噪声图像的快速二维Otsu阈值分割

Fast thresholding algorithm of 2D Otsu for low SNR image

为了提高二维阈值分割法处理速度,提出了二维Otsu法的快速实现方法。基于二维随机变量的边缘概率分布,将二维最佳阈值(s*,t*)的求解拆分成两个一维最佳阈值s*和t*的求解;同时为了改善原算法的分割效果,引入类内方差的定义,提出了新的最佳阈值判别式。实验结果表明,本方法不仅保留了原二维阈值法抗噪性强的特点,其时间复杂度由O(L4)降为O(L),空间复杂度由S(L2)降为S(L),且分割错误率低于原二维Otsu法。该方法适合处理高斯噪声图像的快速阈值分割问题。

In order to improve 2D thresholding algorithm＇ s processing speed, this paper presented a fast implementation method of 2D Otsu. Based on marginal probability distribution of bivariate discrete random variable, it calculated two 1 D opti- mal threshold, s ＊ and t＂ , and then kept （s ＊ ,t ＊ ） as the optimal 2D Otsu threshold. Furthermore, in order to improve the seg- mentation of the original algorithm, this paper introduced the definition of intra-class variance and proposed a new discrimi- nant. The experimental results show that the proposed algorithm outperforms original algorithm. Without losing the robustness to noise, its time complexity is reduced from O （ L4 ） to O （ L）, space complexity is reduced from S （L2 ） to S （L）, and the mis- classification rate is lower. The method is suitable for handling the fast threshold segmentation of Gaussian noise images.