Infrared small target detection algorithm based on potential regions proposal

Shuaihao Wang; Jiangpeng Du; Juanfang Chai; Yiji Liu; Chengshi Tang

doi:10.1117/12.2516772

12 March 2019 Infrared small target detection algorithm based on potential regions proposal

Shuaihao Wang, Jiangpeng Du, Juanfang Chai, Yiji Liu, Chengshi Tang

Proceedings Volume 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application; 110234R (2019) https://doi.org/10.1117/12.2516772
Event: Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 2018, Xi'an, China

Abstract

A novel infrared small target detection algorithm based on potential regions proposal is proposed in this paper. Potential regions mean subsets (size are 16 by 16 in this paper) with small targets of an infrared image. A convolution neural network (CNN) classifier has been trained by using constructed datasets to discriminate potential regions of an input image. Traditional methods such as tophat transform, max-mean and max-median filter are used to suppress the background and noise of potential regions. Some experiments are carried out to verify the algorithm performance, and the results show that the gains of signal noise ratio and contrast ratio have better performance than traditional methods.

Citation Download Citation

Shuaihao Wang, Jiangpeng Du, Juanfang Chai, Yiji Liu, and Chengshi Tang "Infrared small target detection algorithm based on potential regions proposal", Proc. SPIE 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 110234R (12 March 2019); https://doi.org/10.1117/12.2516772

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