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Journal of Applied Remote Sensing

Anisotropy regularization-based restoration of imaging process in line-scanning spectrometer
Author(s): Ran Wei; Ye Zhang; Yushi Chen
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Paper Abstract

Hyperspectral image (HSI) restoration is a technique to inverse the information degradation process that occurs on a hyperspectral imaging system, i.e., spectrometer. Spectrometers can be classified as two types: plane-scanning and line-scanning spectrometers. It is necessary for a restoration algorithm to match the corresponding degradation process. However, most current restoration algorithms are only suitable to the former one. To solve such a mismatch of restoration algorithms to the imaging process in this paper, a new framework of HSI restoration is proposed. Compared to the existing frameworks, the proposed one is more applicable to a line-scanning spectrometer. Moreover, to solve the ill-posedness of such a framework, an anisotropy regularization term combining a vertical total variation and a linear spectral mixture is designed. Experimental results based on two simulation datasets, Pavia and San Diego, proved the effectiveness of the proposed framework and regularization term.

Paper Details

Date Published: 28 May 2015
PDF: 17 pages
J. Appl. Remote Sens. 9(1) 095078 doi: 10.1117/1.JRS.9.095078
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Ran Wei, Harbin Institute of Technology (China)
Ye Zhang, Harbin Institute of Technology (China)
Yushi Chen, Harbin Institute of Technology (China)


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