Transform image coding based on joint adaptation of filter banks and tree structures

Recent work on lter banks and related expansions has revealed an interesting insight: diierent lter bank trees can be regarded as diierent ways of constructing or-thonormal bases for linear signal expansion. In particular , fast algorithms for nding best bases in an operational rate-distortion sense have been successfully used in image coding. Independently of this work, recent research has also explored the design of lter banks that optimize energy compaction for a single signal or a class of signals. In this paper we integrate these two diierent but complementary approaches to best-basis design and propose an image coder in which subband lter banks, tree structure and quantizers are chosen so as to optimize rate-distortion performance. These optimal lter banks, tree structure and quantizers represent side information. They are selected from a codebook designed from training data, using a rate-distortion criterion.