NDLI: SVD-Based Image De-Nosing with the Minimum Engergy Model

Content Provider	IEEE Xplore Digital Library
Author	Shi, Z.L. Zhang, Z.J. Tang, Y.T.
Copyright Year	2006
Description	Author affiliation: Shenyany Inst. of Autom., Shenyang (Shi, Z.L.)
Abstract	This paper proposes a new solution integrating energy function into singular value decomposition (SVD) for image de-noising. The singular values on the diagonal matrix obtained through SVD represent different components in image. By selecting the proper singular values that represent signal and discarding the ones that represent noise, the additive noise of an image can be eliminated effectively. In order to obtain the optimal number of the singular values for image reconstruction and to eliminate the noise, the paper presents a minimum energy model. This model is used to obtain the optimum number for de-noising through calculating the minimum in the defined energy curve. The experiment results show that the established model is effective in the circumstance that the image has simple/regular structure/pattern.
Starting Page	1
Ending Page	7
File Size	3282145
Page Count	7
File Format	PDF
ISBN	1889335339
DOI	10.1109/WAC.2006.375745
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-24
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	TSI Press
Subject Keyword	Matrix decomposition Optical noise Singular value decomposition Automation Image denoising Image reconstruction Additive noise Image coding Educational institutions Noise reduction Minimum energy model Image de-nosing SVD
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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