Abstract

This paper examines the compression benefits that can be obtained by reordering the bands of a multispectral image. In particular, we consider a model of lossless image compression in which each band of a multispectral image is coded using a prediction function involving values from a previously coded band of the compression. Clearly, the ordering of the bands determines which bands can be used for prediction, and this in turn can strongly influence compression performance. This paper presents an efficient algorithm for computing the optimal band ordering for a multispectral image. This algorithm has time complexity O(n 2 ) for an n-band image, while the naive algorithm takes time\Omega\Gamma n!). We also define a slight variant of the optimal ordering problem that is motivated by some practical concerns on band extraction, and prove that this problem is NP-hard in all cases except for the most trivial possibility. In addition, we report on our experimental findings using the algori...

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