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

Jianfei Cai, Chang Wen Chen

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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 = 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.

Original languageEnglish
Title of host publicationProceedings of the 1999 Visual Communications and Image Processing
PublisherSPIE - International Society for Optical Engineering
Pages208-217
Number of pages10
Volume3653
EditionI
Publication statusPublished - 1999
Externally publishedYes
EventVisual Communications and Image Processing 1999 - San Jose, United States of America
Duration: 25 Jan 199927 Jan 1999

Conference

ConferenceVisual Communications and Image Processing 1999
CountryUnited States of America
CitySan Jose
Period25/01/9927/01/99

Cite this

Cai, J., & Chen, C. W. (1999). Uniform threshold TCQ with block classification for image transmission over noisy channels. In Proceedings of the 1999 Visual Communications and Image Processing (I ed., Vol. 3653, pp. 208-217). SPIE - International Society for Optical Engineering.