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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Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 27; no. 11; pp. 5625 - 5637
Main Authors:	Han, Xian-Hua, Shi, Boxin, Zheng, Yinqiang
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.11.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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
Online Access:	Get full text
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