云背景下红外弱小目标检测算法研究

Research on detection algorithm of infrared dim small targets in cloud background

针对红外搜索跟踪设备对云背景下红外弱小目标的检测问题,提出了一种新的综合滤波算法。在对图像进行对比度增强的基础上,采用高通滤波去除大面积云背景,并利用中值滤波孤立图像点噪声,而后使用全局阈值分割法分割目标和残余噪点,从而实现小目标的检测。通过图像质量评价方法对原图像和处理后图像进行计算分析表明,背景抑制图像的信噪比和对比度得到有效提高,能够清晰检测出云背景下的红外弱小目标。实验数据有效证明了综合滤波算法的合理性和可行性。

Aiming at the problem of infrared search and tracking equipment detecting infrared dim small targets in cloud background,a new integrated filtering algorithm is proposed. On the basis of image contrast enhancement,high-pass filtering is used to remove large area cloud background,and median filtering is used to isolate image point noise,and then the global threshold segmentation method is used to segment the target and residual noise,so as to realize the detection of the small targets. Comparing the original image with the processed image by the method of image quality evaluation,the signal-to-noise ratio and contrast of the background suppressed image are effectively improved,and the infrared dim small targets in cloud background can be clearly detected. The experimental data effectively proved the rationality and feasibility of the integrated filtering algorithm.