Infrared dim small target segmentation method based on ALI-PCNN model

Abstract

Pulse Coupled Neural Network (PCNN) is improved by Adaptive Lateral Inhibition (ALI), while a method of infrared (IR) dim small target segmentation based on ALI-PCNN model is proposed in this paper. Firstly, the feeding input signal is modulated by lateral inhibition network to suppress background. Then, the linking input is modulated by ALI, and linking weight matrix is generated adaptively by calculating ALI coefficient of each pixel. Finally, the binary image is generated through the nonlinear modulation and the pulse generator in PCNN. The experimental results show that the segmentation effect as well as the values of contrast across region and uniformity across region of the proposed method are better than the OTSU method, maximum entropy method, the methods based on conventional PCNN and visual attention, and the proposed method has excellent performance in extracting IR dim small target from complex background.