Infrared Dim Target Detection Using Shearlet’s Kurtosis Maximization under Non-Uniform Background

Symmetry

Yuhan Liu¹  Meihui Li¹  Lingbing Peng¹  Zhenming Peng¹  Tianfang Zhang² 

[1] School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;

关键词: infrared target detection;    maximum kurtosis;    multiscale feature fusion;    shearlet transform;    non-uniform background;   

DOI  :  10.3390/sym11050723

来源: DOAJ

【 摘 要 】

A novel method based on multiscale and multidirectional feature fusion in the shearlet transform domain and kurtosis maximization for detecting the dim target in infrared images with a low signal-to-noise ratio (SNR) and serious interference caused by a cluttered and non-uniform background is presented in this paper. First, an original image is decomposed using the shearlet transform with translation invariance. Second, various directions of high-frequency subbands are fused and the corresponding kurtosis of fused image is computed. The targets can be enhanced by strengthening the column with maximum kurtosis. Then, processed high-frequency subbands on different scales of images are merged. Finally, the dim targets are detected by an adaptive threshold with a maximum contrast criterion (MCC). The experimental results show that the proposed method has good performance for infrared target detection in comparison with the nonsubsampled contourlet transform (NSCT) method.

【 授权许可】

Unknown