Infrared dim target detection algorithm based on improved LCM

Zhang Xiangyue; Ding Qinghai; Luo Haibo; Hui Bin; Chang Zheng; Zhang Junchao

doi:10.3788/IRLA201746.0726002

How to detect infrared dim targets accurately under complex background and low SCR condition is of great significance for the development of precision guided weapons and infrared warning. In order to improve the SCR and detect the dim targets effectively, a new method for infrared dim target detection based on the gray contrast between the central region and its neighborhood was proposed. The contrast of the target was improved by calculating the contrast map and saliency map of the input image while suppressing the background clutter. The adaptive threshold was set on this basis to separate the dim targets. Experimental results show that the proposed method can achieve higher detection rate and lower false alarm rate compared with conventional LCM(Local Contrast Measure) method. The proposed method has an outperformance compared with other algorithms, especially in the case of complex background.

Infrared dim target detection algorithm based on improved LCM

1. Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China;

2. Key Laboratory of Opt-Electronic Information Processing,Chinese Academy of Sciences,Shenyang 110016,China;

3. University of Chinese Academy of Sciences,Beijing 100049,China;

4. Space Star Technology Co,LTD,Beijing 100086,China

Received Date: 2016-11-10

Rev Recd Date: 2016-12-20

Publish Date: 2017-07-25

Key words:

Abstract: How to detect infrared dim targets accurately under complex background and low SCR condition is of great significance for the development of precision guided weapons and infrared warning. In order to improve the SCR and detect the dim targets effectively, a new method for infrared dim target detection based on the gray contrast between the central region and its neighborhood was proposed. The contrast of the target was improved by calculating the contrast map and saliency map of the input image while suppressing the background clutter. The adaptive threshold was set on this basis to separate the dim targets. Experimental results show that the proposed method can achieve higher detection rate and lower false alarm rate compared with conventional LCM(Local Contrast Measure) method. The proposed method has an outperformance compared with other algorithms, especially in the case of complex background.

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Reference (11)

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Infrared dim target detection algorithm based on improved LCM

doi: 10.3788/IRLA201746.0726002

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