Compression Of High Spectral Resolution Imagery'

Richard L. Baker; Yi Tong Tse

doi:10.1117/12.948466

16 December 1988 Compression Of High Spectral Resolution Imagery'

Richard L. Baker, Yi Tong Tse

Proceedings Volume 0974, Applications of Digital Image Processing XI; (1988) https://doi.org/10.1117/12.948466
Event: 32nd Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1988, San Diego, CA, United States

Abstract

NASA will acquire billions of gigabytes of data over the next decade. Often there is a problem just funneling the data down to earth. The 80 foot long Earth Orbiting Satellite (EOS), scheduled for launch in the mid-1990s, is a prime example. EOS will include a next generation multispectral imaging system (HIRIS) having unprecedented spatial and spectral resolution. Its high resolution, however, comes at the cost of a raw data rate which exceeds the communication channel capacity assigned to the entire EOS mission. This paper explores noisy compression algorithms which may compress multispectral data by up to 30:1 or more. Algorithm performance is measured using both traditional (mse) and mission-oriented criteria (e.g., feature classification consistency). We show that vector quantization, merged with suitable preprocessing techniques, emerges as the most viable candidate.

Citation Download Citation

Richard L. Baker and Yi Tong Tse "Compression Of High Spectral Resolution Imagery'", Proc. SPIE 0974, Applications of Digital Image Processing XI, (16 December 1988); https://doi.org/10.1117/12.948466

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