N. Joudar
ABSTRACT
In this paper, we propose a novel vision of image restoration problem. Based on the classical image restoration model, we introduce a modified optimization model with a new decision vector that indicates the pixels categories. Depending on the degraded image and its median corrected version, the technique allows via the optimization criterion to choose on which one of the both generates the best solution of the model, which in turn is solved by the genetic algorithm. Once noisy pixels are detected, a median based filter is performed only for these pixels. Experiments shows that the results are satisfactory in term of both visual quality and quantitative measurement.
- Nodes, T. A., & Gallagher Jr, N. C, The output distribution of median type filters, IEEE Transactions on Communications (1984), 32(5), 532--541. Google Scholar
Cross Ref
- Hwang, H., & Haddad, R. A, Adaptive median filters: new algorithms and results, IEEE Transactions on image processing (1995), 4(4), 499--502. Google ScholarDigital Library
- G.Aubert P.Kornprobst "Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations", Springer, 2002, Vol.147.Google Scholar
- J Hadamard, "Sur les problèmes aux dérivées partielles et leur signification physique.", Princeton Univ.Bull, Vol.13,1902, pp.49--52.Google Scholar
- R. Lagendijk, J. Biemond and D. E. Boekee, "Regularized iterative image restoration with ringing reduction". IEEE Transactions on Acoustics, Speech and Signal Processing, Vol36, No.12, 1988, pp. 1874--1888. Google ScholarCross Ref
- P.Hansen, "analysis of discrete ill-posed problems by means of the L-curve". SIAM, Review.43, 1992, pp.561--580. Google ScholarDigital Library
- Tikhonov and Arsenine, "Méthodes de résolution de problèmes mal posés". Editions MIR, Moscou, Russie, 1976.Google Scholar
- Michalewicz. Z, Genetic algorithms, numerical optimization, and constraints. In Proceedings of the sixth international conference on genetic algorithms, 1995, Morgan Kaufmann, San Mateo, CA, 151--158Google Scholar
- J.H. Holland, Adaptation in Nature and Artificial Systems, University of Michigan Press, 1975.Google Scholar
- Kumar, A. Encoding schemes in genetic algorithm. International Journal of Advanced Research in IT and Engineering, (2013), 2(3), 1--7.Google Scholar
- N.Joudar, K. El Moutouakil, M. Ettaouil, An original Continuous Hopfield Network for optimal images restoration, WSEAS, transaction on computer, 2015, Vol.14 pp.668--678.Google Scholar
- Wu, Y. D., Zhu, Q. X., Sun, S. X., & Zhang, H. Y. (2006). Image restoration using variational PDE-based neural network. Neurocomputing, 69(16), 2364--2368. Google ScholarCross Ref
Recommendations
Noise free image restoration using hybrid filter with adaptive genetic algorithm
We modelled a Hybrid filter with AGA to remove the noise from the images.The noisy free images are restored by shining the pixel values using AGA.The performance is analysed by taking number of images and comparing the result with existing technique. ...
Adaptive Four-dot Median Filter for Removing 1-99% Densities of Salt-and-Pepper Noise in Images
In order to accelerate denoising and improve the denoising performance of the current median filters, an Adaptive Four-dot Median Filter (AFMF) for image restoration is proposed in this article. AFMF is not only very efficient and fast in logic ...
Restoration of embedded image from corrupted stego image
Digital images are easily corrupted by noise during transmission. This paper presents a robust method for restoring embedded image from corrupted stego image. We firstly identify unreliable bits of each pixel in the embedded image by detecting noise in ...
Comments