Band selection for lossless image compression

Shawn D. Hunt; Miguel Velez-Reyes

doi:10.1117/12.437053

20 August 2001 Band selection for lossless image compression

Shawn D. Hunt, Miguel Velez-Reyes

Proceedings Volume 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII; (2001) https://doi.org/10.1117/12.437053
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

Lossless compression algorithms typically do not use spectral prediction, and typical algorithms that do, use only one adjacent band. Using one adjacent band has the disadvantage that if the last band compressed is needed, all previous bands must be decompressed. One way to avoid this is to use a few selected bands to predict the others. Exhaustive searches for band selection have a combinatorial problem, and are therefore not possible except in the simplest cases. To counter this, the use of a fast approximate method for band selection is proposed. The bands selected by this algorithm are a reasonable approximation to the principal components. Results are presented for exhaustive studies using entropy measures, sum of squared errors, and compared to the fast algorithm for simple cases. Also, it was found that using six bands selected by the fast algorithm produces comparable performance to one adjacent band.

Citation Download Citation

Shawn D. Hunt and Miguel Velez-Reyes "Band selection for lossless image compression", Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); https://doi.org/10.1117/12.437053

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