【 中文摘要 】本发明提出一种基于多尺度形态学图像融合的加权局部熵红外小目标检测方法，首先，对红外图像进行转换至灰度域进行处理；其次，对红外图像进行多尺度形态学Top‑Hat图像分割处理，在相邻尺度的Top‑Hat的基础上求图像差异，得到最小差异图，再将最小差异图与经Top‑Hat变换的图像的最小均值图做融合，得到背景抑制后的图像；然后，通过计算初始图像的局部熵，得到局部熵信息图；之后，对背景抑制后的图像与局部熵信息图进行点乘，并归一化，得到红外小目标的显著图；最后，利用阈值分割技术对红外小目标显著图滤波并二值化，得到处理后图像，其中的二值化为1的区域就是红外小目标。本发明适合于红外小目标检测领域，能够有效的提高红外小目标检测的准确率，并且有效的降低虚警率。

【 英文摘要 】The invention provides a weighted local entropy infrared small target detection method based on multi-scale morphological image fusion, and the method comprises the steps : firstly, converting an infrared image into a gray domain, and carrying out the processing; secondly, performing multi-scale morphology Top-Hat image segmentation processing on the infrared image; solving image difference on thebasis of adjacent scale Top-Hat and obtaining minimum difference graph is obtained, and then comparing the minimum difference graph with a minimum mean value image of the image subjected to Hat transformation to obtain an image subjected to background suppression; then, obtaining a local entropy information graph by calculating the local entropy of the initial image; then, carrying out dot multiplication on the image subjected to background suppression and the local entropy information graph, and carrying out normalization to obtain a saliency map of the infrared small target; and finally, filtering and binarizing the infrared small target saliency map by using a threshold segmentation technology to obtain a processed image, the region with the binarized value of 1 being the infrared smalltarget. The method is suitable for the field of infrared small target detection, can effectively improve the accuracy of infrared small target detection, and effectively reduces the false alarm rate.

【 技术功效 】