Design Trees For Adaptive Coding Of Images And Videos Using Set Partitioning In Generalized Hierarchical Trees Having Directionality

Abstract: Adaptive entropy encoding and decoding which utilizes Set Partitioning within Generalized Hierarchical Trees (SPRIGHT) and a method of designing trees utilizing directionality. After decorrelation and quantization a tree structure is selected from multiple candidates  based on geometric relationships within the image block  for coding the coefficients toward improving zero-clustering of coefficients. Trees for the SPRIGHT encoding are created in response to finding frequency position of each coefficient and scaling frequency position followed by use of octave-band partitioning of coefficient patterns into squares and L-shapes  and the L-shapes are iteratively partitioned into squares. The tree comprises leaf nodes containing coefficients associated with each non-leaf node. The number of zero clustered coefficients can be increased  thus decreasing the number of nodes coded into the encoded image output.

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