摘要
针对合成孔径雷达(SAR)图像的特点,本文提出基于灰度直方图的混合偏移Rayleigh分布假设下的最小误差阈值化分割算法,并与现有的基于Gauss和Poisson分布假设下的最小误差分割算法以及经典的Otsu算法作了比较。实验和Kolmogorov-Smirnov检验结果表明对SAR图像而言,基于Rayleigh假设的算法可以取得更好的分割效果。
This paper presents a minimum error thresholding algorithm under the hypothesis that the gray level histogram of SAR image fitting to a mixture model of shifted Rayleigh distribution. This algorithm is applied to real SAR images and compared with traditional Otsu algorithm and other minimum error thresholding algorithms based on various models of histogram. The hypothesis of Rayleigh distribution model is confirmed by Kolmogorov-Smirnov testing and the results obtained show that the proposed new algorithm has good performance in image thresholding for SAR images.
基金
国家自然科学基金
关键词
SAR图像
Ravleigh分布
图像分割
K-S检验
SAR image, Rayleigh distribution, Minimum error thresholding, Kolmogorov-Smirnov testing
