Department of Electrical Engineering, State University of New York, Amherst Campus, Buffalo, NY 14260.
IEEE Trans Pattern Anal Mach Intell. 1987 Apr;9(4):569-77. doi: 10.1109/tpami.1987.4767944.
This correspondence describes a new algorithm for extracting edges from natural images. Starting from a simple image model, the algorithm poses the problem of edge extraction as a statistical classifier problem. The algorithm is capable of extracting and detecting edges from images even in the presence of noise. A step by step mathematical derivation of the algorithm reveals the flexibility of the algorithm with pertinent parameters that can be varied for the specific need of the user. Finally, the proposed edge operator is compared to the well-known Marr-Hildreth's edge operator.
这封通信描述了一种从自然图像中提取边缘的新算法。该算法从一个简单的图像模型出发，将边缘提取问题转化为统计分类器问题。即使在存在噪声的情况下，该算法也能够从图像中提取和检测边缘。算法的逐步数学推导揭示了算法的灵活性，其中包含可以针对用户的特定需求进行调整的相关参数。最后，将提出的边缘算子与著名的 Marr-Hildreth 边缘算子进行了比较。
