Self-Similarity Constrained Sparse Representation for Hyperspectral Image Super-Resolution

Fusing a low-resolution hyperspectral (HS) image with the corresponding high-resolution multispectral image to obtain a high-resolution HS image is an important technique for capturing comprehensive scene information in both the spatial and spectral domains. Existing approaches adopt sparsity promot...

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Vydáno v:	IEEE transactions on image processing Ročník 27; číslo 11; s. 5625 - 5637
Hlavní autoři:	Han, Xian-Hua, Shi, Boxin, Zheng, Yinqiang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.11.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Convex functions Dictionaries dictionary learning global-structure self-similarity High resolution Hyper-spectral image super-resolution Hyperspectral imaging Image reconstruction Image resolution local-spectral self-similarity non-negative sparse coding Outliers (statistics) Pixels Representations Self-similarity Similarity Spatial resolution Spectra Visual effects
ISSN:	1057-7149, 1941-0042, 1941-0042
On-line přístup:	Získat plný text
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