基于分解的二维Renyi灰度熵的图像阈值分割  

Decomposition based two-dimensional thresholding for image using Renyi gray entropy

作　　者：龚劬[1] 王菲菲[1] 倪麟[1] 

机构地区：[1]重庆大学数学与统计学院,重庆401331

出　　处：《计算机工程与应用》2013年第1期181-185,共5页Computer Engineering and Applications

基　　金：重庆大学"211工程"三期创新人才培养计划建设项目(No.S-09110)

摘　　要：针对传统二维Renyi熵阈值法的高计算复杂性,提出一种新的基于分解的二维Renyi灰度熵阈值分割方法。该方法通过求解两个一维Renyi灰度熵阈值替代二维Renyi灰度熵的最佳阈值,理论上证明当满足一定条件时,两者等价;同时将计算复杂度由O(L4)降到O(L),所耗时间约为传统二维Renyi熵算法的1/10000。Because of the high computational complexity of classical 2D Renyi entropy thresholding, a new 2D Renyi gray entropy image thresholding is proposed. This method calculates two optimal thresholds of 1D Renyi gray entropy algorithm inde-pendently instead of the optimal threshold of a 2D Renyi gray entropy algorithm. It proves that the two are equal when some condition is satisfied, and its computational complexity is reduced from O（L4） to O（L）, the computational time is only one ten-thousandth of the computational time than of the classical method.

关 键 词：图像分割 阈值选取 RENYI熵 分解 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]