SUBBAND IMAGE CODING U SING E NTROPY-CODED QUANTIZATION OVER NOISY C HANNELS t
Naoto Tanabe, Nariman Farvardin · 1990
In this paper, we study the design and performance of two entropy-coded subband image coding schemes. The difference between these schemes is the procedure used for encoding the lowest frequency subband: predictive coding is used in one system and transform coding in the other. Other subbands are encoded using zero-memory quantization. It is shown that, in the absence of channel noise, both schemes perform better than other known subband coding schemes. After demonstrating the unacceptable sensitivity of these schemes to transmission noise, we will develop a combined source/channel coding scheme in which rate-compatible punctured convolutional codes are used to provide protection against channel noise. We will show that, in the presence of channel noise, these channel-optimized schemes offer dramatic performance improvements over the schemes designed based on a noiseless channel assumption.