Study of hyperspectral and multispectral image compression using vector quantization in development of CCSDS international standards

Shen-En Qian

doi:10.1117/12.830094

28 September 2009 Study of hyperspectral and multispectral image compression using vector quantization in development of CCSDS international standards

Shen-En Qian

Author Affiliations +

Proceedings Volume 7477, Image and Signal Processing for Remote Sensing XV; 74770O (2009) https://doi.org/10.1117/12.830094
Event: SPIE Remote Sensing, 2009, Berlin, Germany

Abstract

The Consultative Committee for Space Data System (CCSDS) is developing new international standards for satellite multispectral and hyperspectral data compression. The Canadian Space Agency's Successive Approximation Multi- Stage Vector Quantization (SAMVQ) has been selected as a candidate. The preliminary evaluation results show that the SAMVQ produces competitive rate-distortion performance on the CCSDS test images acquired by the hyperspectral sensors and hyperspectral sounders. There is a constraint to achieve lower bit rates on the multispectral images when the SAMVQ is applied to them due to the small number of bands. This is because the SAMVQ was designed for compression of hyperspectral imageries, which contain much more spectral bands than the multispectral images. This paper briefly reports the compression results of the SAMVQ on the CCSDS hyperspectral and hyperspectral sounders test images and studies on how to enhance the capability of the SAMVQ for compressing multispectral images while maintaining its unique properties for hyperspectral images.

Citation Download Citation

Shen-En Qian "Study of hyperspectral and multispectral image compression using vector quantization in development of CCSDS international standards", Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 74770O (28 September 2009); https://doi.org/10.1117/12.830094

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