Multi-level image fusion and enhancement for target detection

He Weiji; Feng Weiyi; Peng Yiyue; Chen Qian; Gu Guohua; Miao Zhuang

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Multi-level image fusion and enhancement for target detection

He Weiji 1 * #,Feng Weiyi 1,Peng Yiyue 2,Chen Qian 1,Gu Guohua 1,Miao Zhuang 2

1.Jiangsu Key Lab of Spectral Imaging & Intelligence Sense (SIIS), Nanjing University of Science and Technology, Nanjing 210094

2.Science and Technology on Low Light Level (LLL) Night Vision Lab, Xi’an 710065

*Correspondence author

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Funding: the specialized research fund of Ministry of Education of China for the doctoral program of colleges and universities （No.Grant 20103219120016）, the National Natural Science Foundation of China （No.NSFC)）, the Seventh Six-talent Peak project of Jiangsu Province of China （No.Grant DZXX-104）

Opened online:24 February 2014

Accepted by: none

Citation: He Weiji,Feng Weiyi,Peng Yiyue.Multi-level image fusion and enhancement for target detection[OL]. [24 February 2014] http://en.paper.edu.cn/en_releasepaper/content/4585933

In this paper, a novel infrared-to-visible image fusion algorithm for enhancing contrast and visibility is proposed. A multi-level method based on the characteristics of images and the properties of the targets is designed to complete the image fusion process, where a contrast enhancement method is added in the low-frequency information of the layered images and the edge information is enhanced in the high-frequency information using the correlation between the low- and high-frequency components. In the experiments, three groups of infrared-to-visible images were used to demonstrate the effectiveness of the multi-level fusion method. All the evaluation indexes, such as standard deviation and information entropy, were significantly higher than other existing methods. Thus, the experiental results verified the effectiveness of the proposed image fusion methods. The quality of the fusion images was improved for better differentiability in terms of contrast and features of the targets

Keywords:Multi-level image fusion; Infrared and visible images; Contrast enhancement; Wavelet decomposition

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