DocumentCode :
3363090
Title :
Multi-focus Image Fusion Based on PCNN Model
Author :
Wang, Xiaorui ; Zhou, Dongming ; Nie, Rencan ; Zhao, Dongfeng
Author_Institution :
Inf. Coll., Yunnan Univ., Kunming, China
Volume :
1
fYear :
2012
fDate :
26-27 Aug. 2012
Firstpage :
289
Lastpage :
292
Abstract :
Based on the PCNN model and contrast modulation method, a new multi-focus image fusion method is proposed in this paper. Send source images into the PCNN and compute the contrast. The characteristic of image region clustering enhances the veracity of contrast. Then using the normalization contrast modulation gets two fusion images. Finally, use local variance to get the new fusion image. The experiment indicates that the fusion image contains more information about the edge, texture and detail, and it has a better contrast. Compared with the common methods, the innovative method embodies better fusion performance in information, standard and average grads.
Keywords :
image fusion; neural nets; pattern clustering; PCNN model; contrast modulation method; image region clustering characteristics; multifocus image fusion method; pulse coupled neural nets; source images; Clocks; Computational modeling; Image edge detection; Image fusion; Modulation; Neurons; Standards; PCNN; image fusion; local variance; modulate; multi-focus image fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on
Conference_Location :
Nanchang, Jiangxi
Print_ISBN :
978-1-4673-1902-7
Type :
conf
DOI :
10.1109/IHMSC.2012.79
Filename :
6305683
Link To Document :
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