Based on a nonlocal Laplacian operator, a novel edge detection method of the grayscale image is proposed in this paper. This operator utilizes the information of neighbor pixels for a given pixel to obtain effective and delicate edge detection. The nonlocal edge detection method is used as an initialization for solving the Allen-Cahn equation to achieve two-phase segmentation of the grayscale image. Efficient exponential time differencing (ETD) solvers are employed in the time integration, and finite difference method is adopted in space discretization. The maximum bound principle and energy stability of the proposed numerical schemes are proved. The capability of our segmentation method has been verified in numerical experiments for different types of grayscale images.
翻译:在非本地拉普拉西亚操作员的基础上,本文件建议对灰度图像采用一种新的边缘探测方法。 该操作员利用邻居像素的信息对给定像素进行有效和微妙的边缘探测。 非本地边缘探测方法用作解决Allen-Cahn等式的初始程序,以便实现灰度图像的两阶段分割。 在时间整合中使用了高效的指数时间差异求解(ETD)解答器,在空间离散中采用了有限差异方法。 证明了拟议数字方法的最大约束原理和能量稳定性。 我们的分解方法的能力已在不同类型灰度图像的数字实验中得到验证。