DocumentCode :
2854451
Title :
Extending depth-of-field by image fusion using multi-objective genetic algorithm
Author :
Aslantas, Veysel ; Kurban, Rifat
Author_Institution :
Dept. of Comput. Eng., Erciyes Univ., Kayseri, Turkey
fYear :
2009
fDate :
23-26 June 2009
Firstpage :
331
Lastpage :
336
Abstract :
Optical imaging systems used in industrial vision applications suffer from the limited depth of field problem. Image fusion is a practical way to obtain an everywhere-in-focus image of a scene. In this paper, a spatial domain image fusion method using multi-objective genetic algorithm is proposed to obtain an optimal fused image. Experimental results conducted with industrial images show that the proposed method outperforms Laplacian Pyramid and DWT methods.
Keywords :
discrete wavelet transforms; genetic algorithms; image fusion; optical images; Laplacian Pyramid; depth of field problem; discrete wavelet transform methods; industrial vision applications; multiobjective genetic algorithm; optical imaging systems; spatial domain image fusion method; Discrete wavelet transforms; Focusing; Genetic algorithms; Genetic engineering; Image fusion; Inspection; Laplace equations; Layout; Lenses; Optical imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Informatics, 2009. INDIN 2009. 7th IEEE International Conference on
Conference_Location :
Cardiff, Wales
ISSN :
1935-4576
Print_ISBN :
978-1-4244-3759-7
Electronic_ISBN :
1935-4576
Type :
conf
DOI :
10.1109/INDIN.2009.5195826
Filename :
5195826
Link To Document :
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