Improved prediction for lossless compression of multispectral images

We study the use of spectral deltas for lossless multispectral image compression. Spectral deltas are differences between prediction errors. When bands are correlated, the prediction errors between the two bands are similar, thus the difference results in a smaller value. Building upon earlier work, we examine methods of detecting correlations and harnessing current advances in lossless still image compression. The result is an algorithm that works well over a broad set of test images.