6533b870fe1ef96bd12cf95e

RESEARCH PRODUCT

A Comparative Study and an Evaluation Framework of Multi/Hyperspectral Image Compression

Tadeusz SliwaJonathan DelcourtYvon VoisinAlamin Mansouri

subject

Set partitioning in hierarchical treesWaveletPixelbusiness.industryPrincipal component analysisMultispectral imageWavelet transformHyperspectral imagingPattern recognitionArtificial intelligencebusinessDecorrelationMathematics

description

In this paper, we investigate different approaches for multi/hyperspectral image compression. In particular, we compare the classic multi-2D compression approach and two different implementations of 3D approach (full 3D and hybrid) with regards to variations in spatial and spectral dimensions. All approaches are combined with a weighted Principal Component Analysis (PCA) decorrelation stage to optimize performance. For consistent evaluation, we propose a larger comparison framework than the conventionally used PSNR, including eight metrics divided into three families. The results show the weaknesses and strengths of each approach.

yearjournalcountryeditionlanguage
2009-11-012009 Fifth International Conference on Signal Image Technology and Internet Based Systems
https://doi.org/10.1109/sitis.2009.23