NDLI: Image deconvolution using multigrid natural image prior and its applications

Content Provider	IEEE Xplore Digital Library
Author	Tingbo Hou Sen Wang Hong Qin Miller, R.L.
Copyright Year	2010
Description	Author affiliation: Department of Computer Science, Stony Brook University, USA (Tingbo Hou; Hong Qin) \|\| Kodak Research Laboratories, Eastman Kodak Company, USA (Sen Wang; Miller, R.L.)
Abstract	The natural image prior has been proven to be a powerful tool for image deblurring in recent years, though its performance against noise in various applications has not been thoroughly studied. In this paper, we present a multigrid natural image prior for image deconvolution that enhances its robustness against noise, and afford three applications of image deconvolution using this prior: deblurring, super-resolution, and denoising. The prior is based on a remarkable property of natural images that derivatives with different resolutions are subject to the same heavy-tailed distribution with a spatial factor. It can serve in both blind and non-blind deconvolutions. The performances of the proposed prior in different applications are demonstrated by corresponding experimental results.
Starting Page	3569
Ending Page	3572
File Size	830063
Page Count	4
File Format	PDF
ISBN	9781424479924
ISSN	15224880
e-ISBN	9781424479948
e-ISBN	9781424479931
DOI	10.1109/ICIP.2010.5651083
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-26
Publisher Place	Hong Kong
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Deconvolution Image resolution Kernel Noise reduction Pixel PSNR image denoising Image deblurring natural image prior super-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

Image deconvolution using multigrid natural image prior and its applications.

Handling noise in image deconvolution with local/non-local priors

A new total variation based image denoising and deblurring technique

Multi image super resolution using compressed sensing

Video deblurring in complex wavelet domain using local Laplace prior for enhancement and anisotropic spatially adaptive denoising for PSF detection

A study on some techniques for denoising and blind deconvolution of color images

Image deblurring and denoising using color priors

Noisy Radial Deblurring Using Natural Image Prior

Image deblurring in super-resolution framework

Image deconvolution using multigrid natural image prior and its applications

Similar Documents

Image deconvolution using multigrid natural image prior and its applications.

Handling noise in image deconvolution with local/non-local priors

A new total variation based image denoising and deblurring technique

Multi image super resolution using compressed sensing

Video deblurring in complex wavelet domain using local Laplace prior for enhancement and anisotropic spatially adaptive denoising for PSF detection

A study on some techniques for denoising and blind deconvolution of color images

Image deblurring and denoising using color priors

Noisy Radial Deblurring Using Natural Image Prior

Image deblurring in super-resolution framework

Image deconvolution using multigrid natural image prior and its applications