28 May 2015 Anisotropy regularization-based restoration of imaging process in line-scanning spectrometer
Author Affiliations +
J. of Applied Remote Sensing, 9(1), 095078 (2015). doi:10.1117/1.JRS.9.095078
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.
© 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)
Ran Wei, Ye Zhang, 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



Image processing

Data processing

Imaging systems

3D modeling

Hyperspectral imaging


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