Enhancing image denoising by controlling noise incursion in learned dictionaries

Enhancing image denoising by controlling noise incursion in learned dictionaries

Existing image denoising frameworks via sparse representation using learned dictionaries have an weakness that the dictionary, trained from noisy image, suffers from noise incursion. This paper analyzes this noise incursion, explicitly derives the noise component in the dictionary update step, and p...

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Main Authors: Anamitra Makur (EEE), Sahoo, Sujit Kumar
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2015
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Online Access:https://hdl.handle.net/10356/107084
http://hdl.handle.net/10220/25303
http://dx.doi.org/10.1109/LSP.2015.2388712
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Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-107084
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spelling sg-ntu-dr.10356-1070842019-12-06T22:24:23Z Enhancing image denoising by controlling noise incursion in learned dictionaries Anamitra Makur (EEE) Sahoo, Sujit Kumar School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Existing image denoising frameworks via sparse representation using learned dictionaries have an weakness that the dictionary, trained from noisy image, suffers from noise incursion. This paper analyzes this noise incursion, explicitly derives the noise component in the dictionary update step, and provides a simple remedy for a desired signal to noise ratio. The remedy is shown to perform better both in objective and subjective measures for lesser computation, and complements the framework of image denoising. Accepted version 2015-03-30T08:51:54Z 2019-12-06T22:24:23Z 2015-03-30T08:51:54Z 2019-12-06T22:24:23Z 2015 2015 Journal Article Sujit, K. S., & Anamitra Makur. (2015). Enhancing image denoising by controlling noise incursion in learned dictionaries. IEEE signal processing letters, 22(8), 1123-1126. https://hdl.handle.net/10356/107084 http://hdl.handle.net/10220/25303 http://dx.doi.org/10.1109/LSP.2015.2388712 183149 en IEEE signal processing letters © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/LSP.2015.2388712]. 4 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Anamitra Makur (EEE)
Sahoo, Sujit Kumar
Enhancing image denoising by controlling noise incursion in learned dictionaries
description Existing image denoising frameworks via sparse representation using learned dictionaries have an weakness that the dictionary, trained from noisy image, suffers from noise incursion. This paper analyzes this noise incursion, explicitly derives the noise component in the dictionary update step, and provides a simple remedy for a desired signal to noise ratio. The remedy is shown to perform better both in objective and subjective measures for lesser computation, and complements the framework of image denoising.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Anamitra Makur (EEE)
Sahoo, Sujit Kumar
format Article
author Anamitra Makur (EEE)
Sahoo, Sujit Kumar
author_sort Anamitra Makur (EEE)
title Enhancing image denoising by controlling noise incursion in learned dictionaries
title_short Enhancing image denoising by controlling noise incursion in learned dictionaries
title_full Enhancing image denoising by controlling noise incursion in learned dictionaries
title_fullStr Enhancing image denoising by controlling noise incursion in learned dictionaries
title_full_unstemmed Enhancing image denoising by controlling noise incursion in learned dictionaries
title_sort enhancing image denoising by controlling noise incursion in learned dictionaries
publishDate 2015
url https://hdl.handle.net/10356/107084
http://hdl.handle.net/10220/25303
http://dx.doi.org/10.1109/LSP.2015.2388712
_version_ 1681046932531707904

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