Method of thresholding using two-dimensional exponent entropy and its fast algorithm
二维指数熵图像阈值选取方法及其快速算法

The two-dimensional Shannon's information entropy is a classical and commonly used image segmentation method,but there still are some disadvantages involved.Then,a two-dimensional exponent information entropy method for threshold selection was proposed here,which could overcome the disadvantages in the Shannon's entropy.The logarithm entropy was changed into the exponent entropy to get a higher speed.Meanwhile,a fast algorithm of two-dimensional exponent entropy thresholding method was also given,which changed the two-dimensional threshold into one-dimensional by using new area partition method,and the speed of the algorithm was no less than 1% of the original algorithm.The results of the experiment indicate that the proposed algorithm has high speed of calculation and good segmentation quality.