Effective Infrared Small Target Detection Utilizing a Novel Local Contrast Method

Effective detection of small targets plays a pivotal role in infrared (IR) search and track applications for modern military defense or attack. Consequently, an effective small IR target detection algorithm based on a novel local contrast measure (NLCM) is proposed in this letter. Initially, difference of Gaussian band-pass filter is employed to enhance target and suppress background clutter. Then, a segmentation operation is implemented to obtain IR local regions of fixed size larger than general IR small target size. Finally, the salient map is obtained using the NLCM, and an adaptive threshold is applied to extract the target region. Experimental results on two real sequences show that the proposed method has better detection performance compared with conventional baseline methods.