Linear prediction in lossless compression of hyperspectral images

Jarno S. Mielikainen; Pekka J. Toivanen; Arto Kaarna

doi:10.1117/1.1557174

1 April 2003 Linear prediction in lossless compression of hyperspectral images

Jarno S. Mielikainen, Pekka J. Toivanen, Arto Kaarna

Optical Engineering, Vol. 42, Issue 4, (April 2003). https://doi.org/10.1117/1.1557174

This study proposes an interband version of the linear prediction approach for hyperspectral images. Linear prediction represents one of the best performing and most practical and general purpose lossless image compression techniques known today. The interband linear prediction method consists of two stages: predictive decorrelation producing residuals, and entropy coding of these residuals. Our method achieved an average compression ratio of 3.23 using 13 airborne visible/infrared imaging spectrometer (AVIRIS) images.

©(2003) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Jarno S. Mielikainen, Pekka J. Toivanen, and Arto Kaarna "Linear prediction in lossless compression of hyperspectral images," Optical Engineering 42(4), (1 April 2003). https://doi.org/10.1117/1.1557174

Published: 1 April 2003

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