A block Karhunen–Loève Transform based efficient lossy compression algorithm for optical remote sensing imagery. Issue 10 (3rd October 2017)

• Record Type: Journal Article
• Authors: Kumar, Satish; Dhadwal, Vipin
• Is Part Of: Geocarto international. Volume 32:Issue 10(2017)
• Page Start: 1159
• Page End: 1170
• Publication Date: 2017-10-03
• Subjects: Remote sensing -- multispectral imagery -- lossy compression -- spectral de-correlation; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2016.1195887
• Languages: English
• ISSNs: 1010-6049

Abstract

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).