Learning Locality-Constrained Sparse Coding for Spectral Enhancement of Multispectral Imagery

Owing to easy acquisition and large coverage from the space, multispectral (MS) imaging has garnered growing interest in various applications of remote sensing. However, the limited spectral information of MS data, to a great extent, leads to difficulties in classifying the materials more accurately...

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Vydáno v:	IEEE geoscience and remote sensing letters Ročník 19; s. 1 - 5
Hlavní autoři:	Hong, Danfeng, Wu, Xin, Gao, Lianru, Zhang, Bing, Chanussot, Jocelyn
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Coding Constraints Hyperspectral (HS) Hyperspectral imaging Image coding Image enhancement Image reconstruction Imagery locality multispectral (MS) Optimization partially Performance assessment Remote sensing remote sensing (RS) Signal resolution sparse coding Spatial resolution Spectra spectral enhancement Spectral resolution Task analysis
ISSN:	1545-598X, 1558-0571
On-line přístup:	Získat plný text
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