An evaluation framework and a benchmark for multi/hyperspectral image compression

Jonathan Delcourt 1 Alamin Mansouri 2, * Tadeusz Sliwa 2 Yvon Voisin 2
* Auteur correspondant
1 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes
2 Le2i - Laboratoire Electronique, Informatique et Image
Abstract : This paper benchmarks three multi/hyperspectral image compression approaches: the classic Multi-2D compression approach and two different implementations of 3D approach (Full 3D and Hybrid). All approaches are combined with a spectral PCA decorrelation stage to optimize performance. These three compression approaches are compared within a larger comparison framework than the conventionally used PSNR, which includes eight metrics divided into three families. The comparison is carried out with regard to variations in bitrates, spatial, and spectral dimensions variations of images. The time and memory consumption difference between the three approaches is also discussed. Results of this comparison show the weaknesses and strengths of each approach.
Keywords : Multi/hyperspectral images compression wavelets
Type de document :
Article dans une revue
Computer Vision Graphics and Image Processing, Elsevier, 2011, 1 (1), pp.55-71. <10.4018/ijcvip.2011010105>
Liste complète des métadonnées

https://hal-univ-bourgogne.archives-ouvertes.fr/hal-00637853
Contributeur : Alamin Mansouri <>
Soumis le : jeudi 3 novembre 2011 - 10:31:43
Dernière modification le : mercredi 24 juin 2015 - 11:00:53
Document(s) archivé(s) le : samedi 4 février 2012 - 02:22:39

Fichier

IJCVIP.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

LE2I | UNAM | IRCCYN | IRCCYN-ADTSI

Citation

Jonathan Delcourt, Alamin Mansouri, Tadeusz Sliwa, Yvon Voisin. An evaluation framework and a benchmark for multi/hyperspectral image compression. Computer Vision Graphics and Image Processing, Elsevier, 2011, 1 (1), pp.55-71. <10.4018/ijcvip.2011010105>. <hal-00637853>

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de
la notice

477

Téléchargements du document

227

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD