NDLI: Hyperspectral image denoising using 3D wavelets

Content Provider	IEEE Xplore Digital Library
Author	Rasti, B. Sveinsson, J.R. Ulfarsson, M.O. Benediktsson, J.A.
Copyright Year	2012
Description	Author affiliation: University of Iceland, Faculty of Electrical and Computer Engineering, Hjardarhagi 2-6. IS-107 Reykjavik, Iceland (Rasti, B.; Sveinsson, J.R.; Ulfarsson, M.O.; Benediktsson, J.A.)
Abstract	In this paper, we propose a denoising method for hyperspectral images using 3D wavelets. We use the sparse analysis regularization using a 3D overcomplete wavelet dictionary. The minimization problem is solved using iterative Chambolle algorithm. The simulation results show that the 3D dictionary outperforms the 2D one, in terms of Peak Signal to Noise Ratio (PSNR). Denosing hysperspectral cubes is likely to increase the classification accuracy of the hyperspectral data since it can enhance the spectral profiles (or features) that can be useful to discriminate between information classes.
Starting Page	1349
Ending Page	1352
File Size	183377
Page Count	4
File Format	PDF
ISBN	9781467311601
ISSN	21536996
e-ISBN	9781467311595
e-ISBN	9781467311588
DOI	10.1109/IGARSS.2012.6351286
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	Wavelet transforms Dictionaries Hyperspectral imaging Noise reduction PSNR sparse regularization Hyperspectral image 3D wavelets denoising overcomplete dictionary
Content Type	Text
Resource Type	Article

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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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