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《Opto-Electronic Engineering》 2007-06
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Image fusion algorithm based on independent component analysis

CHEN Mi1, 2,XUAN Jian-hui3,LI De-ren2,QIN Qian-qing2,JIA Yong-hong4 ( 1. College of Education Technology, Capital Normal University, Beijing 100037, China; 2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China; 3. College of Computing Science, Wuhan University, Wuhan 430079, China; 4. College of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China )  
Independent Component Analysis (ICA) was a recently developed linear data analysis method, which could realize sparse coding of images and capture the essential edge structures of the image data. A multi-focus image fusion algorithm was proposed based on ICA and Support Vector Machines (SVMs). Using features extracted from the ICA domain coefficients, the SVMs were trained to classify the multi-focus images into clear regions and blur regions, and the images were segmented to extract the main edge information. Finally using the feature based fusion rules the corresponding clear regions of ICA domain coefficients and the edge information were fused into the composite representation. Experimental results show that the proposed algorithm is effective.
【Fund】: 国家自然科学基金资助项目(40204008);; 绘科技项目(1469990624201)
【CateGory Index】: TN911.73
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