A small target detection algorithm in infrared image by combining multi-response fusion and local contrast enhancement

The detection of small target in infrared (IR) images is the key technology for IR search, tracking and early warning. When the target locates at distance, the target occupies tiny area, shows low signal-to-noise ratio, which is hard to be detected. An infrared small target detection algorithm by combining multi-response fusion and local contrast enhancement (MRF-LCE) is introduced in this paper. First, Laplacian of Gaussian (LoG) filter and negative LoG filter are utilized to obtain the response map of bright and dark targets, respectively. Second, a multi-response fusion method is designed to respond to the bright and dark targets, simultaneously. Finally, a local contrast method is implemented to further enhance the targets and suppress the background, and these small targets are segmented by an adaptive threshold method. Experiments on three different real sequences show that the proposed algorithm can effectively detect targets in different scenarios.

Automated summary

A infrared small target detection algorithm combining multi-response fusion and local contrast enhancement is introduced in this paper, which can effectively detect targets in different scenarios.