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Low-complexity lossless compression of hyperspectral images using scalar coset codes

This paper is available in a repository.
This paper is available in a repository.

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Abstract

In this paper we propose a new algorithm for lossless compres- sion of remote sensing images, based on distributed source cod- ing. The objective of this algorithm is to achieve low-complexity encoding, with compression performance as close as possible to a full-complexity coder. The complexity reduction is obtained by coding each spectral channel separately, whereas high coding effi- ciency is achieved through joint decoding. Experimental results on hyperspectral images show that the proposed algorithm has signifi- cantly better performance than JPEG-LS, with similar complexity. We also provide profiling results on a LEON-3 architecture.