Title :
3D MR image restoration by combining local genetic algorithm with adaptive pre-conditioning
Author :
Jiang, Tianzi ; Kruggel, Frithjof
Author_Institution :
Max-Planck Inst. of Cognitive Neurosci., Leipzig, Germany
Abstract :
In this paper, we propose a novel efficient method by incorporating a local genetic algorithm and a new pre-conditioning technique into Markov random field model for image restoration. The role of genetic algorithm is to improve the quality of restoration and the pre-conditioning technique aims at accelerating the convergence. The remarkable advantage of our approach is that restoring corrupted images and preserving the shape transitions in the restored results have been orchestrated very well. The experiments on 3D MR image show that our method work very well
Keywords :
Markov processes; adaptive signal processing; convergence; genetic algorithms; image restoration; magnetic resonance imaging; 3D MR image restoration; GA; MRI; Markov random field model; adaptive pre-conditioning; convergence; corrupted image restoration; image restoration; local genetic algorithm; shape transition preservation; Acceleration; Automation; Genetic algorithms; Image processing; Image restoration; Laboratories; Markov random fields; Neuroscience; Pattern recognition; Random variables;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.903544