二维直方图准分的Tsallis熵阈值分割及其快速实现

传统二维Tsallis熵阈值法主要由于对二维直方图采用近似假设等原因,导致分割结果不够准确,由此提出了基于二维直方图准分的Tsallis熵快速图像分割方法.首先,准确选择邻域模板构建二维直方图并将Tsallis熵法用于此直方图上以便提高分割性能;然后,舍弃二维直方图中关于主对角区域的概率和近似为1的假设而准确计算使阈值选取更准确;最后,结合Tsallis熵公式对二维直方图进行分析得到其特性和2个定理,利用此特性和2个定理导出新型、快速的递推算法来降低计算复杂度.实验结果表明,与传统二维Tsallis熵法相比,所提出的方法不仅分割更准确和抗噪性更强,而且占用的存储空间和运行时间都更少.

Precise 2-D Tsallis entropy image threshold segmentation and its fast recursive realization

Traditional two-dimensional(2-D) Tsallis entropy(TE) thresholding methods can not obtain accurate results mainly owing to the supposition that the sum of the probabilities of 2-D histogram main-diagonal region is approximately one.So a fast and precise 2-D TE image thresholding method is proposed in this paper.First,a 2-D histogram is created through accurately selecting neighborhood template and the TE method is used on the 2-D histogram to improve the segmentation performance.Then,with precise calculation...