The robust detection of small targets is one of the crucial techniques in an infrared system. It is still a challenge to detect small targets under complex backgrounds. Aiming at the problem where infrared small target detection is easily disturbed by complex backgrounds, an infrared single frame detection method based on a block-matching approach is proposed in this paper. Firstly, the input infrared image is processed by extracting blocks from it. A new infrared model is constructed by finding blocks that are similar to each such block. Then, the small target detection based on the block-matching model is formulated as an optimization problem of recovering low-rank and sparse matrices, which are effectively solved using robust principal component analysis. Finally, the results of processing are reconstructed to obtain the target and background images. A simple segmentation method is used to segment the target image. The experimental results from the actual infrared sequences show that the proposed method has better background suppression ability under complex backgrounds and better detection performance than conventional baseline methods.
Keywords: block-matching; infrared image; low-rank matrix recovery; small target detection.