Uniform-threshold TCQ with block classification for image transmission over noisy channels

Jianfei Cai; Chang Wen Chen

doi:10.1117/12.334668

28 December 1998 Uniform-threshold TCQ with block classification for image transmission over noisy channels

Jianfei Cai, Chang Wen Chen

Proceedings Volume 3653, Visual Communications and Image Processing '99; (1998) https://doi.org/10.1117/12.334668
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

Abstract

A combined source-channel coding scheme without explicit error protection is proposed to transmit images over noisy channels. Major components of the proposed coding scheme include 2-D DCT with block classification, fixed-length uniform threshold trellis coded quantization (UTTCQ), optimal bit allocation algorithm and noise reduction (NR) filters. The integration of these components allows us to organize the compressed bitstream in such a way that it is less sensitive to channel noise, and hence achieves data compression and error resilience at the same time. This paper reports our recent study by incorporating the block classification into the integrated scheme. Experimental results show that, in the case of noise-free channels and at the bit rate of 0.5 bpp, an improvement of 2.33 dB can be achieved with the classification. In the case of noisy channels, the gain is decreasing with the increasing of bit error rate to an average improvement of 0.46 dB with BER equals 0.1. Our proposed system uses no error protection, no synchronization codewords and no entropy coding. However, it shows decent compression ratio and gracious degradation with respect to increasing channel errors.

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Jianfei Cai and Chang Wen Chen "Uniform-threshold TCQ with block classification for image transmission over noisy channels", Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); https://doi.org/10.1117/12.334668

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KEYWORDS

Image compression

Quantization

Image transmission

Denoising

Image classification

Digital filtering

Algorithm development

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