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《Applied Laser》 2016-01
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Study on Infrared Light with Grayscale Optical Images Fusion based on SGCT

Guo Hongyan;Wang Shumin;Zhengzhou Vocational University of Information and Technology;Xuchang Vocational Technical College;  
In this paper,based on the second generation based on the Curvelet transform theory,combined with infrared and visible light imaging and physical characteristics,in order to more effectively measure information quality in the pixels of the image,a second-generation Curvelet algorithm is proposed for IR fused with grayscale optical images.In the algorithm introduced the second generation Curvelet transform domain activity weighted to the pixels in the image information to assess their quality and directional contrast and weighted to measure the significant level,presents significant measurement coefficient with the method of selection and extraction of infrared image of the target characteristics,and gray-scale characteristics of visible in the image a lot of background information..Simulation results show that the algorithm can retain important information in the source image at the same time,edge details of the image much clearer and edge smoother after fusion.
【Fund】: 2015年度河南省软科学研究计划资助项目(项目编号:152400410185 152400410597)
【CateGory Index】: TP391.41
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