为了提高检测红外弱小目标的速度和精度,提出了一种用于预检测红外弱小目标的灰度迭代法。通过由红外图像X的灰度均值、最大值和抑制比定义的迭代函数系统对X的灰度值进行分形迭代来降低X中的背景灰度值和噪声灰度值,从而增强X中红外弱小目标的亮度。运用这种方法对夜空、乌云和丛林三类单帧红外图像进行分形处理,预检测效果较好。 In order to improve the speed and accuracy of infrared weak targets detection, a gray-level iteration method is proposed for pre-detection of infrared weak targets. The background gray value and noise gray value in X are reduced by the iterative function system defined by the mean, maximum and suppression ratio of the infrared image X. The X mid-infrared weakness is enhanced The brightness of the target. Applying this method to the fractal processing of night sky, dark clouds and jungle three types of single-frame infrared images, pre-detection is better.