Publicou 12 edições por ano
ISSN Imprimir: 0040-2508
ISSN On-line: 1943-6009
Indexed in
AN AUTOMATIC APPROACH TO LOSSY COMPRESSION OF AVIRIS HYPERSPECTRAL DATA
RESUMO
In this paper we design and study an automatic approach to lossy compression of AVIRIS hyperspectral data. This approach takes into account the statistical characteristics of noise in component images as well as the considerable inter-channel correlation of data. An automatic method to estimate the noise variance in component images is proposed, and its performance is studied. It is shown that the accuracy of the variance estimates is appropriate for further use. Then, the selection of compression parameters of an advanced DCT-based coder, AGU, for componentwise (2-D) and group-wise (3-D) lossy compression of hyperspectral data is discussed. These two ways of lossy compression are compared for a set of standard AVIRIS images. We demonstrate that channel grouping with respect to estimated noise variances allows minimizing distortions and provides compression ratios which are approximately twice larger than in component-wise automatic lossy compression. It is shown that for AVIRIS images the achieved compression ratios can be of the order 7...29. Moreover, we demonstrate that for those subbands where noise is relatively intensive, noise attenuation is provided simultaneously with data compression whilst for other subband images no visible distortions are introduced by our lossy coder.
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Lukin Vladimir V., Methods and automatic procedures for processing images based on blind evaluation of noise type and characteristics, Journal of Applied Remote Sensing, 5, 1, 2011. Crossref
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Lukin V.V., Zemliachenko A.N., Tchobanou M.K., Efficiency of lossy compression of noisy and pre-filtered remote sensing images, 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves, 2013. Crossref