Paper
13 March 1996 Error-resilient image compression based on JPEG
Prashant P. Gandhi, Wade E. Darlington, Howard L. Dyckman
Author Affiliations +
Proceedings Volume 2669, Still-Image Compression II; (1996) https://doi.org/10.1117/12.234760
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
Abstract
JPEG-compressed images, when transmitted over a noisy channel, are highly susceptible to errors. The effects of bit errors on images compressed by any method, including JPEG, are significantly augmented since the majority of statistical redundancies are removed in the compression process. Furthermore, errors affecting the run-lengths and Huffman codewords within JPEG have a much more profound influence on reconstructed images than those affecting only coefficient values. This paper presents a detailed investigation of uncompressed and JPEG-compressed (baseline and progressive) image transmission in noisy channels. Several modifications within JPEG are proposed to improve reconstructed image quality. Among the techniques investigated, a hybrid technique, combining the concepts of the baseline and progressive JPEG modes, appears to give the best performance. Here, the DC coefficients (with absolute and/or fixed bit encoding), AC codewords, and some positional information are separately coded and protected using forward error correction. The actual AC coefficient values are sent separately. This partitioning of codewords and values enable isolating, for special protection, portions of the representation that are highly sensitive to errors and that may cause lengthy error propagation. It enables sending `view-quality' images in the presence of a channel bit error rate as high as 0.01.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Prashant P. Gandhi, Wade E. Darlington, and Howard L. Dyckman "Error-resilient image compression based on JPEG", Proc. SPIE 2669, Still-Image Compression II, (13 March 1996); https://doi.org/10.1117/12.234760
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Cited by 3 scholarly publications.
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KEYWORDS
Image compression

Image segmentation

Image quality

Computer programming

Error analysis

Image processing

Visualization

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