Iterative determination of local bound constraints in iterative image restoration

Kaaren May; Tania Stathaki; Anthony G. Constantinides; Aggelos K. Katsaggelos

Iterative determination of local bound constraints in iterative image restoration

Kaaren May^*, Tania Stathaki, Anthony G. Constantinides, Aggelos K. Katsaggelos

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

Abstract

In this paper, the problem of how to better estimate spatially adaptive intensity bounds for image restoration is addressed. When the intensity bounds are estimated from a degraded image, blurring leads to underestimation of the bounds in the edge and texture regions. Therefore, an iterative implementation of the restoration algorithm has been proposed in which the intensity bounds are re-estimated from the current image estimate. However, direct update of the bounds leads to over-smoothing in regions where the bounds are active. Furthermore, the resulting algorithm exhibits slow convergence. In this paper, alternative methods of initially estimating and updating the bounds are proposed, and the results for the fixed- and updated-bound implementations are compared. A method for estimation of the bound tightness parameter is also proposed.

Original language	English (US)
Title of host publication	IEEE International Conference on Image Processing
Publisher	IEEE Comp Soc
Pages	833-837
Number of pages	5
Volume	2
State	Published - Dec 1 1998
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

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

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Cite this

May, K., Stathaki, T., Constantinides, A. G., & Katsaggelos, A. K. (1998). Iterative determination of local bound constraints in iterative image restoration. In IEEE International Conference on Image Processing (Vol. 2, pp. 833-837). IEEE Comp Soc.

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title = "Iterative determination of local bound constraints in iterative image restoration",

abstract = "In this paper, the problem of how to better estimate spatially adaptive intensity bounds for image restoration is addressed. When the intensity bounds are estimated from a degraded image, blurring leads to underestimation of the bounds in the edge and texture regions. Therefore, an iterative implementation of the restoration algorithm has been proposed in which the intensity bounds are re-estimated from the current image estimate. However, direct update of the bounds leads to over-smoothing in regions where the bounds are active. Furthermore, the resulting algorithm exhibits slow convergence. In this paper, alternative methods of initially estimating and updating the bounds are proposed, and the results for the fixed- and updated-bound implementations are compared. A method for estimation of the bound tightness parameter is also proposed.",

author = "Kaaren May and Tania Stathaki and Constantinides, {Anthony G.} and Katsaggelos, {Aggelos K.}",

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AU - May, Kaaren

AU - Stathaki, Tania

AU - Constantinides, Anthony G.

AU - Katsaggelos, Aggelos K.

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N2 - In this paper, the problem of how to better estimate spatially adaptive intensity bounds for image restoration is addressed. When the intensity bounds are estimated from a degraded image, blurring leads to underestimation of the bounds in the edge and texture regions. Therefore, an iterative implementation of the restoration algorithm has been proposed in which the intensity bounds are re-estimated from the current image estimate. However, direct update of the bounds leads to over-smoothing in regions where the bounds are active. Furthermore, the resulting algorithm exhibits slow convergence. In this paper, alternative methods of initially estimating and updating the bounds are proposed, and the results for the fixed- and updated-bound implementations are compared. A method for estimation of the bound tightness parameter is also proposed.

AB - In this paper, the problem of how to better estimate spatially adaptive intensity bounds for image restoration is addressed. When the intensity bounds are estimated from a degraded image, blurring leads to underestimation of the bounds in the edge and texture regions. Therefore, an iterative implementation of the restoration algorithm has been proposed in which the intensity bounds are re-estimated from the current image estimate. However, direct update of the bounds leads to over-smoothing in regions where the bounds are active. Furthermore, the resulting algorithm exhibits slow convergence. In this paper, alternative methods of initially estimating and updating the bounds are proposed, and the results for the fixed- and updated-bound implementations are compared. A method for estimation of the bound tightness parameter is also proposed.

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