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Proceedings Paper

Multispectral satellite image compression based on multimode linear prediction
Author(s): Wen-Nung Lie; Chun-Hung Chen; Chi-Fa Chen
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Paper Abstract

In this paper, we propose a multi-mode linear prediction (MM_LP) scheme for the compression of multi-spectral satellite images. This scheme, extending our prior work on block-based single mode linear prediction, discards the prediction residuals and transforms the traditional residual-encoding problem into another mode-map encoding problem. The increase in the extra storage for more coefficients is nearly negligible and the compression of mode-map might be expected to have a higher efficiency than the residuals can achieve. We also propose an alternative scheme to hide the mode information in the LSB (least significant bit) of the residual data, which are then encoded to give a nearly lossless compression with PSNR larger than 51 dB (error variance (sigma) 2 equals 0.5/per pixel). Comprehensive experiments justify performance of our MM_LP schemes and recommend that MM_LP (k >= 2) is suitable for PSNR less than 41.5 dB; single-mode LP (k equals 1) is for PSNR between 41.5 dB and 50 dB, while 2-mode mode- embedding approach is for PSNR > 50 dB.

Paper Details

Date Published: 30 May 2000
PDF: 8 pages
Proc. SPIE 4067, Visual Communications and Image Processing 2000, (30 May 2000); doi: 10.1117/12.386686
Show Author Affiliations
Wen-Nung Lie, National Chung Cheng Univ. (Taiwan)
Chun-Hung Chen, National Chung Cheng Univ. (Taiwan)
Chi-Fa Chen, I-Shou Univ. (Taiwan)


Published in SPIE Proceedings Vol. 4067:
Visual Communications and Image Processing 2000
King N. Ngan; Thomas Sikora; Ming-Ting Sun, Editor(s)

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