Anisotropy regularization-based restoration of imaging process in line-scanning spectrometer

Ran Wei; Ye Zhang; Yushi Chen

doi:10.1117/1.JRS.9.095078

28 May 2015 Anisotropy regularization-based restoration of imaging process in line-scanning spectrometer

Ran Wei, Ye Zhang, Yushi Chen

Author Affiliations +

Funded by: Natural Science Foundation of China

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 095078 (May 2015). https://doi.org/10.1117/1.JRS.9.095078

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.

Citation Download Citation

Ran Wei, Ye Zhang, and Yushi Chen "Anisotropy regularization-based restoration of imaging process in line-scanning spectrometer," Journal of Applied Remote Sensing 9(1), 095078 (28 May 2015). https://doi.org/10.1117/1.JRS.9.095078

Published: 28 May 2015

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