Image Restoration of Depth of Field Extension Imaging System Based on Genetic Algorithm

Yun He; Yan Gang Wu; Jia Lin Tian; Wen Xu

doi:10.4028/www.scientific.net/AMM.539.131

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 539Image Restoration of Depth of Field Extension...

Image Restoration of Depth of Field Extension Imaging System Based on Genetic Algorithm

Abstract:

Genetic algorithm is a search algorithm based on genetic mechanism and natural selection. It has been widely applied to research fields including image processing field. The paper improves standard genetic algorithm and improves the arithmetic speed of the algorithm, which achieves better image restoration effect. And the paper compares the image restoration quality of traditional algorithm, standard genetic algorithm and improved genetic algorithm to prove the feasibility of applying genetic algorithm to image restoration.

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Periodical:

Applied Mechanics and Materials (Volume 539)

Pages:

131-135

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.539.131

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Online since:

July 2014

Authors:

Yun He*, Yan Gang Wu, Jia Lin Tian, Wen Xu

Keywords:

Genetic Algorithm (GA), Image Degradation, Image Processing, Image Restoration

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References

[1] Trent Bills, Ashok Sarnal, Two dimensional chromosomes and their application to computer vision, SPIE Neural and Stochastic Methods in Image and Signal Processing III, 2304: 65-75.

DOI: 10.1117/12.179241

Google Scholar

[2] Hunt, R Super-resolution of imagery: understanding the basis for recovery of spmial frequencies beyond the diffraction limit, Information, Decision and Control, 0De 99. Proceedings. )PP: 243-248, Feb. (1999).

DOI: 10.1109/idc.1999.754163

Google Scholar

[3] Yen-Wei Chen, Zensho Nakao, Xue Fang, Shinichi Tamura, A parallel genetic algofithm for image restoration. In: Proceedings of the 1 3th International Conference on Pattern Recognition, Vienna, Austmia, 1996, 3: 694·698.

DOI: 10.1109/icpr.1996.547654

Google Scholar

[4] Wu Y D, Zhang H Y。A Novel Image Restoration Algorithm Using Neural Network Based on Variational PDE Model f A 3. In: Proceedings of the Conference on Communications, Circuits and Systems[c]。San-Francisco, CA, USA, 2006: 433·436.

DOI: 10.1109/icccas.2006.284670

Google Scholar

[5] Charles K. Wang J z-Wavelet—based minimal-energy approach to image restoration[J]. Applied and Computational Harmonic Analysis. 2007, 23(1): 114—130.

DOI: 10.1016/j.acha.2007.01.006

Google Scholar