ADAPTIVE ENTROPY CODING FOR IMAGES AND VIDEOS USING SET PARTITIONING IN GENERALIZED HIERARCHICAL TREES

摘要

Adaptive entropy encoding and decoding utilizing set partitioning within generalized hierarchical trees which is applicable to both embedded and non- embedded encoding. After decorrelation and quantization during encoding, a tree structure is selected from multiple candidates, based on geometric relationships within the image block, for coding the coefficients toward improving coefficient zero clustering. The tree structure has leaf and non-leaf nodes in a specified arrangement, with leaf nodes containing coefficients associated with each non-leaf node. By proper tree selection, the number of zero clustered coefficients which may be eliminated from the encoded output stream is increased. During decoding, a tree structure compatible with the encoding for the current block is used for decoding the existing coefficients from the symbol stream and restoring missing zero coefficients.