Abstract
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.