Abstract
In present study, a block Karhunen–Loève Transform (KLT) based efficient lossy compression algorithm for optical remote sensing imagery is proposed. A Discrete Wavelet Transform (DWT) is performed on each band of the imagery to remove the spatial correlation. Each band of the imagery is decomposed into non-overlapping blocks of similar size and the transform coefficients of each block in the wavelet domain are treated as a single object. A rate-distortion optimization is introduced to perform rate allocation of multiple bands. Each band is partitioned into code-blocks. The embedded block coding with optimized truncation algorithm is executed on the code-blocks to produce final bit-stream. The complexity of the proposed algorithm is compared with global KLT-DWT. The result reports the complexity of JPEG 2000 (Part 1) is lowest with encoding time 114 ms as compared to global KLT-DWT (N = 1024), global DWT-KLT (N = 1024), block-based DWT-KLT (N = 512), block-based DWT-KLT (N = 256), block-based DWT-KLT (N = 128), block-based DWT-KLT (N = 64) and block-based DWT-KLT (N = 32).
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