Novel infrared and visible image fusion method based on independent component analysis  

作　　者：Yin LU Fuxiang WANG Xiaoyan LUO Feng LIU 

机构地区：[1]National Key Laboratory of CNS/ATM, School of Electronics and Information Engineering, Beihang University, Beijing 100191, China

出　　处：《Frontiers of Computer Science》2014年第2期243-254,共12页中国计算机科学前沿（英文版）

摘　　要：The goal of infrared （IR） and visible image fu- sion is for the fused image to contain IR object features from the IR image and retain the visual details provided by the visible image. The disadvantage of traditional fusion method based on independent component analysis （ICA） is that the primary feature information that describes the IR objects and the secondary feature information in the IR image are fused into the fused image. Secondary feature information can de- press the visual effect of the fused image. A novel ICA-based IR and visible image fusion scheme is proposed in this paper. ICA is employed to extract features from the infrared image, and then the primary and secondary features are distinguished by the kurtosis information of the ICA base coefficients. The secondary features of the IR image are discarded during fu- sion. The fused image is obtained by fusing primary features into the visible image. Experimental results show that the pro- posed method can provide better perception effect.The goal of infrared （IR） and visible image fu- sion is for the fused image to contain IR object features from the IR image and retain the visual details provided by the visible image. The disadvantage of traditional fusion method based on independent component analysis （ICA） is that the primary feature information that describes the IR objects and the secondary feature information in the IR image are fused into the fused image. Secondary feature information can de- press the visual effect of the fused image. A novel ICA-based IR and visible image fusion scheme is proposed in this paper. ICA is employed to extract features from the infrared image, and then the primary and secondary features are distinguished by the kurtosis information of the ICA base coefficients. The secondary features of the IR image are discarded during fu- sion. The fused image is obtained by fusing primary features into the visible image. Experimental results show that the pro- posed method can provide better perception effect.

关 键 词：image fusion independent component analysis（ICA） feature extraction KURTOSIS 

分 类 号：TN911.73[电子电信—通信与信息系统] TN215[电子电信—信息与通信工程]