodeAngular. For the chroma MPM-list derivation, whenever the current luma block uses an LWIP-mode, the same mapping may be used to translate the ALWIP-mode to a conventional intra prediction mode. 5.11 Experimental results Evaluation of the test was performed according to the common test conditions JVET-J1010 [2], for the intra-only (Al) and random-access (RA) configurations with the VTM software version 3.0.1. The corresponding simulations were conducted on an Intel Xeon cluster (E5-2697A v4, AVX2 on, turbo boost off) with Linux OS and GCC 7.2.1 compiler. Table 1. Result of CE3-1.2.2 for VTM Al configuration Table 2. Result of CE3-1.2.2 for VTM RA configuration 5.12 Additional results with further encoder speedups We additionally provide two further results for tests that relied on the same syntax as CE 3-1.2.2 but with an optimized Encoder search. Table 1. Result of CE3-1.2.2 for VTM Al configuration, First Encoder Speedup Table 2. Result of CE3-1.2.2 for VTM RA configuration. First Encoder Speedup Table 3. Result of CE3-1.2.2 for VTM Al configuration, Second Encoder Speedup Table 4. Result of CE3-1.2.2 for VTM RA configuration, Second Encoder Speedup 6. The encoder of Fiq. 10 Fig. 10 shows another example which may be construed from the examples of Figs. 1, 2, and 5-9 (in particular, some features may be directly derived from Fig. 2 and are therefore here not repeated). Fig. 10 shows an encoder 14 which may be, for example, a particular case of the encoder of Fig. 1. Analogously to Fig. 2, encoder 14 may comprise a subtractor 22 configured to subtract from the inbound signal, i.e. picture 10 or, on a block basis, current block 18, the corresponding prediction signal 24 (e.g., the block 18 with the reconstructed samples 104 as obtained at step 812), so as to obtain the prediction residual signal 26 which is then encoded by a prediction residual encoder 28 into a datastream 12. The prediction residual encoder 28 may include a lossy encoding stage 28a and a lossless encoding stage (entropy coder) 28b. The lossy encoding stage 28a may receive the prediction residual signal 26 and comprise a quantizer 30 (not shown) configured to quantize the samples of the prediction residual signal 26. The obtained prediction residual signal 34 is then subject to lossless coding by the lossless encoding stage 28b which is an entropy coder entropy coding quantized prediction residual signal 34 into datastream 12. Encoder 14 may further comprise the prediction residual signal reconstruction stage 36 connected to the output of the lossy encoding stage 28a, so as to reconstruct from the transformed and quantized prediction residual signal 34’. The encoder 14 may comprise an adder 42 to add the reconstructed prediction residual signal 34’ as output by stage 36 and the prediction signal 24 (e.g., including the block 18 with the reconstructed samples 104 as obtained at step 813), so as to output a reconstructed signal, i.e. reconstructed samples. This output is fed into the predictor 44 which may then determine the prediction signal 24 based thereon (e.g., by applying the techniques illustrated in Figs. 8.1-7.4). As can be seen, in Fig. 9 the method steps 811, 812, 813 are here mapped by stages 811’, 812’, 813’, respectively, within the predictor 44: the method steps 811, 812, 813 may be implemented in hardware units and/or procedural routines, collectively indicated with 811', 812’, 813’, in the predictor 44 or controlled by the predictor. It is shown that it is possible, in examples, to skip the deriving stage 813’, as in the example of Fig. 7.1. In particular, stage 811 and/or 813 may be depicted as presenting a register such as the register 910 for performing the shifting operations discussed above (the register 910 is not necessarily a part of the stage 811 or 813: it can be a unit which is controlled by the subjecting stage). Instead, stage 812 is depicted as having or controlling a multiplier 1910 in which the multiplications performed between the Pred elements of the selected or averaged samples 102 of the neighbouring samples 17 are multiplied by the Q or Qred weighting factors of the matrixes 17M In the stages 81 T, 812’, 813’, other elements (such as adders, etc.) are not shown for brevity. A storage 1044 is here indicated as storing the ALWIP matrixes 17M or (e.g., in the sets So, S1, S2) and offset vectors (hereinabove also indicated as bk) The index 944(e.g., one or more of the indexes discussed above such as i, k, transposed index, set index) i of the matrix and/or offset may be encoded in the datastream 12. The Q or Qred weighting factors are, in general, not signalled in the datastream 12: this is because the decoder already has notion of the Q or Qred weighting factors of the ALWIP matrixes 17M (e.g., has a copy of the data stored in the storage 1044), hence reducing the payload. Even if not shows in the figures, there is the possibility for the encoder 14 to decide the dimensions of the ALWIP matrixes to be used (e.g., which set among the sets S0, S1, S2), e.g. on the basis of the dimensions of the block 18. In some cases, it is not necessary to signal this choice, as consequent on the choice of the dimensions of the block 18. Hence, the encoder 14 is configured to insert, for the predetermined block 18, a prediction residual 34 into the data stream 12 from which the predetermined block 18 is reconstructible using the prediction residual and the predicted values 24 (104) for the predetermined samples obtained at the step 812. In addition or alternatively, the encoder 14 may be configured to insert, for the predetermined block (18), a prediction residual (26, 34) into the data stream (12) which indicates for each of the Q or Qred predetermined samples a corresponding residual value so that the predetermined block (18) may be reconstructed using the prediction residual (26, 34) and the predicted values for the predetermined samples by correcting the predicted value for each of the set of Q or Qred values so that the corresponding reconstructed value depends on the Pred neighbouring samples (102) within the reduced set (102) of sample values strictly linearly except for, optionally, a clipping applied after prediction and/or correction. In addition or alternatively, the encoder 14 may be configured to subdivide the picture (16) into a plurality of blocks of different block sizes, which comprises the predetermined block (18). The encoder 14 may be configured to select the linear or affine linear transformation (19, Ak) depending on a width W (also indicated with N) and height H (also indicated with M) of the predetermined block (18) such that the linear or affine linear transformation (19, Ak) selected for the predetermined block (18) is selected out of a first set of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a first set (e.g., associated to S0) of width/height pairs and a second set of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a second set (e.g., associated to S1) of width/height pairs which is disjoint to the first set of width/height pairs. In addition or alternatively, the encoder may be configured so that the third set (e.g. So) of one or more width/height pairs merely comprises one width/height pair, W', H’, and each linear or affine linear transformation within second set of linear or affine linear transformations is for transforming N’ sample values to W’*H’ predicted values for an W’xH’ array of sample positions. In addition or alternatively, the encoder may be configured so that each of the first and second sets of width/height pairs comprises a first width/height pairs WP,HP with Wp being unequal to Hp and a second width/height pair Wq,Hq with Hq=Wp and Wq=Hp. In addition or alternatively, the encoder may be configured so that each of the first and second sets of width/height pairs additionally comprises a third width/height pairs WP,HP with Wp being equal to Hp and Hp > Hq. In addition or alternatively, the encoder may be configured to insert for the predetermined block a set index into the data stream, select the linear or affine linear transformation depending on the set index out of a predetermined set of linear or affine linear transformations. In addition or alternatively, the encoder may be configured so that the plurality of neighbouring samples extend one-dimensionally along two sides of the predetermined block and the encoder is configured to perform the reduction by, for a first subset of the plurality of neighbouring samples, which adjoin a first side of the predetermined block, grouping the first subset into first groups (110) of one or more consecutive neighbouring samples and, for a second subset of the plurality of neighbouring samples, which adjoin a second side of the predetermined block, grouping the second subset into second groups (110) of one or more consecutive neighbouring samples and performing a downsampling or an averaging on each of the first and second groups of one or more neighbouring samples which has more than two neighbouring samples, so as to obtain first sample values from the first groups and second sample values for the second groups, and the encoder configured to select the linear or affine linear transformation depending on the set index out of a predetermined set of linear or affine linear transformations such that two different states of the set index result into a selection of one of the linear or affine linear transformations of the predetermined set of linear or affine linear transformations, and subject the reduced set of sample values to the predetermined linear or affine linear transformation in case of the set index assuming a first of the two different states in form of a first vector to yield an output vector of predicted values, and distribute the predicted values of the output vector along a first scan order onto the predetermined samples of the predetermined block and in case of the set index assuming a second of the two different states in form of a second vector, the first and second vectors differing so that components populated by one of the first sample values in the first vector are populated by one of the second sample values in the second vector, and components populated by one of the second sample values in the first vector are populated by one of the first sample values in the second vector, so as to yield an output vector of predicted values, and distribute the predicted values of the output vector along a second scan order onto the predetermined samples of the predetermined block which is transposed relative to the first scan order. In addition or alternatively, the encoder may be configured so that each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N1 sample values to w1*h1 predicted values for an w1xh1 array of sample positions and each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N2 sample values to W2*h2 predicted values for an W2Xh2 array of sample positions, and wherein for a first predetermined one of the first set of width/height pairs, w1 exceeds the width of the first predetermined width/height pair or hi exceeds the height of the first predetermined width/height pair, and for a second predetermined one of the first set of width/height pairs neither w1 exceeds the width of the second predetermined width/height pair nor hi exceeds the height of the second predetermined width/height pair, and the encoder may be configured to perform the reducing (100), by downsampling or averaging, the plurality of neighbouring samples to obtain the reduced set (102) of samples values so that the reduced set (102) of samples values has N1 sample values if the predetermined block is of the first predetermined width/height pair and if the predetermined block is of the second predetermined width/height pair, and perform the subjecting the reduced set of sample values to the selected linear or affine linear transformation by using only a first sub-portion of the selected linear or affine linear transformation which is related to a subsampling of the w1xh1 array of sample positions along width dimension if wi exceeds the width of the one width/height pair, or along height dimension if hi exceeds the height of the one width/height pair if the predetermined block is of the first predetermined width/height pair, and the selected linear or affine linear transformation completely if the predetermined block is of the second predetermined width/height pair. In addition or alternatively, the encoder may be configured so that each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming Ni sample values to w1*h1 predicted values for an wixhi array of sample positions with w1=h1 and each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N2 sample values to w2*h2 predicted values for an w2xh2 array of sample positions with W2=h2. 7. The example of Fig. 11 Fig. 11 shows another example which may be construed from the examples of Figs. 3-9 (in particular, some features may be directly derived from Fig. 4 and are therefore here not repeated). Fig. 11 shows a possible implementation of the decoder 54 of Fig. 4, namely one fitting to the implementation of encoder 14 of Fig. 10. In particular, adder 42' and predictor 44' may be connected into a prediction loop in the same manner that they are in encoder 14 of Fig. 10. The reconstructed, i.e. dequantized and retransformed prediction residual signal applied to adder 42' may be derived by a sequence of entropy decoder which inverses the entropy encoding of entropy encoder, followed by the residual signal reconstruction stage which is composed of dequantizer and inverse transformer 40' just as it is the case on encoding side. The decoder's output is the reconstruction of picture 10. The reconstruction of picture 10 may be available directly at the output of adder 42' or, alternatively, at the output of an in-loop filter. As can be seen, stages 813’, 812’, 813’ may be as the encoder 14, and the storing unit 1044 may store the sets of matrixes as in the encoder 14. Hence, the discussion is here not repeated. The index 944 (e.g., one or more of the indexes discussed above such as i, k, transposed index, set index) may be directly obtained from the datastream 12. The choice among the sets S0, S1, S2 may follow the size (e.g., H/K, or M/N, for example). In addition or alternatively, the decoder may be configured to derive, for the predetermined block (18), a prediction residual (34”) from the data stream (12), and reconstruct (42’) the predetermined block (18) using the prediction residual (34”) and the predicted values (24’) for the predetermined samples (24’, 104, 108, 108’). In addition or alternatively, the decoder may be configured to derive, for the predetermined block (18), a prediction residual (34”) from the data stream (12) in order to obtain for each of the set of Q or Qred predetermined samples a corresponding residual value, and reconstruct the predetermined block (18) using the prediction residual (34”) and the predicted values (24’, 104) for the predetermined samples (118’, 118”) by correcting the predicted value for each of the set of Q or Qred predetermined samples by the corresponding residual value (34”) to obtain a corresponding reconstructed value (10) so that the corresponding reconstructed value (10) depends on the Pred neighbouring samples (102) within the reduced set of sample values strictly linearly except for, optionally, a clipping applied after prediction and/or correction. In addition or alternatively, the decoder may be configured so that the decoder is configured to subdivide the picture (10) into a plurality of blocks of different block sizes, which comprises the predetermined block (18), wherein the decoder is configured to select the linear or affine linear transformation (19, 17M, Ak) depending on a width W and height H of the predetermined block (18) such that the linear or affine linear transformation selected for the predetermined block (18) is selected out of a first set of linear or affine linear transformations as long as the width W and height H of the predetermined block (81) are within a first set of width/height pairs and a second set of linear or affine linear transformations as long as the width W and height H of the predetermined block are within a second set of width/height pairs which is disjoint to the first set of width/height pairs. In addition or alternatively, the decoder may be configured so the decoder is configured to subdivide the picture (10) into a plurality of blocks of different block sizes, which comprises the predetermined block (18), wherein the decoder is configured to select the linear or affine linear transformation (19, 17M, Ak) depending on a width W and height H of the predetermined block (18) such that the linear or affine linear transformation selected for the predetermined block (18) is selected out of a first set of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a first set of width/height pairs, a second set of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a second set of width/height pairs which is disjoint to the first set of width/height pairs, and a third set of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a third set of one or more width/height pairs, which is disjoint to the first and second sets of width/height pairs. In addition or alternatively, the decoder may be configured so the third set of one or more width/height pairs merely comprises one width/height pair, W’, H’, and each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N’ sample values to W’*H’ predicted values for an W’xH’ array of sample positions. In addition or alternatively, the decoder may be configured so Each of the first and second sets of width/height pairs comprises a first width/height pairs Wp, Hp with Wp being unequal to Hp and a second width/height pair Wq, Hq with Hq=Wp and Wq=Hp. In addition or alternatively, the decoder may be configured so Each of the first and second sets of width/height pairs additionally comprises a third width/height pairs Wp, Hp with Wp being equal to Hp and Hp > Hq. In addition or alternatively, the decoder may be configured so Read for the predetermined block (18) a set index (k) from the data stream (12), select the linear or affine linear transformation depending on the set index (k) out of a predetermined set of linear or affine linear transformations. In addition or alternatively, the decoder may be configured so the plurality of neighbouring samples (17) extend one-dimensionally along two sides of the predetermined block (18) and the decoder is configured to perform the reduction (811) by, for a first subset of the plurality of neighbouring samples, which adjoin a first side of the predetermined block, grouping the first subset into first groups (110) of one or more consecutive neighbouring samples and, for a second subset of the plurality of neighbouring samples, which adjoin a second side of the predetermined block, grouping the second subset into second groups (110) of one or more consecutive neighbouring samples and performing a downsampling or an averaging on each of the first and second groups of one or more neighbouring samples which has more than two neighbouring samples, so as to obtain first sample values from the first groups and second sample values for the second groups, and the decoder may be configured to select the linear or affine linear transformation depending on the set index out of a predetermined set of linear or affine linear transformations such that two different states of the set index result into a selection of one of the linear or affine linear transformations of the predetermined set of linear or affine linear transformations, and subject the reduced set of sample values to the predetermined linear or affine linear transformation, in case of the set index assuming a first of the two different states in form of a first vector to yield an output vector of predicted values, and distribute the predicted values of the output vector along a first scan order onto the predetermined samples of the predetermined block, and in case of the set index assuming a second of the two different states in form of a second vector, the first and second vectors differing so that components populated by one of the first sample values in the first vector are populated by one of the second sample values in the second vector, and components populated by one of the second sample values in the first vector are populated by one of the first sample values in the second vector, so as to yield an output vector of predicted values, and distribute the predicted values of the output vector along a second scan order onto the predetermined samples of the predetermined block which is transposed relative to the first scan order. In addition or alternatively, the decoder may be configured so each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N1 sample values to w1*h1 predicted values for an W1xh1 array of sample positions and each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N2 sample values to w2*h2 predicted values for an w2xh2 array of sample positions, and wherein for a first predetermined one of the first set of width/height pairs, w1 exceeds the width of the first predetermined width/height pair or hi exceeds the height of the first predetermined width/height pair, and for a second predetermined one of the first set of width/height pairs neither wi exceeds the width of the second predetermined width/height pair nor h1 exceeds the height of the second predetermined width/height pair, and wherein the decoder is configured to perform the reducing (100), by downsampling or averaging, the plurality of neighbouring samples to obtain the reduced set (102) of samples values so that the reduced set (102) of samples values has N1 sample values if the predetermined block is of the first predetermined width/height pair and if the predetermined block is of the second predetermined width/height pair, and perform the subjecting the reduced set of sample values to the selected linear or affine linear transformation by using only a first sub-portion of the selected linear or affine linear transformation which is related to a subsampling of the w1xh1 array of sample positions along width dimension if w1 exceeds the width of the one width/height pair, or along height dimension if h1 exceeds the height of the one width/height pair if the predetermined block is of the first predetermined width/height pair, and the selected linear or affine linear transformation completely if the predetermined block is of the second predetermined width/height pair. In addition or alternatively, the decoder may be configured so each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N1 sample values to w1*h1 predicted values for an wixhi array of sample positions with w1=h1 and each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N2 sample values to w2*h2 predicted values for an w2xh2 array of sample positions with w2=h2. 8. Discussion on effects of the present techniques Independently of using operations such as bit-shifting for averaging and/or interpolating (which comes, inter alia, to the effect of reducing the computational efforts) it is also noted that other effects may be obtained which, in some examples, may even transcend from the effective use of bit-shifting. In particular, with the present examples, prediction modes can be shared across different block-shapes, so that the selection of the ALWIP matrix 17M (e.g. at step 812a) is performed on a limited number of sets. E.g., there may be less sets of ALWIP matrixes than possible dimensions (e.g. pairs of heights/widths) of the blocks 18 to be predicted. Reference can be made to Fig. 12, which maps different width/height pairs of blocks 18 to be predicted into one of sets S0 (e.g. with n0 matrixes, e.g. with no=16), S1 (e.g. with n1 matrixes, e.g. with n1=8), and S2 (e.g. with n2 matrixes, e.g. with n2=6), as discussed above (different repartitions may be possible). For example, the 16x8 matrixes of set S1 may be shared by prediction modes for blocks with any of the dimensions 4x 8,4x 16,4x 32,4x 64,8x 4,8x8,16x4,32x 4, and 64x 4, and the 64x8 matrixes of set S2 may be shared by prediction modes for blocks with any of the dimensions 8x 16,8x 32,8x 64,16X 8,16x 16,16x 32,16x 64,32x 8,32x 16,32x 32,32x 64,64x 8,64x 16,64x 32,64x 64. It is simply necessary to perform techniques such as those discussed for the reducing step 811 (see above) for reducing the dimensions of the boundary 17 to the necessary Pred number of samples for forming the set 102, but, at step 812, the original dimension of the block 18 to be predicted is irrelevant. At the step 813 (if implemented), it will be possible to arrive at the complete prediction of the block by simply perform interpolations. It has been noted that this approach permits to reduce the storage space necessary at the storage space 1044 at unexpected dimensions of 16*16*4+8*16*8+6*64*8=5120 values (e.g., each value being, for example, an 8-bit value). In comparison, a traditional technique would require to use a set of matrixes for each width/height pairs. As can be easily understood from Fig. 12, there would be needed 25 sets! It can be easily understood how 25 sets of matrixes require much more than a storage space of 5120 values. In order to reduce the necessary storage space, it would therefore necessary to reduce the number of matrixes for each set: however, if only few matrixes are at disposal for the prediction, quality would be reduced! The reduction of the storage space in view of the sharing technique is even amplified by the reduction of the size of the stored matrixes themselves. For example, the prediction of a MxN=64x64 block would require a matrix of size QxP=(M*N)x(M+N), i.e. with (64*64)*(64+64)=524288 values to be stored in the storage space! Hence, with the present techniques it is possible to save even more storage space than expected. Hence, the present techniques permit to reduce the number of parameters that need to be stored in the unit 1044. With or without the actual use of the bit-shifting, the storage resources at disposal of the encoder or decoder may be reduced or, conversely, more prediction modes may be used to parity of storage space. Optimal effects are notwithstanding achieved by combining the bit-shifting techniques (at step 811 and/or 813) with that of sharing the same prediction mode for multiple modes (at step 812). With respect to the traditional approach of using 25 different sets for the 25 different pairs of height/width, the present technique could apparently be interpreted as increasing complexity (as step 811 and/or 813 is not conceivable with traditional techniques). However, the introduction of step 811 and/or 813 can be more than compensated by the reduction of multiplications. Moreover, with respect to the traditional approach of using 25 different sets for the 25 different pairs of height/width, the instructions necessary for controlling this processing require more storing space (as additional instructions for step 811 and/or 813 are to be stored). However, the necessity of storing the instructions for step 811 and/or 813 can be more than compensated by the reduction of space implied by the reduced number of matrixes stored. 9. Further embodiments and examples Generally, examples may be implemented as a computer program product with program instructions, the program instructions being operative for performing one of the methods when the computer program product runs on a computer. The program instructions may for example be stored on a machine readable medium. Other examples comprise the computer program for performing one of the methods described herein, stored on a machine-readable carrier. In other words, an example of method is, therefore, a computer program having program instructions for performing one of the methods described herein, when the computer program runs on a computer. A further example of the methods is, therefore, a data carrier medium (or a digital storage medium, or a computer-readable medium) comprising, recorded thereon, the computer program for performing one of the methods described herein. The data carrier medium, the digital storage medium or the recorded medium are tangible and/or non-transitionary, rather than signals which are intangible and transitory. A further example of the method is, therefore, a data stream or a sequence of signals representing the computer program for performing one of the methods described herein. The data stream or the sequence of signals may for example be transferred via a data communication connection, for example via the Internet. A further example comprises a processing means, for example a computer, or a programmable logic device performing one of the methods described herein. A further example comprises a computer having installed thereon the computer program for performing one of the methods described herein. A further example comprises an apparatus or a system transferring (for example, electronically or optically) a computer program for performing one of the methods described herein to a receiver. The receiver may, for example, be a computer, a mobile device, a memory device or the like. The apparatus or system may, for example, comprise a file server for transferring the computer program to the receiver. In some examples, a programmable logic device (for example, a field programmable gate array) may be used to perform some or all of the functionalities of the methods described herein. In some examples, a field programmable gate array may cooperate with a microprocessor in order to perform one of the methods described herein. Generally, the methods may be performed by any appropriate hardware apparatus. The above described examples are merely illustrative for the principles discussed above. It is understood that modifications and variations of the arrangements and the details described herein will be apparent. It is the intent, therefore, to be limited by the scope of the impending claims and not by the specific details presented by way of description and explanation of the examples herein. Equal or equivalent elements or elements with equal or equivalent functionality are denoted in the following description by equal or equivalent reference numerals even if occurring in different figures. References [1] P. Helle et al., “Non-linear weighted intra prediction”, JVET-L0199, Macao, China, October 2018. [2] F. Bossen, J. Boyce, K. Suehring, X. Li, V. Seregin, “JVET common test conditions and software reference configurations for SDR video”, JVET-K1010, Ljubljana, SI, July 2018. Claims 1. Decoder (54) for decoding a picture (10) from a data stream (12), configured to predict a predetermined block (18) of the picture using a plurality of neighbouring samples (17) by reducing (100, 813) the plurality of neighbouring samples to obtain a reduced set (102) of samples values lower, in number of samples, than compared to the plurality of neighbouring samples (17), subjecting (812) the reduced set of sample values (102) to a linear or affine linear transformation (19, 17M) to obtain predicted values for predetermined samples (104, 118’, 188”) of the predetermined block (18). 2. The decoder (54) of claim 1, further configured to perform the reducing (100, 813) by downsampling. 3. The decoder (54) of claim 1, further configured to perform the reducing (100, 813) by averaging. 4. The decoder of claim 3, wherein averaging includes bit-shifting. 5. The decoder (54) of any of the preceding claims, further configured to derive (813), by interpolation, prediction values for further samples (108, 108’) of the predetermined block (18) on the basis of the predicted values for the predetermined samples (104, 118’, 118”) and the plurality of neighbouring samples (17). 6. The decoder of claim 5, wherein the plurality of neighbouring samples (17) extend one-dimensionally along two sides of the predetermined block (18), the predetermined samples are arranged in rows and columns and, along at least one of the rows and columns, the predetermined samples are positioned at every nth position from a sample (112) of the predetermined sample (112) adjoining the two sides of the predetermined block and the decoder is configured to, based on the plurality of neighbouring samples (17), determine for each of the at least one of the rows and the columns, a support value (118) for one (118) of the plurality of neighbouring positions, which is aligned to the respective one of the at least one of the rows and the columns, wherein the decoder is configured to derive, by interpolation, the prediction values for the further samples (108, 108’) of the predetermined block (18) on the basis of the predicted values for the predetermined samples (104, 118’, 118”) and the support values for the neighbouring samples (118) aligned to the at least one of rows and columns. 7. The decoder of claim 6, wherein the predetermined samples (104) are positioned at every nth position from the sample (112) of the predetermined sample (112) which adjoins the two sides of the predetermined block along the rows and the predetermined samples are positioned at every mth position from the sample (112) of the predetermined sample which (112) adjoins the two sides of the predetermined block (18) along the columns, wherein n, m>1. 8. The decoder of claim 7, wherein n=m. 9. The decoder of any of claims 6 to 8, configured to, along at least one of the rows (17c) and columns (17a), perform the determining of the support values by downsampling or averaging (122), for each support value, a group (120) of neighbouring samples within the plurality of neighbouring samples which includes the neighbouring sample (118) for which the respective support value is determined. 10. The decoder of any of claims 5 to 9, configured to perform the interpolation by bit-shifting. 11. The decoder of any of claims 1 to 10, wherein the plurality of neighbouring samples (17) extend one-dimensionally along two sides of the predetermined block (18) and the decoder is configured to perform the reduction (811) by grouping the plurality of neighbouring samples (17) into groups (110) of one or more consecutive neighbouring samples and performing a downsampling or an averaging on each of the group (110) of one or more neighbouring samples which has two or more than two neighbouring samples. 12. The decoder of any of claims 1 to 11, wherein the linear or affine linear transformation comprises PredQred or Pred*Q weighting factors with Pred being the number of sample values (102) within the reduced set (102) of sample values and Qred or Q is the number of predetermined samples within the predetermined block (18), wherein at least ¼ Pred*Qred or ¼ Pred*Q weighting factors are non-zero weighting values, which the Pred*Qred or Pred*Q weighting factors comprise, for each of the Q or Qred predetermined samples, a series of Pred weighting factors relating to the respective predetermined sample, wherein the series, when being arranged one below the other according to a raster scan order among the predetermined samples of the predetermined block (18), form an envelope which is omnidirectionally non-linear. 13. The decoder of claim 12, wherein the Pred*Q or Pred*Qred weighting factors are unrelated to each other via any regular mapping rule. 14. The decoder of claim 12 or 13, wherein a mean of maxima of cross correlations between a first series of weighting factors relating to the respective predetermined sample, and a second series of weighting factors relating to predetermined samples other than the respective predetermined sample, or a reversed version of the latter series, whatever leads to a higher maximum, is lower than a predetermined threshold. 15. The decoder of claim 14, wherein the predetermined threshold is 0.3. 16. The decoder of any of claims 12 to 15, wherein the Pred neighbouring samples (17) are located along a one-dimensional path extending along two sides of the predetermined block (18) and, for each of the Q or Qred predetermined samples, the series of Pred weighting factors relating to the respective predetermined sample are ordered in a manner traversing the one-dimensional path in a predetermined direction. 17. The decoder of any of claims 1 to 16, configured to derive, for the predetermined block (18), a prediction residual (34”) from the data stream (12), and reconstruct (42’) the predetermined block (18) using the prediction residual (34”) and the predicted values (24’) for the predetermined samples (24’, 104, 108, 108’). 18. The decoder of any of claims 10 to 17, configured to derive, for the predetermined block (18), a prediction residual (34”) from the data stream (12) in order to obtain for each of the set of Q or Qred predetermined samples a corresponding residual value, and reconstruct the predetermined block (18) using the prediction residual (34”) and the predicted values (24’, 104) for the predetermined samples (118’, 118”) by correcting the predicted value for each of the set of Q or Qred predetermined samples by the corresponding residual value (34”) to obtain a corresponding reconstructed value (10) so that the corresponding reconstructed value (10) depends on the Pred neighbouring samples (102) within the reduced set (102) of sample values strictly linearly except for, optionally, a clipping applied after prediction and/or correction. 19. The decoder of any of claims 1 to 18, wherein the decoder is configured to subdivide the picture (10) into a plurality of blocks of different block sizes, which comprises the predetermined block (18), wherein the decoder is configured to select the linear or affine linear transformation (19, 17M, Ak) depending on a width W and height H of the predetermined block (18) such that the linear or affine linear transformation selected for the predetermined block (18) is selected out of a first set of linear or affine linear transformations as long as the width W and height H of the predetermined block (81) are within a first set of width/height pairs and a second set of linear or affine linear transformations as long as the width W and height H of the predetermined block are within a second set of width/height pairs which is disjoint to the first set of width/height pairs. 20. The decoder of any of claims 1 to 19, wherein the decoder is configured to subdivide the picture (10) into a plurality of blocks of different block sizes, which comprises the predetermined block (18), wherein the decoder is configured to select the linear or affine linear transformation (19, 17M, Ak) depending on a width W and height H of the predetermined block (18) such that the linear or affine linear transformation selected for the predetermined block (18) is selected out of a first set (Si) of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a first set of width/height pairs, a second set (S2) of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a second set of width/height pairs which is disjoint to the first set of width/height pairs, and a third set (S0) of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a third set of one or more width/height pairs, which is disjoint to the first and second sets of width/height pairs. 21. The decoder of claim 20, configured so that the third set (So) of one or more width/height pairs merely comprises one width/height pair, W’, H’, and each linear or affine linear transformation within the third set (S0) of linear or affine linear transformations is for transforming N’ sample values to W’*H’ predicted values for an W’xH’ array of sample positions. 22. The decoder of claim 19, 20 or 21, configured so that each of the first and second sets (S1, S2) of width/height pairs comprises a first width/height pair Wp, Hp with Wp being unequal to Hp and a second width/height pair Wq, Hq with Hq=Wp and Wq=Hp. 23. The decoder of claim 22, configured so that each of the first and second sets (S1, S2) of width/height pairs additionally comprises a third width/height pair Wp, Hp with Wp being equal to Hp and Hp > Hq. 24. The decoder of any of claims 19 to 23, wherein same set of linear or affine linear transformations is shared by multiple pairs of width/height of the predetermined block. 25. The decoder of any of claims 1 to 23, configured to read for the predetermined block (18) a set index (944) from the data stream (12), select the linear or affine linear transformation depending on the set index (k) out of a predetermined set of linear or affine linear transformations. 26. The decoder of claim 25, wherein the plurality of neighbouring samples (17) extend one-dimensionally along two sides of the predetermined block (18) and the decoder is configured to perform the reduction (811) by, for a first subset (17a) of the plurality of neighbouring samples, which adjoin a first side of the predetermined block, grouping the first subset (17a) into first groups (110) of one or more consecutive neighbouring samples and, for a second subset (17c) of the plurality of neighbouring samples, which adjoin a second side of the predetermined block, grouping the second subset (17c) into second groups (110) of one or more consecutive neighbouring samples and performing a downsampling or an averaging on each of the first and second groups (110) of one or more neighbouring samples which has more than two neighbouring samples, so as to obtain first sample values (110) from the first groups (17a) and second sample values (102) for the second groups (17c), and the decoder being configured to select the linear or affine linear transformation depending on the set index out of a predetermined set of linear or affine linear transformations such that two different states of the set index result into a selection of one of the linear or affine linear transformations of the predetermined set of linear or affine linear transformations, and subject the reduced set (102) of sample values to the predetermined linear or affine linear transformation, in case of the set index assuming a first of the two different states in form of a first vector to yield an output vector of predicted values, and distribute the predicted values of the output vector along a first scan order onto the predetermined samples of the predetermined block, and in case of the set index assuming a second of the two different states in form of a second vector, the first and second vectors differing so that components populated by one of the first sample values in the first vector are populated by one of the second sample values in the second vector, and components populated by one of the second sample values in the first vector are populated by one of the first sample values in the second vector, so as to yield an output vector of predicted values, and distribute the predicted values of the output vector along a second scan order onto the predetermined samples of the predetermined block which is transposed relative to the first scan order. 27. The decoder of any of claims 18 to 26, wherein each linear or affine linear transformation within first set (S1) of linear or affine linear transformations is for transforming N1 sample values to wi*hi predicted values for an w1xh1 array of sample positions and each linear or affine linear transformation within second set (S2) of linear or affine linear transformations is for transforming N2 sample values to w2*h2 predicted values for an w2xh2 array of sample positions, and wherein for a first predetermined one of the first set (S1) of width/height pairs, w1 exceeds the width of the first predetermined width/height pair or h1 exceeds the height of the first predetermined width/height pair, and for a second predetermined one of the first set (S1) of width/height pairs neither W1 exceeds the width of the second predetermined width/height pair nor h1 exceeds the height of the second predetermined width/height pair, and wherein the decoder is configured to perform the reducing (100, 811), by downsampling or averaging, the plurality of neighbouring samples to obtain the reduced set (102) of samples values so that the reduced set (102) of samples values has N1 sample values if the predetermined block is of the first predetermined width/height pair and if the predetermined block is of the second predetermined width/height pair, and perform the subjecting (813) the reduced set (102) of sample values to the selected linear or affine linear transformation by using only a first sub-portion of the selected linear or affine linear transformation which is related to a subsampling of the W1xh1 array of sample positions along width dimension if wi exceeds the width of the one width/height pair, or along height dimension if h1 exceeds the height of the one width/height pair if the predetermined block is of the first predetermined width/height pair, and the selected linear or affine linear transformation completely if the predetermined block is of the second predetermined width/height pair. 28. The decoder of any of claims 1 to 27, wherein each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N1 sample values to W1*h1 predicted values for an W1*h1 array of sample positions with w1=h1 and each linear or affine linear transformation within second set of linear or affine linear transformations is for transforming N2 sample values to W2*h2 predicted values for an w2xh2 array of sample positions with W2=h2. 29. A decoding method, comprising: predicting a predetermined block (18) of the picture using a plurality of neighbouring samples (17) by reducing (100, 811), by downsampling or averaging, the plurality of neighbouring samples to obtain a reduced set (102) of samples values lower, in number of samples, than compared to the plurality of neighbouring samples, subjecting (812) the reduced set (102) of sample values to a linear or affine linear transformation (19) to obtain predicted values for predetermined samples (104, 118’, 188”) of the predetermined block. 30. Encoder for encoding a picture into a data stream, configured to predict a predetermined block (18) of the picture using a plurality of neighbouring samples (17a,c) by reducing (100, 811) the plurality of neighbouring samples to obtain a reduced set (102) of samples values lower, in number of samples, than compared to the plurality of neighbouring samples, subjecting (812) the reduced set (102) of sample values to a linear or affine linear transformation (19) to obtain predicted values for predetermined samples (104) of the predetermined block. 31. The encoder (54) of claim 30, further configured to perform the reducing (100, 811) by downsampling. 32. The encoder (54) of claim 30, further configured to perform the reducing (100, 811) by averaging. 33. The encoder of claim 32, wherein averaging includes bit-shifting. 34. The encoder of any of claims 30 to 33, configured to derive, by interpolation, prediction values for further samples (108) of the predetermined block on the basis of the predicted values for the predetermined samples and the plurality of neighbouring samples. 35. The encoder of claim 34, wherein the plurality of neighbouring samples extend one-dimensionally along two sides of the predetermined block, the predetermined samples are arranged in rows and columns and, along at least one of the rows and columns, the predetermined samples are positioned at every nth position from a sample (112) of the predetermined sample adjoining the two sides of the predetermined block and the encoder is configured to, based on the plurality of neighbouring samples, determine for each of the at least one of the rows and the columns, a support value for one (118) of the plurality of neighbouring positions, which is aligned to the respective one of the at least one of the rows and the columns, wherein the encoder is configured to derive, by interpolation, the prediction values for the further samples (108) of the predetermined block on the basis of the predicted values for the predetermined samples and the support values for the neighbouring samples aligned to the at least one of rows and columns. 36. The encoder of claim 35, wherein the predetermined samples are positioned at every nth position from the sample (112) of the predetermined sample which adjoins the two sides of the predetermined block along the rows and the predetermined samples are positioned at every mth position from the sample (112) of the predetermined sample which adjoins the two sides of the predetermined block along the columns, wherein n, m>1. 37. The encoder of claim 36, wherein n=m. 38. The encoder of any of claims 36 to 37, configured to, along at least one of the rows and column, perform the determining the support values by downsampling or averaging (122), for each support value, a group (120) of neighbouring samples within the plurality of neighbouring samples which includes the neighbouring sample (118) for which the respective support value is determined. 39. The encoder of any of claims 34 to 38, configured to perform the interpolation by bit-shifting. 40. The encoder of any of claims 30 to 39, wherein the plurality of neighbouring samples extend one-dimensionally along two sides of the predetermined block and the encoder is configured to perform the reduction by grouping the plurality of neighbouring samples into groups (110) of one or more consecutive neighbouring samples and performing a downsampling or an averaging on each of the group of one or more neighbouring samples which has more than two neighbouring samples. 41. The encoder of any of claims 30 to 40, wherein the linear or affine linear transformation comprises Pred*Qred or Pred*Q weighting factors with P being the number of sample values within the reduced set (102) of sample values and Q is the number predetermined samples within the predetermined block, wherein at least ¼ Pred*Qred or ¼ Pred*Q weighting factors are non-zero weighting values in which the PredQred or Pred*Q weighting factors comprise, for each of the Q or Qred predetermined samples, a series of Pred weighting factors relating to the respective predetermined sample, wherein the series, when being arranged one below the other according to a raster scan order among the predetermined samples of the predetermined block, form an envelope which is omnidirectionally non-linear. 42. The encoder of claim 41, wherein the Pred*Qred or Pred*Qweighting factors are unrelated to each other via any regular mapping rule. 43. The encoder of claim 41 or 42, wherein a mean of maxima of cross correlations between a first series of weighting factors relating to the respective predetermined sample, and a second series of weighting factors relating to predetermined samples other than the respective predetermined sample, or a reversed version of the latter series, whatever leads to a higher maximum, is lower than a predetermined threshold. 44. The encoder of claim 43, wherein the predetermined threshold is 0.3. 45. The encoder of any of claims 41 to 44, wherein the P neighbouring samples are located along a one-dimensional path extending along two sides of the predetermined block and, for each of the Q predetermined samples, the series of P weighting factors relating to the respective predetermined sample are ordered in a manner traversing the one-dimensional path in a predetermined direction. 46. The encoder of any of claims 30 to 45, configured to insert, for the predetermined block, a prediction residual into the data stream from which the predetermined block is reconstructible using the prediction residual and the predicted values for the predetermined samples. 47. The encoder of any of claims 41 to 46, configured to insert, for the predetermined block (18), a prediction residual (26, 34) into the data stream (12) which indicates for each of the Q or Qred predetermined samples a corresponding residual value so that the predetermined block (18) may be reconstructed using the prediction residual (26, 34) and the predicted values for the predetermined samples by correcting the predicted value / for each of the set of Q or Qred values so that the corresponding reconstructed value depends on the Pred neighbouring samples (102) within the reduced set (102) of sample values strictly linearly except for, optionally, a clipping applied after prediction and/or correction. 48. The encoder of any of claims 30 to 47, wherein the encoder is configured to subdivide the picture (16) into a plurality of blocks of different block sizes, which comprises the predetermined block (18), wherein the encoder is configured to select the linear or affine linear transformation (19, Ak) depending on a width W and height H of the predetermined block (18) such that the linear or affine linear transformation (19, Ak) selected for the predetermined block (18) is selected out of a first set of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a first set of width/height pairs and a second set of linear or affine linear transformations as long as the width W and height H of the predetermined block (18) are within a second set of width/height pairs which is disjoint to the first set of width/height pairs. 49. The encoder of any of claims 30 to 48, wherein the encoder is configured to subdivide the picture into a plurality of blocks of different block sizes, which comprises the predetermined block, wherein the encoder is configured to select the linear or affine linear transformation depending on a width W and height H of the predetermined block such that the linear or affine linear transformation selected for the predetermined block is selected out of a first set (S1) of linear or affine linear transformations as long as the width W and height H of the predetermined block are within a first set of width/height pairs, a second set (S2) of linear or affine linear transformations as long as the width W and height H of the predetermined block are within a second set of width/height pairs which is disjoint to the first set of width/height pairs, and a third set (S0) of linear or affine linear transformations as long as the width W and height H of the predetermined block are within a third set of (S0) one or more width/height pairs, which is disjoint to the first and second sets of width/height pairs. 50. The encoder of claim 49, configured so that the third set (So) of one or more width/height pairs merely comprises one width/height pair, W’, H’, and each linear or affine linear transformation within third set (S0) of linear or affine linear transformations is for transforming N’ sample values to W’*H’ predicted values for an W’xH’ array of sample positions. 51. The encoder of claim 47, 48, 49 or 50, configured so that each of the first and second sets of width/height pairs comprises a first width/height pairs Wp,Hp with Wp being unequal to Hp and a second width/height pair Wq,Hq with Hq=Wp and Wq=Hp. 52. The encoder of claim 51, configured so that each of the first and second sets of width/height pairs additionally comprises a third width/height pairs WP,HP with Wp being equal to Hp and Hp > Hq. 53. The encoder of any of claims 50 to 52, wherein same set of linear or affine linear transformations is shared by multiple pairs of width/height of the predetermined block. 54. The encoder of any of claims 30 to 52, configured to insert for the predetermined block a set index into the data stream, select the linear or affine linear transformation depending on the set index out of a predetermined set of linear or affine linear transformations. 55. The encoder of claim 54, wherein the plurality of neighbouring samples extend one-dimensionally along two sides of the predetermined block and the encoder is configured to perform the reduction by, for a first subset of the plurality of neighbouring samples, which adjoin a first side of the predetermined block, grouping the first subset into first groups (110) of one or more consecutive neighbouring samples and, for a second subset of the plurality of neighbouring samples, which adjoin a second side of the predetermined block, grouping the second subset into second groups (110) of one or more consecutive neighbouring samples and performing a downsampling or an averaging on each of the first and second groups of one or more neighbouring samples which has more than two neighbouring samples, so as to obtain first sample values from the first groups and second sample values for the second groups, and the encoder configured to select the linear or affine linear transformation depending on the set index out of a predetermined set of linear or affine linear transformations such that two different states of the set index result into a selection of one of the linear or affine linear transformations of the predetermined set of linear or affine linear transformations, and subject the reduced set (102) of sample values to the predetermined linear or affine linear transformation in case of the set index assuming a first of the two different states in form of a first vector to yield an output vector of predicted values, and distribute the predicted values of the output vector along a first scan order onto the predetermined samples of the predetermined block and in case of the set index assuming a second of the two different states in form of a second vector, the first and second vectors differing so that components populated by one of the first sample values in the first vector are populated by one of the second sample values in the second vector, and components populated by one of the second sample values in the first vector are populated by one of the first sample values in the second vector, so as to yield an output vector of predicted values, and distribute the predicted values of the output vector along a second scan order onto the predetermined samples of the predetermined block which is transposed relative to the first scan order. 56. The encoder of any of claims 47 to 55, wherein each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N1 sample values to w1*h1 predicted values for an wixhi array of sample positions and each linear or affine linear transformation within second set of linear or affine linear transformations is for transforming N2 sample values to w2*h2 predicted values for an w2xh2 array of sample positions, and wherein for a first predetermined one of the first set of width/height pairs, Wi exceeds the width of the first predetermined width/height pair or hi exceeds the height of the first predetermined width/height pair, and for a second predetermined one of the first set of width/height pairs neither wi exceeds the width of the second predetermined width/height pair nor hi exceeds the height of the second predetermined width/height pair, and wherein the encoder is configured to perform the reducing (100), by downsampling or averaging, the plurality of neighbouring samples to obtain the reduced set (102) of samples values so that the reduced set (102) of samples values has N1 sample values if the predetermined block is of the first predetermined width/height pair and if the predetermined block is of the second predetermined width/height pair, and perform the subjecting the reduced set (102) of sample values to the selected linear or affine linear transformation by using only a first sub-portion of the selected linear or affine linear transformation which is related to a subsampling of the w1xh1 array of sample positions along width dimension if w1 exceeds the width of the one width/height pair, or along height dimension if h1 exceeds the height of the one width/height pair if the predetermined block is of the first predetermined width/height pair, and the selected linear or affine linear transformation completely if the predetermined block is of the second predetermined width/height pair. 57. The encoder of any of claims 29 to 56, wherein each linear or affine linear transformation within first set of linear or affine linear transformations is for transforming N1 sample values to w1*h1 predicted values for an w1xh1 array of sample positions with w1=h1 and each linear or affine linear transformation within second set of linear or affine linear transformations is for transforming N2 sample values to w2*h2 predicted values for an w2xh2 array of sample positions with w2=h2. 58. An encoding method comprising predicting a predetermined block (18) of the picture using a plurality of neighbouring samples (17a, 17c) by reducing (100), by downsampling or averaging, the plurality of neighbouring samples to obtain a reduced set (102) of samples values lower, in number of samples, than compared to the plurality of neighbouring samples, subjecting the reduced set (102) of sample values to a linear or affine linear transformation (19) to obtain predicted values for predetermined samples (104) of the predetermined block. 59. A system comprising an encoder according to any of the preceding claims and/or a decoder according to any of the preceding claims. 60. A method comprising an encoding method according to any of the preceding claims and a decoding method according to any of the preceding claims. 61. A non-transitory storage unit storing instructions which, when executed by a processor, cause the processor to perform a method according to any of the preceding claims.