Multi-spectral satellite image compression based on multi-mode linear prediction

in this paper, we propose a multi-mode linear prediction (MM_LP) scheme for the compression of multi-spectral satellite images. This scheme, extending our prior work on block-based single mode linear prediction [7], discards the prediction residuals and transforms the traditional residual-encoding problem into another mode-map encoding problem. The increase in the extra storage for more coefficients is nearly negligible and the compression of mode-map might be expected to have a higher efficiency than the residuals can achieve. We also propose an alternative scheme to hide the mode information in the LSB (least significant bit) of the residual data, which are then encoded to give a nearly lossless compression with PSNR larger than 51 dB (error variance sigma(2) = 0.5/per pixel). Comprehensive experiments justify performance of our MM_LP schemes and recommend that MM_LP (k greater than or equal to 2) is suitable for PSNR less than 41.5 dB; single-mode LP (k = 1) is for PSNR between 41.5 dB and 50 dB, while 2-mode mode-embedding approach is for PSNR > 50 dB.