Leilei Geng1, Chaoran Cui1, Qiang Guo1, Sijie Niu2, Guoqing Zhang3, Peng Fu4, *
CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 913-928, 2020, DOI:10.32604/cmc.2020.09975
Abstract The multispectral remote sensing image (MS-RSI) is degraded existing multispectral camera due to various hardware limitations. In this paper, we propose a novel core
tensor dictionary learning approach with the robust modified Gaussian mixture model for
MS-RSI restoration. First, the multispectral patch is modeled by three-order tensor and
high-order singular value decomposition is applied to the tensor. Then the task of MS-RSI
restoration is formulated as a minimum sparse core tensor estimation problem. To improve
the accuracy of core tensor coding, the core tensor estimation based on the robust modified
Gaussian mixture model is introduced More >
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