Spatially-variant roughness penalty design for uniform resolution in penalized-likelihood image reconstruction

J. Webster Stayman; Jeffrey A. Fessler

Spatially-variant roughness penalty design for uniform resolution in penalized-likelihood image reconstruction

Research output: Contribution to conference › Paper › peer-review

Abstract

Traditional space-invariant regularization schemes in tomographic image reconstruction using penalized-likelihood estimators produce images with nonuniform resolution properties. The local point spread functions that quantify the local smoothing properties of such estimators are not only space-variant and asymmetric, but are also object-dependent even for space-invariant systems. We propose a new regularization scheme for increased spatial uniformity and demonstrate the resolution properties of this new method versus conventional regularization schemes through an investigation of local point spread functions.

Original language	English (US)
Pages	685-689
Number of pages	5
State	Published - Dec 1 1998
Externally published	Yes
Event	Proceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA Duration: Oct 4 1998 → Oct 7 1998

Other

Other	Proceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3)
City	Chicago, IL, USA
Period	10/4/98 → 10/7/98

ASJC Scopus subject areas

Hardware and Architecture
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

Cite this

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title = "Spatially-variant roughness penalty design for uniform resolution in penalized-likelihood image reconstruction",

abstract = "Traditional space-invariant regularization schemes in tomographic image reconstruction using penalized-likelihood estimators produce images with nonuniform resolution properties. The local point spread functions that quantify the local smoothing properties of such estimators are not only space-variant and asymmetric, but are also object-dependent even for space-invariant systems. We propose a new regularization scheme for increased spatial uniformity and demonstrate the resolution properties of this new method versus conventional regularization schemes through an investigation of local point spread functions.",

author = "Stayman, {J. Webster} and Fessler, {Jeffrey A.}",

year = "1998",

month = dec,

day = "1",

language = "English (US)",

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note = "Proceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) ; Conference date: 04-10-1998 Through 07-10-1998",

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AU - Fessler, Jeffrey A.

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N2 - Traditional space-invariant regularization schemes in tomographic image reconstruction using penalized-likelihood estimators produce images with nonuniform resolution properties. The local point spread functions that quantify the local smoothing properties of such estimators are not only space-variant and asymmetric, but are also object-dependent even for space-invariant systems. We propose a new regularization scheme for increased spatial uniformity and demonstrate the resolution properties of this new method versus conventional regularization schemes through an investigation of local point spread functions.

AB - Traditional space-invariant regularization schemes in tomographic image reconstruction using penalized-likelihood estimators produce images with nonuniform resolution properties. The local point spread functions that quantify the local smoothing properties of such estimators are not only space-variant and asymmetric, but are also object-dependent even for space-invariant systems. We propose a new regularization scheme for increased spatial uniformity and demonstrate the resolution properties of this new method versus conventional regularization schemes through an investigation of local point spread functions.

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M3 - Paper

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T2 - Proceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3)

Y2 - 4 October 1998 through 7 October 1998

ER -

Spatially-variant roughness penalty design for uniform resolution in penalized-likelihood image reconstruction

Abstract

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ASJC Scopus subject areas

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