VST-based Lossy Compression of Hyperspectral Data for New Generation Sensors

Abstract : This paper addresses lossy compression of hyperspectral images acquired by sensors of new generation for which signal-dependent component of the noise is prevailing compared to the noise-independent component. First, for sub-band (component-wise) compression, it is shown that there can exist an optimal operation point (OOP) for which MSE between compressed and noise-free image is minimal, i.e., maximal noise filtering effect is observed. This OOP can be observed for two approaches to lossy compression where the first one presumes direct application of a coder to original data and the second approach deals with applying direct and inverse variance stabilizing transform (VST). Second, it is demonstrated that the second approach is preferable since it usually provides slightly smaller MSE and slightly larger compression ratio (CR) in OOP. One more advantage of the second approach is that the coder parameter that controls CR can be set fixed for all sub-band images. Moreover, CR can be considerably (approximately twice) increased if sub-band images after VST are grouped and lossy compression is applied to a first sub-band image in a group and to "difference" images obtained for this group. The proposed approach is tested for Hyperion hyperspectral images and shown to provide CR about 15 for data compression in the neighborhood of OOP.
Type de document :
Communication dans un congrès
Conference on Image and Signal Processing for Remote Sensing XIX, Sep 2013, Dresde, Germany. 8892, pp.UNSP 88920L, 2013, Proceedings of SPIE. 〈10.1117/12.2028415〉
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-00959558
Contributeur : Yolande Sambin <>
Soumis le : vendredi 14 mars 2014 - 16:34:37
Dernière modification le : mercredi 16 mai 2018 - 11:23:49

Identifiants

Citation

Alexander Zemliachenko, Ruslan Kozhemiakin, Mikhail Uss, Sergey Abramov, Vladimir Lukin, et al.. VST-based Lossy Compression of Hyperspectral Data for New Generation Sensors. Conference on Image and Signal Processing for Remote Sensing XIX, Sep 2013, Dresde, Germany. 8892, pp.UNSP 88920L, 2013, Proceedings of SPIE. 〈10.1117/12.2028415〉. 〈hal-00959558〉

Partager

Métriques

Consultations de la notice

92