Paper
18 August 2005 Adaptive clustering for hyperspectral sounder data compression
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Abstract
In this paper, which is part of an ongoing sequence of papers devoted to the subject of efficient noise-tolerant lossless compression of satellite data for transmission, we describe an algorithm for this purpose which effectively addresses the above criteria. Our algorithm exhibit the potential to achieve noise-tolerant compression ratios averaging 3.2 : 1. An earlier approach, which we presented at Third GOES-R User Conference in May of 2004, was the first such method to break the 3 to 1 compression barrier for this class of data.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
I. Gladkova, L. Roytman, and M. Goldberg "Adaptive clustering for hyperspectral sounder data compression", Proc. SPIE 5889, Satellite Data Compression, Communications, and Archiving, 588907 (18 August 2005); https://doi.org/10.1117/12.618085
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Data compression

Satellites

Principal component analysis

Visualization

Algorithm development

Data conversion

Image segmentation

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