一种由粗到精的大视场弱小目标检测方法

A Method of Dim and Small Target Detection in Large Field-of-View from Coarse to Fine

大视场的红外图像,由于分辨率高,对图像实现像素级处理很难满足实时性要求。针对大视场特定背景下的低空目标,提出一种由粗到精的检测方法。先将图像分块,计算分块图像熵值,组成熵值矩阵进行熵值分割,区分背景区域,得到所需求的目标可能出现的区域,完成粗检测;然后用Top-hat形态滤波法对所得区域进行精检测,得到检测目标。实测数据证明,该方法能在检测弱小目标的同时大大减少计算量,较好地满足了大视场下弱小目标的实时检测、处理需求。

Infrared image of large field-of-view （FOV） has high resolution, so it is very difficult to process the image in real time by pixel. In order to solve this problem, a method of detection from coarse to fine is put forward to detect the small flying target in a special low-altitude background. We divide image into pieces and compute the entropy, so that the entropyrs segmentation can be performed, complete the background classification and acquire the target area, itrs coarse detection. Then according to top-hat filtering, the dim and small target is detected. The experimental result shows that this method can detect the dim and small target in large FOV more efficiently and accomplish real-time detection.