一种基于数学形态学的多形状多尺度边缘检测算法

基于数学形态学的边缘检测过程中,不同形状、不同尺度的结构元素在滤除噪声和保持边缘细节方面的作用是不同的,为此提出了一种基于多形状多尺度结构元素的自适应边缘检测算法,分别使用不同方向和大小的结构元素提取图像边缘,通过计算信息熵自适应确定权重系数,对多形状结构元素和多尺度结构元素检测的边缘做融合处理.实验结果表明,该算法与几种经典边缘检测算子相比,有效抑制了噪声影响,提高了检测精度,对各种不同图像具有很好的鲁棒性.

A Multi-shape and Multi-scale Edge Detection Algorithm Based on Mathematical Morphology

In the process of edge detection based on mathematical morphology, the structural elements of different shapes/scales play different roles in noise filtering and keeping edge details intact. An adaptive edge detection algorithm based on multi-shape/scale structural elements was therefore proposed, where the image edge was extracted using different directions/sizes structural elements. Then, the weight factors were determined adaptively by computing the information entropy so as to integrate the edges detected by multi-shape and multi-scale structural elements. Experimental results showed that the proposed algorithm can suppress the interference of noise more effectively in comparison with several classical edge detection algorithm, thus improving the detection accuracy and robustness of different images.