Paper
14 March 2005 Image transmission system using adaptive joint source and channel decoding
Author Affiliations +
Proceedings Volume 5685, Image and Video Communications and Processing 2005; (2005) https://doi.org/10.1117/12.585513
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
In this paper, an adaptive joint source and channel decoding method is designed to accelerate the convergence of the iterative log-dimain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec, which makes it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. Due to the error resilience modes, some bits are known to be either correct or in error. The positions of these bits are then fed back to the channel decoder. The log-likelihood ratios (LLR) of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. That is, for lower channel SNR, a larger factor is assigned, and vice versa. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the non-source controlled decoding method up to 5dB in terms of PSNR for various reconstructed images.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Weiliang Liu and David G. Daut "Image transmission system using adaptive joint source and channel decoding", Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); https://doi.org/10.1117/12.585513
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Cited by 2 scholarly publications.
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KEYWORDS
Signal to noise ratio

JPEG2000

Error analysis

Image transmission

Data compression

Image compression

Lawrencium

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