Infrared Dim and Small Target Detection and Tracking Based on Single Multi-Frame Algorithm under Sea Clutter Background

Infrared dim and small target detection and track under sea clutter is significant and crucial in the infrared image process. It is a difficult task because of the disturbing clutter, the changing scenario and weak targets. In this paper, a complete process to detect and track dim small targets is proposed. Firstly, we use Mean and 3D Filtering with Block-Matching (M3DBM) algorithm to denoise infrared images. Inspired by the well-known BM3D algorithm and NLM algorithm, M3DBM can keep small targets from impair while denoising. Then, we use Butterworth high-pass filter and morphological filter to extract possible targets from single frame image. Finally, an optimal pipeline filtering algorithm (OPF) based on target position prediction and multi-target stable track is proposed. Optimal means that choose the best pipe for target and vice versa. OPF can track targets stably and accurately. The experimental results show that the proposed algorithm achieves good results in both accuracy and efficiency.