Lossy compression of hyperspectral images using online learning based sparse coding

Abstract

A lossy hyperspectral image compression method is proposed using online learning based sparse coding. The least number of coefficients are obtained to represent hyperspectral images by applying the sparse coding algorithm which is based on a dicriminative online dictionary learning method. Results indicate that a pre-analysis of the number of non-zero dictionary elements may help in improving the overall compression quality.