Reduction of Interband Correlation for Landsat Image Compression

Daniel G. AcevedoAna M. C. Ruedin

We present a lossless compressor for multispectral images that exploits interband correlations. Each band is divided into blocks, to which a wavelet transform is applied. The wavelet coefficients are predicted by means of a linear combination of coefficients belonging to the same orientation and spatial location. The prediction errors are then encoded with an entropy - based coder. Our original contributions are i) the inclusion, among the candidates for prediction, of coefficients of the same location from other spectral bands, ii) the calculation of weights tuned to the landscape being processed, iii) a fast block classification and a different band-ordering for each landscape. Our compressor reduces the size of an image to about a fourth of its original size. Our method is equivalent to LOCO-I, on 3 of the images tested it was superior. It is superior to other lossless compressors: WinZip, JPEG2000 and PNG.

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