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采用凝视焦平面阵列(FPA)的红外成像制导技术以其优越的性能在空空导弹中得到了广泛的应用。由于空中飞机目标表面各部位的温度不同,使得红外成像探测装置获得的目标图像的不同部位存在着较大的灰度差异,这给正确分割出目标带来了很大的困难。针对飞机目标红外图像的特点和成像制导技术中图像分割的目的,文中提出了一种有利于目标特征点识别的图像分割算法,它首先对目标红外图像进行阈值分割,然后选取合适的结构元素并利用数学形态学的并行性特点对目标内部的空洞区域进行填充,最后得到比较精确的分割图像,这种分割结果对基于灰度连续性的目标特征点识别算法非常有利。
The infrared imaging guidance technology with the gaze focal plane array (FPA) has been widely used in air-to-air missiles due to its superior performance. Due to the different temperature of each part of the target surface of the air plane, there is a big difference in gray level between the different parts of the target image obtained by the infrared imaging detection device, which brings great difficulties for the correct segmentation of the target. According to the characteristics of the target infrared image and the purpose of image segmentation in the imaging guidance technology, an image segmentation algorithm is proposed in this paper, which is beneficial to the target feature recognition. Firstly, the target infrared image is segmented by threshold, and then the appropriate structural elements are selected The parallelism of mathematical morphology is used to fill the empty area inside the target, and finally a more accurate segmentation image is obtained. This segmentation result is very beneficial to the target feature point recognition algorithm based on gray continuity.