LDPC-coded transmission system for lossless compressed hyperspectral image over Rayleigh channel

Xuye Wang; Piming Ma; Yanhua Ma

doi:10.1117/12.901033

15 August 2011 LDPC-coded transmission system for lossless compressed hyperspectral image over Rayleigh channel

Xuye Wang, Piming Ma, Yanhua Ma

Proceedings Volume 8196, International Symposium on Photoelectronic Detection and Imaging 2011: Space Exploration Technologies and Applications; 81961U (2011) https://doi.org/10.1117/12.901033
Event: International Symposium on Photoelectronic Detection and Imaging 2011, 2011, Beijing, China

Abstract

In this paper, a useful lossless compression method of hyperspectral remote sensing images is presented, which combines three-dimension adaptive predictor (3-DAP) and JPEG-LS algorithm. By using LDPC codes as the error-correction scheme, a compressed image transmission system with high spectral efficiency is proposed over Rayleigh fading channel. Linear programming (LP) decoding of LDPC codes is widely concerned for its maximum likelihood features and the maximum likelihood (ML) decoding for LDPC codes can be relaxed to an LP optimization problem. Therefore, the paper focus on an efficient algorithm called infeasible primal-dual interior-point (IPDIP) algorithm for solving LP problem with predictor-corrector technique. This technique decreases the amount of infeasible points and keeps them closing to the central path. Simulation results show that the lossless compression algorithm can reconstruct the hyperspectral image completely with higher compression ratio than JPEG-LS's. Moreover, the image transmission system achieves good bit error rate (BER) performance and good global convergence properties with less iteration number and time.

Citation Download Citation

Xuye Wang, Piming Ma, and Yanhua Ma "LDPC-coded transmission system for lossless compressed hyperspectral image over Rayleigh channel", Proc. SPIE 8196, International Symposium on Photoelectronic Detection and Imaging 2011: Space Exploration Technologies and Applications, 81961U (15 August 2011); https://doi.org/10.1117/12.901033

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KEYWORDS

Image compression

Image transmission

Hyperspectral imaging

Computer programming

Signal to noise ratio

Image restoration

Remote sensing

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