A Method of Small Target Detection in Infrared Image Sequences Based on the Least Absolute Deviation and Chaos-genetic Algorithms
基于最小一乘和混沌遗传算法检测红外小目标

A method of small target detection in infrared image sequences was proposed based on the least absolute deviation background predication and chaos-genetic algorithms.Prediction model of the background signal based on the least absolute deviation criterion was founded.Based on characters of the least absolute deviation estimation,the extreme value was extracted by the chaos-genetic algorithms,obtained by using chaotic variable in genetic algorithms.The estimated image subtracted from the source image gave the residual image.And,the fast threshold selection algorithm based on the two-dimensional exponent entropy was used to segment the residual image.The experimental results are given and analyzed.Compared with the method based on least squares estimation and the traditional genetic algorithms,the results show that approach can precisely detect the small infrared target and has better results.