【作者】 郑莹； 李光耀； 孙燮华；

【Author】 ZHENG Ying1 LI Guang-yao1 SUN Xie-hua2 1 College of Electronics and Information Engineering, Shanghai 201804 , China 2 College of Information Engineering, Zhengjiang Hang Zhou 310018, China

【机构】 同济大学电子与信息工程学院； 中国计量学院信息工程学院；

【摘要】 基于经典形态学的边缘检测方法虽然具有较好的去噪能力,但不能反映图像全部的边缘特征。在深入分析扩展数学形态学的定义基础上,提出了一种基于扩展数学形态学的多尺度多结构元素的自适应灰度图像边缘检测方法。该算法针对图象中噪声和边缘形态的不同建立了多结构元素,利用扩展灰度变换原理进行多尺度边缘提取。实验结果表明,与经典的边缘检测方法相比,该方法不仅能有效地去除噪声,而且检测得到的图像边缘具有良好的边缘特性。更多还原

【Abstract】 Image detection methods based on the classical mathematical morphology can remove noise, but have bad edge performance. On the basis of analyzing of the definition of extended mathematical morphology, a method of adaptive edge detection based on extended morphology of multiscale and multi-structure element is presented. According to the pattern of noise and edge in image, the algorithm employing multi-structure element and the principle of extended morphology in mutiscale edge detection. The simulation results has showed that compared with the traditional image edge detection algorithm, this method can not only remove image noise effectively, but also has better property of image edge.更多还原