一种改进的舰船红外图像分割算法

Improved method of infrared warship image segmentation

图像分割在图像分析和识别中具有重要的意义,针对最大类间方差法—Otsu法在复杂背景或目标灰度与其周围背景灰度相差不大情况下,目标相对面积较小时易出现目标与背景误分割的问题,提出了一种改进的Otsu法。该算法先对预处理后的红外舰船图像归一化投影,然后,按一定阈值对图像进行裁剪,最后,利用Otsu法进行分割。实验结果表明:与Otsu法、递归Otsu法相比,该算法能够更好地分割出目标。

Image threshold segmentation is very important in image analysis and recognition, in view of the problem of maximal variance between-class method-Otsu method that the background and target information being erroneously segmented when object size is relative small in complex background or the object and background has small gray level difference, an improved maximal variance between-class method is put forward. The method is to make a normalized projection for the preprocessing infrared warship image, the image with a certain threshold is cut down, Otsu method is used to segment the image. A comparison among the Otsu method, the recursive Otsu method and this method is carried out ,the experimetal results show that the method has a good adaptive and best segmentation performance.