Wang Xin
School of Information Science and Engineering, Shandong University, Jinan, China.
IEEE Trans Pattern Anal Mach Intell. 2007 May;29(5):886-90. doi: 10.1109/TPAMI.2007.1027.
Laplacian operator is a second derivative operator often used in edge detection. Compared with the first derivative-based edge detectors such as Sobel operator, the Laplacian operator may yield better results in edge localization. Unfortunately, the Laplacian operator is very sensitive to noise. In this paper, based on the Laplacian operator, a model is introduced for making some edge detectors. Also, the optimal threshold is introduced for obtaining a Maximum a Posteriori (MAP) estimate of edges.
拉普拉斯算子是一种常用于边缘检测的二阶导数算子。与基于一阶导数的边缘检测器（如Sobel算子）相比，拉普拉斯算子在边缘定位方面可能会产生更好的结果。不幸的是，拉普拉斯算子对噪声非常敏感。在本文中，基于拉普拉斯算子，引入了一种用于制作一些边缘检测器的模型。此外，还引入了最优阈值以获得边缘的最大后验（MAP）估计。
