NDLI: A new approach in decomposition over multiple-overcomplete dictionaries with application to image inpainting

Content Provider	IEEE Xplore Digital Library
Author	Valiollahzadeh, S.-M. Nazari, M. Babaie-Zadeh, M. Jutten, C.
Copyright Year	2009
Description	Author affiliation: Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran (Valiollahzadeh, S.-M.; Babaie-Zadeh, M.) \|\| Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran (Nazari, M.) \|\| GIPSA-lab, Grenoble, France and Institut Universitaire de France, France (Jutten, C.)
Abstract	Recently, great attention was intended toward overcomplete dictionaries and the sparse representations they can provide. In a wide variety of signal processing problems, sparsity serves a crucial property leading to high performance. Decomposition of a given signal over two or more dictionaries with sparse coefficients is investigated in this paper. This kind of decomposition is useful in many applications such as inpainting, denoising, demosaicing, speech source separation, high-quality zooming and so on. This paper addresses a novel technique of such a decomposition and investigates this idea through inpainting of images which is the process of reconstructing lost or deteriorated parts of images or videos.When samples are missed in an image, the the original sparsity level in representing coefficients is changed, so with an iterative method we can estimate the original level. Simulations are presented to demonstrate the validation of our approach.
Starting Page	1
Ending Page	6
File Size	2120573
Page Count	6
File Format	PDF
ISBN	9781424449477
ISSN	15512541
DOI	10.1109/MLSP.2009.5306206
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-01
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Image reconstruction Noise reduction Filling Time of arrival estimation Signal processing Speech Source separation Iterative methods Signal resolution
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A new approach in decomposition over multiple-overcomplete dictionaries with application to image inpainting.

Sparse decomposition over multi-component redundant dictionaries

A new approach in decompisition over multiple-overcomplete dictionaries with application to image inpainting

A noise robust algorithm for underdetermined source separation

A new method for signal sparse decomposition

A new approach in decompisition over multiple-overcomplete dictionaries with application to image inpainting

Sparse Regression with Structured Priors: Application to Audio Denoising

A sparse signal reconstruction perspective for source localization with sensor arrays

Super-Resolution Direction-of-Arrival Estimation via Blind Signal Separation Methods

A new approach in decomposition over multiple-overcomplete dictionaries with application to image inpainting

Similar Documents

A new approach in decomposition over multiple-overcomplete dictionaries with application to image inpainting.

Sparse decomposition over multi-component redundant dictionaries

A new approach in decompisition over multiple-overcomplete dictionaries with application to image inpainting

A noise robust algorithm for underdetermined source separation

A new method for signal sparse decomposition

A new approach in decompisition over multiple-overcomplete dictionaries with application to image inpainting

Sparse Regression with Structured Priors: Application to Audio Denoising

A sparse signal reconstruction perspective for source localization with sensor arrays

Super-Resolution Direction-of-Arrival Estimation via Blind Signal Separation Methods

A new approach in decomposition over multiple-overcomplete dictionaries with application to image inpainting