An integrated framework for adaptive subband image coding

作     者：Pavlovic, V Moulin, P Ramchandran, K 

作者机构：Compaq Comp Corp Cambridge Res Lab Cambridge MA 02139 USA Univ Illinois Beckman Inst Urbana IL 61801 USA Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA 

出 版 物：《IEEE TRANSACTIONS ON SIGNAL PROCESSING》 (IEEE Trans Signal Process)

年 卷 期：1999年第47卷第4期

页      面：1024-1038页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：National Science Foundation, NSF, (MIP 97-073181, MIP-97-07633) National Science Foundation, NSF 

主　　题：adaptive coding best basis methods filter banks image compression rate-distortion methods subband coding vector quantization 

摘      要：Recent work on filter banks and related expansions has revealed an interesting insight: Different filter bank trees can be regarded as different ways of constructing orthonormal bases: for linear signal expansion, In particular, fast algorithms for finding best bases in an operational rate-distortion (R/D) sense hare been successfully used in image coding, Independently of this work, recent research has also explored the design of filter banks that optimize energy compaction for a single signal or a class of signals. In this paper, we integrate these two different but complementary approaches to best-basis design and propose a coding paradigm in which subband filters, tree structure, and quantizers are chosen to optimize R/D performance, These coder attributes represent side information. They are selected from a codebook designed off-line from training data, using RID as the design criterion. This approach provides a rational framework in which to explore alternatives to empirical design of filter banks, quantizers, and other coding parameters. The on-line coding algorithm is a relatively simple extension of current R/D-optimal coding algorithms that operate,vith fixed filter banks and empirically designed quantizer codebooks. In particular, it is shown that selection of the best adapted filter bank from the codebook is computationally elementary.