Wavelet image coding using blockwise binary classification and trellis coded quantization
Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference（2000）
Abstract
With blockwise binary classification and data partitioning, we convert the image subbands to the type of source data for which the trellis coded quantization (TCQ) has the best quantization performance. Compared to the arithmetic coded TCQ (ACTCQ) and other TCQ-based coding schemes, the proposed algorithm significantly reduces the computational complexity. However, it performs competitively with the best available coding algorithms reported in the literature with regard to the rate-distortion performance.
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Key words
computational complexity,image classification,image coding,quantisation (signal),rate distortion theory,transform coding,trellis codes,wavelet transforms,tcq,blockwise binary classification,computational complexity reduction,data partitioning,image subbands,rate-distortion performance,trellis coded quantization,wavelet image coding,arithmetic coding,binary classification
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