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 into the proposed model by… More >
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