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18 October 1999 Lossless compression of multispectral images based on a bidirectional spectral prediction
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Abstract
When multispectral images are being losslessly compressed, if the inter-band correlation of the data is weak, as it usually occurs for data with few and sparse spectral bands, a 3D prediction may lead to negligible coding benefits. In this case, advantage may be taken from a bidirectional spectral prediction, in which once the (k - 1)st band is available, first the kth band is skipped and the (k + 1)st band is predicted from the (k - 1)st one; then, both these two bands are used to predict the kth band in a spatially causal but spectrally noncausal fashion. Starting from an extremely sophisticated and effective scheme for multispectral prediction based on fuzzy-logic concepts, the causal and noncausal 3D prediction strategies are compared and discussed varying with the spectral correlations of the data. Experiments on Landsat TM data show that a certain gain in bit rate can be obtained at no additional cost, by simply devising a scan order in which some bands are preliminarily skipped and then bidirectionally predicted.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bruno Aiazzi, Luciano Alparone, and Stefano Baronti "Lossless compression of multispectral images based on a bidirectional spectral prediction", Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); https://doi.org/10.1117/12.365844
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