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Hyperspectral image compression based on tucker decomposition and wavelet transform

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3 Author(s)
Karami, A. ; Dept. of Commun. & Electron., Shiraz Univ., Shiraz, Iran ; Yazdi, M. ; Mercier, G.

The compression of hyperspectral images becomes recently very attractive issue for remote sensing applications because of the volumetric data. In this paper, an efficient method for hyperspectral image compression is presented based on Tucker Decomposition (TD) and Discrete Wavelet Transform (DWT). The core idea behind our proposed technique is to apply TD on the DWT coefficients of spectral bands of hyperspectral images. Our method not only exploits redundancies between bands but also uses spatial correlation of every image band. Simulation results applied on the real hyperspectral images show a remarkable compression ratio and quality.

Published in:

Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011 3rd Workshop on

Date of Conference:

6-9 June 2011

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