NDLI: Noise reduction of hyperspectral imagery using nonlocal sparse representation with spectral-spatial structure

Content Provider	IEEE Xplore Digital Library
Author	Yuntao Qian Minchao Ye Qi Wang
Copyright Year	2012
Description	Author affiliation: Institute of Artificial Intelligence, College of Computer Science, Zhejiang University, Hangzhou 310027, China (Yuntao Qian; Minchao Ye; Qi Wang)
Abstract	Noise reduction is always an active research area in image processing due to its importance for the sequential tasks such as object classification and detection. In this paper, we develop a sparse representation based noise reduction method for hyperspectral imagery, which is dependent on the assumption that the non-noise component in the signal can be approximated by only a small number of atoms in a dictionary while noise component has not this property. The main contribution of the paper is in introducing nonlocal similarity and spectral-spatial structure of hyperspectral imagery into sparse representation. Non-locality means the self-similarity of image, by which the whole image can be partitioned into some groups containing similar patches. The similar patches in each group is sparsely represented with shared atoms making the signal and noise more easily separated. Sparse representation with spectral-spatial structure can exploit spectral and spatial joint correlations of hyperspectral imagery also making the signal and noise more distinguished, in which 3-D blocks are instead of 2-D patches for sparse coding. The experimental results indicate that the proposed method has a good quality of restoring the true signal from the noisy observation.
Starting Page	3467
Ending Page	3470
File Size	1102204
Page Count	4
File Format	PDF
ISBN	9781467311601
ISSN	21536996
e-ISBN	9781467311595
e-ISBN	9781467311588
DOI	10.1109/IGARSS.2012.6350674
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-22
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Abstracts Encoding spectral-spatial structure Hyperspectral imagery noise reduction sparse representation nonlocal similarity
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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