A general formulation of the weighted smoothing functional for regularized image restoration

Moon Gi Kang; A. K. Katsaggelos

doi:10.1109/ICIP.1994.413660

A general formulation of the weighted smoothing functional for regularized image restoration

Moon Gi Kang, A. K. Katsaggelos

Department of Electrical and Electronic Engineering

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

3 Citations (Scopus)

Abstract

Proposes a general form of the weighted smoothing functional for regularized image restoration. The weighting matrices which introduce the spatial adaptivity are defined as a function of the (partially) restored image. As a result no prior knowledge about the image is required but the smoothing functional to be minimized is nonlinear with respect to the unknown image. Conditions for the convexity of the functional are established. An iterative algorithm is proposed for obtaining its minimum. Sufficient conditions for the convergence of the algorithm are established. Various forms of the weighting matrices are proposed. Experimental results demonstrate the effectiveness of the approach.

Original language	English
Article number	413660
Pages (from-to)	695-699
Number of pages	5
Journal	Proceedings - International Conference on Image Processing, ICIP
Volume	2
DOIs	https://doi.org/10.1109/ICIP.1994.413660
Publication status	Published - 1994
Event	Proceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA Duration: 1994 Nov 13 → 1994 Nov 16

Bibliographical note

Publisher Copyright:
© 1994 IEEE.

All Science Journal Classification (ASJC) codes

Software
Computer Vision and Pattern Recognition
Signal Processing

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10.1109/ICIP.1994.413660

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abstract = "Proposes a general form of the weighted smoothing functional for regularized image restoration. The weighting matrices which introduce the spatial adaptivity are defined as a function of the (partially) restored image. As a result no prior knowledge about the image is required but the smoothing functional to be minimized is nonlinear with respect to the unknown image. Conditions for the convexity of the functional are established. An iterative algorithm is proposed for obtaining its minimum. Sufficient conditions for the convergence of the algorithm are established. Various forms of the weighting matrices are proposed. Experimental results demonstrate the effectiveness of the approach.",

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AU - Kang, Moon Gi

AU - Katsaggelos, A. K.

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N2 - Proposes a general form of the weighted smoothing functional for regularized image restoration. The weighting matrices which introduce the spatial adaptivity are defined as a function of the (partially) restored image. As a result no prior knowledge about the image is required but the smoothing functional to be minimized is nonlinear with respect to the unknown image. Conditions for the convexity of the functional are established. An iterative algorithm is proposed for obtaining its minimum. Sufficient conditions for the convergence of the algorithm are established. Various forms of the weighting matrices are proposed. Experimental results demonstrate the effectiveness of the approach.

AB - Proposes a general form of the weighted smoothing functional for regularized image restoration. The weighting matrices which introduce the spatial adaptivity are defined as a function of the (partially) restored image. As a result no prior knowledge about the image is required but the smoothing functional to be minimized is nonlinear with respect to the unknown image. Conditions for the convexity of the functional are established. An iterative algorithm is proposed for obtaining its minimum. Sufficient conditions for the convergence of the algorithm are established. Various forms of the weighting matrices are proposed. Experimental results demonstrate the effectiveness of the approach.

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JO - Proceedings - International Conference on Image Processing, ICIP

JF - Proceedings - International Conference on Image Processing, ICIP

M1 - 413660

T2 - Proceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3)

Y2 - 13 November 1994 through 16 November 1994

ER -

A general formulation of the weighted smoothing functional for regularized image restoration

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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