一种新的阈值分割方法

New Image Threshold Segmentation Algorithm

提出了一种基于Renyi熵原理的阈值分割方法.该方法首先计算代表目标的熵和代表背景的熵,然后求出两熵之差并取其绝对值,最佳阈值对应于其中的最小值.Renyi熵比其它熵多了一个参数,此参数使得Renyi熵能处理更多类型的图像.将上述方法进行仿真实验,并且仿真其它熵方法,仿真结果显示,该算法比其他熵方法效果更有效、更一般化.

A thresholding segmentation algorithm based on Renyi＇s entropy is presented. The algorithm calculates the entropy of object and the entropy of background firstly. Then the absolute value of difference between two entropies is gained. The threshold value is corresponding to the minimum of the absolute values. Renyi＇s entropy has an additional parameter comparing to other entropies. The additional parameter makes it process more type of image. The simulating result shows that this algorithm is better than other two-dimensional entropy algorithms.