An Infrared Small Target Detection Algorithm Based on Peak Aggregation and Gaussian Discrimination

Abstract

Due to its inherent characteristics, infrared small target detection plays an important role in the field of image detection. In order to improve the detection accuracy of small infrared targets under complex sea background, by analyzing the difference between small targets and sea clutter, we propose an infrared small target detection algorithm based on the peak aggregation number and Gaussian discrimination. First we remove the background through local large value detection and extracts suspect targets. Then, the peak aggregation number of the suspected target is counted to eliminate most of the strong wave clutter and strong island edges. Finally, the small waves are eliminated by Gaussian discrimination. The experimental results show that our algorithm has good performance under strong noise interference and calm sea conditions.