JOURNAL ARTICLE

Image coding with channel-optimized trellis-coded quantization for channels with memory

Abstract

This paper presents a wavelet-based image coder that is optimized for transmission over binary channels with memory. The proposed coder uses a channel-optimized trellis-coded quantizer (COTCQ) designed for a binary first-order Markov channel. The quantizer stage exploits the channel memory by incorporating the characteristics of the additive correlated channel noise during the quantizer design and by using a new trellis structure. The performance of the proposed memory-optimized COTCQ (MCOTCQ) image coding system is presented for different bit error probabilities and noise correlation parameters. It is shown that the performance of the coder is significantly improved when the second-order statistics of the noise are taken into account at the quantizer design level.

Keywords:
Computer science Algorithm Quantization (signal processing) Trellis (graph) Channel (broadcasting) Binary number Coding (social sciences) Decoding methods Additive white Gaussian noise Trellis modulation Speech recognition Mathematics Telecommunications Arithmetic Statistics Fading

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5
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0.18
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Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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