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Proceedings Paper

Enhancement of resilience to bit-errors of compressed data on-board a hyperspectral satellite using forward error correction
Author(s): Pirouz Zarrinkhat; Shen-En Qian
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Paper Abstract

To deal with the huge volume of data produced by hyperspectral sensors, the Canadian Space Agency (CSA) has developed two simple and fast algorithms for compressing hyperspectral data, namely Successive Approximation Multistage Vector Quantization (SAMVQ) and Hierarchical Self-Organizing Cluster Vector Quantization (HSOCVQ). The CSA intends to use these algorithms, which are capable of providing high compression rates, on-board a proposed Canadian hyperspectral satellite. It has been shown that both SAMVQ and HSOCVQ are near-lossless compression algorithms as their designs restrict compression errors to levels consistent with the level of the intrinsic noise in the original hyperspectral data. Although both of them are more bit-error resistant than the traditional compression algorithms, when the bit-error rate (BER) exceeds 10-6, the compression fidelity starts to drop apparently. This paper explores the benefits of employing forward error correction on top of data compression, by SAMVQ or HSOCVQ, to deal with higher BERs. In particular, it is shown that by proper use of convolutional codes, the resilience of compressed hyperspectral data against bit errors can be improved by close to two orders of magnitude.

Paper Details

Date Published: 5 September 2008
PDF: 9 pages
Proc. SPIE 7084, Satellite Data Compression, Communication, and Processing IV, 708407 (5 September 2008); doi: 10.1117/12.798499
Show Author Affiliations
Pirouz Zarrinkhat, Canadian Space Agency (Canada)
Shen-En Qian, Canadian Space Agency (Canada)


Published in SPIE Proceedings Vol. 7084:
Satellite Data Compression, Communication, and Processing IV
Bormin Huang; Roger W. Heymann; Joan Serra-Sagristà, Editor(s)

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