A NEW BI-PHASED IMAGE RESTORATION
Résumé
In This work a new method for image restoration is proposed. This new method is constituted of two phases. The first phase
which is initialization phase, from a blurred image we get a new one by the use of the search efficiency function based on Levy
distribution as first cost function. In The second phase, the obtained image is introduced to PSO for local restoration where a
restoration cost function is used. The results obtained were excellent.
Références
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March 2008.
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Computational Intelligence and Design, 2008.
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Second Edition, Prentice Hall, 2002.
[2] Mallat S., A Wavelet Tour Of Signal Processing, Second
Edition, Academic Press, Elsevier (USA), 1999.
[3] Pratt W. K., Digital Image Processing: PIKS Inside, Third
Edition, John Wiley & Sons, Inc., 2001.
[4] Perry S. W., Adaptive Image Restoration: Perceptron Based
Neural Network Model and Algorithms, Ph.D. Theses,
School of Electrical and Information Engineering University
of Sidney, Australia, 1999.
[5] Smith S. K., Digital Signal Processing, A Practical Guide
for Engineers and Scientists, Newnes, 2003.
[6] BI Xiao-jun, WANG Ting, “Adaptive Blind Image
Restoration Algorithm of Degraded Image”, Congress on
Image and Signal Processing, 2008 IEEE
[7] Feng-qing Qin, Jun Min, Hong-rong Guo, “A Blind Image
Restoration Method Based on PSF Estimation”, World
Congress on Software Engineering, 2009 IEEE
[8] Jianjun Zhang, Qin Wang, “A New Regularization Method
for Bi-Level Image Restoration”, ICALIP2008, 2008 IEEE.
[9] Jinyoung Youn, Younguk Park, Jeongho Shin, and Joonki
Paik, “Spatially Adaptive Image Restoration and Its FIR
Implementation”, Second International Conference on Future
Generation Communication and Networking Symposia, 2008
IEEE.
[10] Rajeev Srivastava, Harish Parthasarthyt, JRP Guptat and D.
Roy Choudharyl, “Image Restoration from Motion Blurred
Image using PDEs formalism”, IEEE International Advance
Computing Conference (IACC 2009) Patiala, India, 6-7
March 2009.
[11] Satyadhyan Chickerur, Aswatha Kumar M , “A Robust
Cluster Based Approach for Image Restoration”, IEEE
Congress on Image and Signal Processing, 2008.
[12] Sun Jing, Wu Lehua, Gui Qi, “An Improved Multiscale
Maximum Entropy Image Restoration Algorithm”,
Proceedings of the First International Conference on
Innovative Computing, Information and Control
(ICICIC'06), IEEE, 2006.
[13] Sungjun Yim, Jeongho Shin, Joonki Paik, “Block-Based Fast
Image Restoration”, Proceedings of the International
Conference on Wavelet Analysis and Pattern Recognition,
Beijing, China, 2007.
[14] Varlen Grabski, “Digital Image Restoration Based on Pixel
Simultaneous Detection Probabilities”, IEEE Transactions
On Nuclear Science, Vol. 56, No. 3, June 2009.
[15] Yoshinori Abe and Youji Iiguni, “Fast Computation Of The
High Resolution Image Restoration By Using The Discrete
Cosine Transform”, ICASSP, IEEE, 2007.
[16] Abd-Krim Seghouane, “Model Selection Criteria for Image
Restoration”, IEEE Transactions On Neural Networks, Vol.
20, NO. 8, August 2009.
[17] J.K. Prasanna and A.N. Rajagopalan, “Image restoration
using the particle filter: handling non-causality”, IEE Proc.-
Vis. Image Signal Process., Vol. 153, No. 5, October, IEEE,
2006.
[18] Pradeepa D. Samarasinghe, Rodney A. Kennedy, Hongdong
Li, “On Non-blind Image Restoration”, IEEE, 2009.
[19] S. Derin Babacan, Rafael Molina, and Aggelos K.
Katsaggelos, “Parameter Estimation in TV Image
Restoration Using Variational Distribution Approximation”,
IEEE Transactions On Image Processing, Vol. 17, NO. 3,
March 2008.
[20] Shuai Lou, Zhenliang Ding, Feng Yuan, Jing Li, “Image
Restoration Based on Wavelet-Domain Contextual Hidden
Markov Tree Model”, International Conference on Computer
Science and Software Engineering, IEEE, 2008.
[21] Wang Hong-Zhi Zhao Shuang Lv Hong-Wu, “Super-
Resolution Image Restoration with L-Curve”, IEEE
Congress on Image and Signal Processing, 2008.
[22] Wen-Hao Lee, Shang-Hong Lai, and Chia-Lun Chen,
“Iterative Blind Image Motion Deblurring Via Learning A
No-Reference Image Quality Measure”, ICIP 2007.
[23] Xiaolei LU, Furong WANG, Hai HU, Benxiong HUANG,
“Wavelet domain image restoration and parameters
estimation based on variational Bayesian method and
Student-t priors”, IEEE International Symposium on
Computational Intelligence and Design, 2008.
[24] Youshen Xia, and Mohamed S. Kamel, “Novel Cooperative
Neural Fusion Algorithms for Image Restoration and Image
Fusion”, IEEE Transactions On Image Processing, Vol. 16,
NO. 2, February 2007.
[25] Clerc M. and Kennedy J., “The Particle Swarm: Explosion,
Stability and Convergence in a Multi- Dimensional complex
Space”, IEEE Transactions on Evolutionary Computation,
vol. 6, 2001.
[26] Dréo J. & Siarry P., Métaheuristiques pour l’optimisation
difficile, Edition Eyrolles, 2003.
[27] Kennedy J. and Eberhart R. “Particle Swarm Optimization”,
In Proceedings of IEEE International Conference on Neural
Networks, Perth, Australia, vol. 4, 1995.
[28] Kennedy J. & Eberhart R.C., Swarm Intelligence, Morgan
Kaufman Publishers, Academic Press, 2001.
[29] Omran M.G.H., Particle Swarm Optimization Methods for
Pattern Recognition and Image Processing, PhD Thesis,
University of Pretoria, November 2004.
[30] Van den Bergh F., An Analysis of Particle Swarm
Optimizers, PhD Thesis, Department of Computer Science,
University of Pretoria, South Africa, 2002.
[31] Vrahatis M.N., Parsopoulos K.E., “Parameter selection and
adaptation in Unified Particle Swarm Optimization”,
Mathematical and Computer Modelling, vol. 46, 2007.
[32] Wu, Q.H., Ji, T.Y. and Lu, Z., “A Particle Swarm Optimizer
Applied to Soft Morphological Filters for Periodic Noise
Reduction”, Evo Workshops, LNCS4448, 2007.
[33] A. Toumi, N. Rechid, A. Taleb-Ahmed, K. Benmahammed,
“Particle Swarm Optimization forImage Deblurring”, 1st
Mediterraniean Conference on Intelligent Systems and
Automation, Annaba, Algeria, 2008.
[34] A.M. Reynolds,” Cooperative random Lévy flight searches
and the flight patterns of honeybees", Physics Letters A 354,
2006.
Comment citer
TOUMI, A. et al.
A NEW BI-PHASED IMAGE RESTORATION.
Courrier du Savoir, [S.l.], v. 12, mai 2014.
ISSN 1112-3338.
Disponible à l'adresse : >https://revues.univ-biskra.dz./index.php/cds/article/view/448>. Date de consultation : 14 nov. 2024
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