Title :
A hyperspectral image restoration technique
Author :
Zhang, Yifan ; Duijster, Arno ; Scheunders, Paul
Author_Institution :
Dept. of Phys., Univ. of Antwerp, Wilrijk, Belgium
Abstract :
In this paper, a restoration technique for hyperspectral images is presented. The technique requires a low spatial resolution hyperspectral image and a high spatial resolution multispectral image of the same scene. The proposed approach applies a restoration on the hyperspectral image, while accounting for the joint statistics with the multispectral image. The restoration is based on an Expectation-Maximization algorithm, which applies a deconvolution step and a denoising step iteratively. A practical implementation scheme is presented. Simulation experiments are conducted for performance evaluation.
Keywords :
deconvolution; expectation-maximisation algorithm; image denoising; image fusion; image restoration; deconvolution step; denoising step; expectation-maximization algorithm; high spatial resolution; hyperspectral images; image restoration; joint statistics; low spatial resolution; multispectral image; Deconvolution; Hyperspectral imaging; Hyperspectral sensors; Image fusion; Image restoration; Layout; Multispectral imaging; Noise reduction; Spatial resolution; Statistics; Expectation-Maximization (EM); Hyperspectral image; deconvolution; fusion; restoration;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5414587