Compression of the interferential multispectral image based on distributed source coding

Juan Song; Yunsong Li; Chengke Wu; Ying Feng

doi:10.1117/12.794351

5 September 2008 Compression of the interferential multispectral image based on distributed source coding

Juan Song, Yunsong Li, Chengke Wu, Ying Feng

Proceedings Volume 7084, Satellite Data Compression, Communication, and Processing IV; 70840G (2008) https://doi.org/10.1117/12.794351
Event: Optical Engineering + Applications, 2008, San Diego, California, United States

Abstract

A novel compression method for interferential multispectral images based on distributed source coding is proposed. Slepian-Wolf and Wyner-Ziv theorems on source coding with side information are taken as the basic coding principles. In our system, a rate control solution is proposed to avoid the feedback channel used in many practical distributed source coding solutions. The residual statistics between corresponding coefficients in original frame and the side information frame is assumed to be modeled by Laplacian distribution. We estimate the distribution parameter on line at the encoder at subband levels. The experimental results show that our method outperforms significantly over JPEG2000, especially at medium and low bit rates, the method can obtain about 5dB gains than JPEG2000, and the subjective quality is obviously enhanced.

Citation Download Citation

Juan Song, Yunsong Li, Chengke Wu, and Ying Feng "Compression of the interferential multispectral image based on distributed source coding", Proc. SPIE 7084, Satellite Data Compression, Communication, and Processing IV, 70840G (5 September 2008); https://doi.org/10.1117/12.794351

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KEYWORDS

Computer programming

Data compression

Image compression

JPEG2000

Multispectral imaging

Image enhancement

Image quality

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