红外小目标检测一直是图像处理研究的热点和难点, 由于受到多种因素的影响, 红外小目标图像存在信噪比低、对比度差的问题, 目标容易被背景所覆盖。研究天空背景红外图像特征, 针对图像场景各部分的特点, 采用形态学算法对原始图像进行预处理, 剔除噪声的影响, 然后利用图像像素间的相关性, 即若同为目标像元, 则在水平和垂直方向上, 灰度变化一般较为平缓, 据此利用对角线邻域像素差值信息, 对噪声抑制后的图像进行红外小目标检测。仿真实验结果表明, 该算法计算简单方便, 能够较为有效地提取出目标。

Infrared small target detection has been the hot and difficult research of image processing, influenced by many factors, infrared small target images have the problems of low signal to noise ratio (SNR), poor-contrast and easy to be covered by background. Infrared image characteristics in sky background are researched. According to the characteristics of image scene, morphological algorithm is used to preprocess the original image and suppress noise influence. And then, using the correlation between pixels, if the same target cell, gray variance is generally gentler in horizontal and vertical directions, and the diagonal neighboring pixel difference information is used to perform infrared small target detection to noise suppressed images. Simulation results show that the algorithm is simple and convenient and can effectively extract targets.