Iterative blind image restoration using local constraints

Kaaren May; Tania Stathaki; Aggelos K Katsaggelos

Iterative blind image restoration using local constraints

Kaaren May, Tania Stathaki, Aggelos K Katsaggelos

Electrical and Computer Engineering

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

1 Scopus citations

Abstract

A new method of incorporating local image constraints into blind image restoration is proposed. The local mean and variance of the degraded image are used to obtain .in initial estimate of the pixel intensity bounds. As the restoration proceeds, the bounds are updated from the current image estimate. I lie iterative-bound algorithm shows an improvement over the use of fixed bounds taken from the blurred image, in which case underestimation of the variance occurs at edges and textures. Simulations are presented for both the fixed-And iterative-bound implementations.

Original language	English (US)
Journal	European Signal Processing Conference
Volume	1998-January
State	Published - Jan 1 1998
Event	9th European Signal Processing Conference, EUSIPCO 1998 - Island of Rhodes, Greece Duration: Sep 8 1998 → Sep 11 1998

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering

Cite this

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title = "Iterative blind image restoration using local constraints",

abstract = "A new method of incorporating local image constraints into blind image restoration is proposed. The local mean and variance of the degraded image are used to obtain .in initial estimate of the pixel intensity bounds. As the restoration proceeds, the bounds are updated from the current image estimate. I lie iterative-bound algorithm shows an improvement over the use of fixed bounds taken from the blurred image, in which case underestimation of the variance occurs at edges and textures. Simulations are presented for both the fixed-And iterative-bound implementations.",

author = "Kaaren May and Tania Stathaki and Katsaggelos, {Aggelos K}",

year = "1998",

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language = "English (US)",

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AU - Katsaggelos, Aggelos K

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N2 - A new method of incorporating local image constraints into blind image restoration is proposed. The local mean and variance of the degraded image are used to obtain .in initial estimate of the pixel intensity bounds. As the restoration proceeds, the bounds are updated from the current image estimate. I lie iterative-bound algorithm shows an improvement over the use of fixed bounds taken from the blurred image, in which case underestimation of the variance occurs at edges and textures. Simulations are presented for both the fixed-And iterative-bound implementations.

AB - A new method of incorporating local image constraints into blind image restoration is proposed. The local mean and variance of the degraded image are used to obtain .in initial estimate of the pixel intensity bounds. As the restoration proceeds, the bounds are updated from the current image estimate. I lie iterative-bound algorithm shows an improvement over the use of fixed bounds taken from the blurred image, in which case underestimation of the variance occurs at edges and textures. Simulations are presented for both the fixed-And iterative-bound implementations.

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M3 - Conference article

AN - SCOPUS:0346869384

SN - 2219-5491

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JF - European Signal Processing Conference

T2 - 9th European Signal Processing Conference, EUSIPCO 1998

Y2 - 8 September 1998 through 11 September 1998

ER -

Iterative blind image restoration using local constraints

Abstract

ASJC Scopus subject areas

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