Multiple wavelet-tree-based image coding and robust transmission

Lei Cao; Chang Wen Chen

doi:10.1117/12.577932

25 October 2004 Multiple wavelet-tree-based image coding and robust transmission

Lei Cao, Chang Wen Chen

Proceedings Volume 5600, Multimedia Systems and Applications VII; (2004) https://doi.org/10.1117/12.577932
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States

Abstract

In this paper, we present techniques based on multiple wavelet-tree coding for robust image transmission. The algorithm of set partitioning in hierarchical trees (SPIHT) is a state-of-the-art technique for image compression. This variable length coding (VLC) technique, however, is extremely sensitive to channel errors. To improve the error resilience capability and in the meantime to keep the high source coding efficiency through VLC, we propose to encode each wavelet tree or a group of wavelet trees using SPIHT algorithm independently. Instead of encoding the entire image as one bitstream, multiple bitstreams are generated. Therefore, error propagation is limited within individual bitstream. Two methods based on subsampling and human visual sensitivity are proposed to group the wavelet trees. The multiple bitstreams are further protected by the rate compatible puncture convolutional (RCPC) codes. Unequal error protection are provided for both different bitstreams and different bit segments inside each bitstream. We also investigate the improvement of error resilience through error resilient entropy coding (EREC) and wavelet tree coding when channels are slightly corruptive. A simple post-processing technique is also proposed to alleviate the effect of residual errors. We demonstrate through simulations that systems with these techniques can achieve much better performance than systems transmitting a single bitstream in noisy environments.

Citation Download Citation

Lei Cao and Chang Wen Chen "Multiple wavelet-tree-based image coding and robust transmission", Proc. SPIE 5600, Multimedia Systems and Applications VII, (25 October 2004); https://doi.org/10.1117/12.577932

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KEYWORDS

Wavelets

Data compression

Image compression

Visualization

Forward error correction

Image quality

Error analysis

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