Transform-based lossy compression has a huge potential for hyperspectral data reduction. In this paper we propose a lossy compression scheme for hyperspectral data based on a new low-complexity version of the Karhunen-Loève transform, in which complexity and performance can be balanced in a scalable way, allowing one to choose the best trade off that better matches a specific application. Moreover, we integrate this transform in the framework of Part 2 of the JPEG 2000 standard, taking advantage of the high coding efficiency of JPEG 2000, and exploiting the interoperability of an international standard. I.
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Penna et al. (2006) studied this question.
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