Wyner-Ziv coding of multispectral images for space and airborne platforms

Abstract

This paper investigates the application of lossy distributed source coding to high resolution multispectral images. The choice of distributed source coding is motivated by the need for very low encoding complexity on space and airborne platforms. The data consists of red, blue, green and infra-red channels and is compressed in an asymmetric Wyner-Ziv setting. One image channel is compressed using traditional JPEG and transmitted to the ground station where it is available as side information for Wyner-Ziv coding of the other channels. Encoding is accomplished by quantizing the image data, applying a Low-Density Parity Check code to the remaining three image channels, and transmitting the resulting syndromes. At the ground station, the image data is recovered from the syndromes by exploiting the correlation in the frequency spectrum of the band being decoded and the JPEG-decoded side information band. In experiments with real uncompressed images obtained by a satellite, the rate-distortion performance is found to be vastly superior to JPEG compression of individual image channels and rivals that of JPEG2000 at much lower encoding complexity. Picture Coding Symposium (PCS) This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c ©Mitsubishi Electric Research Laboratories, Inc., 2010 201 Broadway, Cambridge, Massachusetts 02139

DOI: 10.1109/PCS.2010.5702474

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Cite this paper

@inproceedings{Rane2010WynerZivCO, title={Wyner-Ziv coding of multispectral images for space and airborne platforms}, author={Shantanu Rane and Yige Wang and Petros Boufounos and Anthony Vetro}, booktitle={PCS}, year={2010} }