基于模板分解和积分图像的快速Kirsch边缘检测

Fast Kirsch Edge Detection Based on Templates Decomposition and Integral Image

将Kirsch算子的模板分解为差值模板和公共模板,然后通过相邻差值模板的差异比较,找出边缘强度最大的方向,并计算出相应的边缘强度值,避免了将8个方向的边缘强度全部算出,减少了Kitsch算子的模板与原图像的卷积运算.公共模板和原图像的卷积则利用灰度信息处理时得到的积分图像米加速.实验证明应用这种快速算法的Kirsch边缘检测,运算量比当前主流快速算法(FKC算法)有较大幅度的减少.另外,运用模板分解和积分图像减少卷积运算的思路具有一定通用性,实例说明此思路可用于一些其它边缘检测和空域滤波算法中.

Templates of Kirsch operators are decomposed into difference templates and a common template. By a contrast between every two-neighbor difference templates, the direction of maximum edge intensity is found and the corresponding value of edge intensity is worked out. Thus it is no longer necessary to compute the edge intensity in eight directions, greatly reducing the convolution between templates of Kirsch operators and original image, and at the same time accelerating the convolution between the common template and original image by integral image that has been worked out in gray information processing. Using such a fast algorithm, Kirsch edge detection is made much less time-consuming than that of the current mainstream fast algorithm （FKC algorithm）. The validity is proved by experiments. The idea of reducing convolution with templates decomposition and integral image has some universality. Examples show that this idea can also be applied in other edge detection algorithms and space filters.