Block-based KLT compression for multispectral images

摘要

An efficient lossy compression algorithm for multispectral images based on block Karhunen-Loeve transform (KLT) is proposed. First, a two-dimensional discrete wavelet transform is performed on each band of multispectral images to remove the spatial correlation. Subsequently, each band is partitioned into non-overlapping blocks of the same size, and the transform coefficients of each block in the wavelet domain are treated as a single object. Blocks that are co-located in the spectral orientation are affected by an adaptive Karhunen-Loeve transform to remove their spectral correlation. Finally, embedded block coding with optimized truncation is performed on all principal components to generate the final bit-stream. Experimental results show that the proposed algorithm, based on block KLT, outperforms the algorithm based on global KLT, without significant increase of complexity.