25 October 1988 Regularization Theory In Discrete Image Restoration
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Proceedings Volume 1001, Visual Communications and Image Processing '88: Third in a Series; (1988) https://doi.org/10.1117/12.968935
Event: Visual Communications and Image Processing III, 1988, Cambridge, MA, United States
Abstract
This paper presents several aspects of the application of Regularization Theory in image restoration. This is accomplished by extending the applicability of the stabilizing functional approach to 2-D ill-posed inverse problems. Image restoration is formulated as the constrained minimization of a stabilizing functional. The analytical study of this optimization problem results in a variety of regularized solutions. A relationship between these regularized solutions and optimal Wiener estimation is identified. The resulting algorithms are evaluated through experimental results.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nicolaos B. Karayiannis, Nicolaos B. Karayiannis, Anastasios N. Venetsanopoulos, Anastasios N. Venetsanopoulos, } "Regularization Theory In Discrete Image Restoration", Proc. SPIE 1001, Visual Communications and Image Processing '88: Third in a Series, (25 October 1988); doi: 10.1117/12.968935; https://doi.org/10.1117/12.968935
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