Optimal algorithm for gradient based on edge detection
一种基于灰度的梯度边界检测优化算法*

Two approximations to gradient have been introduced to reduce the computational complexity of the gradient based edge detection algorithm. However, these approximations yield anisotropy so that the performance of the edge detection deteriorates.This paper firstly established a general mathematical model for the approximation to gradient and suggested two optimization principles of the approximation model, and then developed two optimal algorithms to reach minimum anisotropy or minimum approximation error while keeping computational simplicity.In addition,proposed some simple and direct hard-ware implementations.The mathematical analyses indicate that the performance of the proposed optimal algorithm gets better 4.4 times in isotropy and 5-7 times in approximation error than the existing approximations, and the computer simulation results support the analysis.