Estimation and optimization based ill-posed inverse restoration using fuzzy logic

Intelligent systems ranging from neural network, evolutionary computations and swarm intelligence to fuzzy systems are extensively exploited by researchers to solve variety of problems. In this paper focus is on deblurring that is considered as an inverse problem. It becomes ill-posed when noise con...

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Veröffentlicht in:	Multimedia tools and applications Jg. 69; H. 3; S. 1067 - 1087
Hauptverfasser:	Bilal, Mohsin, Hussain, Ayyaz, Jaffar, Muhammad Arfan, Choi, Tae-Sun, Mirza, Anwar M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Boston Springer US 01.04.2014 Springer Springer Nature B.V
Schlagworte:	Algebra Algorithms Analysis Applied sciences Artificial intelligence Computer Communication Networks Computer Science Computer science; control theory; systems Connectionism. Neural networks Data Structures and Information Theory Digitization Estimating techniques Exact sciences and technology Fuzzy logic Ill posed problems Inverse problems Methods Multimedia computer applications Multimedia Information Systems Neural networks Noise Optimization Parameter estimation Pattern recognition. Digital image processing. Computational geometry Regularization methods Remedies Smoothness Special Purpose and Application-Based Systems Studies Deblurring Constrained least square error Steepest descent Quadratic functional regularization Blur and noise Fuzzy regularization parameter Parameter estimation Image processing Noise reduction Evolutionary algorithm Steepest descent method Expert system Modeling Optimization Restoration Efficiency Least squares method Swarm intelligence Ill posed problem Robustness System identification Intelligent system Error function Neural network Blurred image Inverse problem Fuzzy logic Artificial intelligence Quadratic functional Signal to noise ratio
ISSN:	1380-7501, 1573-7721
Online-Zugang:	Volltext
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