Fast relative Newton algorithm for blind deconvolution of images

Alexander M. Bronstein; Michael Zibulevsky; Yehoshua Y. Zeevi; Michael M. Bronstein

Fast relative Newton algorithm for blind deconvolution of images

Alexander M. Bronstein^*, Michael Zibulevsky, Yehoshua Y. Zeevi, Michael M. Bronstein

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

Abstract

We present an efficient Newton-like algorithm for quasi-maximum likelihood (QML) blind deconvolution of images. This algorithm exploits the sparse structure of the Hessian. An optimal distribution-shaping approach by means of sparsification allows one to use simple and convenient sparsity prior for processing of a wide range of natural images. Simulation results demonstrate the efficiency of the proposed method.

Original language	English
Pages (from-to)	1233-1236
Number of pages	4
Journal	Proceedings - International Conference on Image Processing, ICIP
Volume	5
State	Published - 2004
Externally published	Yes
Event	2004 International Conference on Image Processing, ICIP 2004 - , Singapore Duration: 18 Oct 2004 → 21 Oct 2004

Cite this

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title = "Fast relative Newton algorithm for blind deconvolution of images",

abstract = "We present an efficient Newton-like algorithm for quasi-maximum likelihood (QML) blind deconvolution of images. This algorithm exploits the sparse structure of the Hessian. An optimal distribution-shaping approach by means of sparsification allows one to use simple and convenient sparsity prior for processing of a wide range of natural images. Simulation results demonstrate the efficiency of the proposed method.",

author = "Bronstein, {Alexander M.} and Michael Zibulevsky and Zeevi, {Yehoshua Y.} and Bronstein, {Michael M.}",

year = "2004",

language = "אנגלית",

volume = "5",

pages = "1233--1236",

journal = "Proceedings - International Conference on Image Processing, ICIP",

issn = "1522-4880",

note = "null ; Conference date: 18-10-2004 Through 21-10-2004",

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TY - JOUR

T1 - Fast relative Newton algorithm for blind deconvolution of images

AU - Bronstein, Alexander M.

AU - Zibulevsky, Michael

AU - Zeevi, Yehoshua Y.

AU - Bronstein, Michael M.

PY - 2004

Y1 - 2004

N2 - We present an efficient Newton-like algorithm for quasi-maximum likelihood (QML) blind deconvolution of images. This algorithm exploits the sparse structure of the Hessian. An optimal distribution-shaping approach by means of sparsification allows one to use simple and convenient sparsity prior for processing of a wide range of natural images. Simulation results demonstrate the efficiency of the proposed method.

AB - We present an efficient Newton-like algorithm for quasi-maximum likelihood (QML) blind deconvolution of images. This algorithm exploits the sparse structure of the Hessian. An optimal distribution-shaping approach by means of sparsification allows one to use simple and convenient sparsity prior for processing of a wide range of natural images. Simulation results demonstrate the efficiency of the proposed method.

UR - http://www.scopus.com/inward/record.url?scp=20444493214&partnerID=8YFLogxK

M3 - מאמר מכנס

AN - SCOPUS:20444493214

VL - 5

SP - 1233

EP - 1236

JO - Proceedings - International Conference on Image Processing, ICIP

JF - Proceedings - International Conference on Image Processing, ICIP

SN - 1522-4880

Y2 - 18 October 2004 through 21 October 2004

ER -

Fast relative Newton algorithm for blind deconvolution of images

Abstract

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