Two-dimensional signal and image processing
Two-dimensional signal and image processing
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Digital image processing
Digital Image Processing
Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Fundamentals of Algorithms)
Two image restoration algorithms using variational PDE based neural network
IWCMC '07 Proceedings of the 2007 international conference on Wireless communications and mobile computing
Spatially Adaptive Regularization Image Restoration Using a Modified Hopfield Network
CERMA '07 Proceedings of the Electronics, Robotics and Automotive Mechanics Conference
Genetic fingerprinting for copyright protection of multicast media
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Bio-Inspired Information Hiding; Guest editors: Jeng-Shyang Pan, Ajith Abraham
A new method for parameter estimation of edge-preserving regularization in image restoration
Journal of Computational and Applied Mathematics
A refactoring method for cache-efficient swarm intelligence algorithms
Information Sciences: an International Journal
A segmentation-based regularization term for image deconvolution
IEEE Transactions on Image Processing
Image restoration using a modified Hopfield network
IEEE Transactions on Image Processing
Weight assignment for adaptive image restoration by neural networks
IEEE Transactions on Neural Networks
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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 contaminates the blurry image. Hence the problem is very sensitive to small perturbation in data. Conventionally, smoothness constraints are considered as a remedy to cater the sensitivity of the problem. In this paper, fuzzy rule based regularization parameter estimation is proposed with quadratic functional smoothness constraint. For deblurring image in the presence of noise, a constrained least square error function is minimized by the steepest descent algorithm. Visual results and quantitative measurements show the efficiency and robustness of the proposed technique compared to the state of the art and recently proposed methods.