Tensor non-local low-rank regularization for recovering compressed hyperspectral images

Sparsity-based methods have been widely used in hyperspectral imagery compression recovery (HSI-CR). However, most of the available HSI-CR methods work on vector space by vectorizing hyperspectral cubes in spatial and spectral domain, which will destroy spatial and spectral correlation and result in...

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Vydané v:	2017 IEEE International Conference on Image Processing (ICIP) s. 3046 - 3050
Hlavní autori:	Zhao, Yongqiang, Xue, Jize, Hao, Jinglei
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.09.2017
Predmet:	alternative direction multiplier method compression recovery Correlation Hyperspectral image Hyperspectral imaging Image coding Image reconstruction Matrix decomposition non-local self-similarity structured sparsity Tensile stress tensor low-rank approximation Three-dimensional displays
ISSN:	2381-8549
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