Journal of Systems Engineering and Electronics ›› 2010, Vol. 32 ›› Issue (5): 1055-1059.doi: 10.3969/j.issn.1001-506X.2010.05.038

• 软件、算法与仿真 • 上一篇    下一篇

灰度图像的模糊Renyi熵多级阈值分割方法

聂方彦1,2, 高潮1, 郭永彩1   

  1. (1. 重庆大学光电工程学院光电技术及系统教育部重点实验室, 重庆 400030; 2. 湖南文理学院计算机学院, 湖南 常德 415000)
  • 出版日期:2010-05-24 发布日期:2010-01-03

Multilevel thresholding method based on fuzzy Renyi entropy for gray-level images

NIE Fang-yan1,2, GAO Chao1, GUO Yong-cai1   

  1. (1. Key Lab of Optoelectronic Technology and Systems, Coll. of Optoelectronic Engineering, Chongqing Univ., Chongqing 400030, China;2. Coll. of Computer, Hunan Univ. of Arts and Science, Changde 415000, China)
  • Online:2010-05-24 Published:2010-01-03

摘要:

为克服Renyi熵阈值化方法在处理图像固有模糊特性上的不足,基于模糊集理论,提出一种有效的图像多级阈值化方法。把图像转换到模糊域,定义分割区域的模糊Renyi熵,然后应用最大熵原理对图像实施阈值分割。另外,在方法实现中采用差分演化算法搜索最佳阈值,以提高计算效率。在合成及真实图像上的实验结果表明了提出方法的有效性,同时,运用差分演化算法使方法满足图像分割时间性能需求。

Abstract:

In order to overcome the deficiency of Renyi entropy-based thresholding method on images with inherent fuzzy characteristics, a valid multilevel thresholding method based on fuzzy set theory is presented. The Renyi entropies of fuzzy partitions are defined when the image is converted to the fuzzy domain, and then the image is segmented by maximum entropy principle. In addition, the differential evolution algorithm is used to search the optimal thresholds and improve the computational efficiency in implementation of the proposed method. Experimental results on both synthetic and real images demonstrate the effectiveness of the proposed method. Meanwhile, the proposed method satisfies the time performance requirements of image segmentation when the differential evolution algorithm is used.