Infrared small target detection algorithm based on potential regions proposal

A novel infrared small target detection algorithm based on potential regions proposal is proposed in this paper. Potential regions mean subsets (size are 16 by 16 in this paper) with small targets of an infrared image. A convolution neural network (CNN) classifier has been trained by using constructed datasets to discriminate potential regions of an input image. Traditional methods such as tophat transform, max-mean and max-median filter are used to suppress the background and noise of potential regions. Some experiments are carried out to verify the algorithm performance, and the results show that the gains of signal noise ratio and contrast ratio have better performance than traditional methods.