Noisy image restoration by cost function minimization

Eli Harouche; Shmuel Peleg; Haim Shvaytser; Larry S. Davis

doi:10.1016/0167-8655(85)90044-3

Noisy image restoration by cost function minimization

Eli Harouche^*, Shmuel Peleg, Haim Shvaytser, Larry S. Davis

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Implementation of a new approach to the nonlinear noisy image restoration problem, which is feasible for large images, is described. The approach is based on a vector space representation of images and on using the conjugate gradient algorithm to solve a least squares minimization problem. Computer simulations yield good results with relatively little computational cost.

Original language	English
Pages (from-to)	65-69
Number of pages	5
Journal	Pattern Recognition Letters
Volume	3
Issue number	1
DOIs	https://doi.org/10.1016/0167-8655(85)90044-3
State	Published - Jan 1985
Externally published	Yes

Keywords

Image restoration
nonlinear restoration
picture vector space

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10.1016/0167-8655(85)90044-3

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title = "Noisy image restoration by cost function minimization",

abstract = "Implementation of a new approach to the nonlinear noisy image restoration problem, which is feasible for large images, is described. The approach is based on a vector space representation of images and on using the conjugate gradient algorithm to solve a least squares minimization problem. Computer simulations yield good results with relatively little computational cost.",

keywords = "Image restoration, nonlinear restoration, picture vector space",

author = "Eli Harouche and Shmuel Peleg and Haim Shvaytser and Davis, \{Larry S.\}",

year = "1985",

month = jan,

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AU - Harouche, Eli

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AU - Shvaytser, Haim

AU - Davis, Larry S.

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N2 - Implementation of a new approach to the nonlinear noisy image restoration problem, which is feasible for large images, is described. The approach is based on a vector space representation of images and on using the conjugate gradient algorithm to solve a least squares minimization problem. Computer simulations yield good results with relatively little computational cost.

AB - Implementation of a new approach to the nonlinear noisy image restoration problem, which is feasible for large images, is described. The approach is based on a vector space representation of images and on using the conjugate gradient algorithm to solve a least squares minimization problem. Computer simulations yield good results with relatively little computational cost.

KW - Image restoration

KW - nonlinear restoration

KW - picture vector space

UR - https://www.scopus.com/pages/publications/0022205014

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JF - Pattern Recognition Letters

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Noisy image restoration by cost function minimization

Abstract

Keywords

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