【摘要】 提出一种在噪声图像中基于边缘分段自增强的启发式边缘搜索算法.首先对噪声图像进行小尺度高斯滤波;再使用本文设计的新型边缘检测算子获取引导信息,此边缘检测算子在定位精度、抑制噪声和虚假边缘方面具有较好的性能;然后对各搜索轨迹进行分段自增强;最后根据自增强累积的程度获取噪声图像的边缘.实验结果表明:此算法能够有效地从噪声图像中提取物体的真实边缘,并能最大限度地保留细节信息,其性能优于经典的 Can-ny 算子.更多还原

【Abstract】 A novel heuristic search algorithm based on sub-edge self-reinforce for edge extraction in noise image is proposed in this paper.Firstly,The noise image is filtered by a small scale Gaussian Filter.Then a new Large Template Edge Detector is designed in order to get more accurate leading information,and the corresponding search trajectories are self-reinforced according to this information.Finally,the real edge of noise image is extracted according to the accumulated degree of self-reinforces.The new Large Template Edge Detector has good performance in orientation precision,noise resistance and false edge.Experimental results on image with noise demonstrate better performance of the proposed method,which keeps more image details in extracting real edges of objects,compared with the classical methods,especially Canny Operator.更多还原