计算机科学 ›› 2012, Vol. 39 ›› Issue (7): 253-256.

• 图形图像 • 上一篇    下一篇

基于最小方差滤波的相对嫡闭值分割方法

张弘,范九伦   

  1. (西安电子科技大学电子工程学院 西安 710071) (西安邮电学院自动化学院 西安 710121) (西安邮电学院通信与信息工程学院 西安 710121)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Relative Entropy Threshold Segmentation Method Based on the Minimum Variance Filtering

  • Online:2018-11-16 Published:2018-11-16

摘要: 基于共生矩阵的相对嫡阂值分割法是一类常用的图像分割方法。采用自适应滤波方法构造非对称共生矩阵,对相对嫡阂值分割法进行改进,使其更好地适应含噪图像的阂值分割问题。实验结果表明,该方法能更有效地降低噪声干扰,使分割目标更为完整,边缘更加清晰。

关键词: 图像分割,相对嫡,共生矩阵,最小方差滤波

Abstract: The relative entropy thresholding segmentation algorithm based on the co-occurrence matrix is a commonly used image segmentation method. An asymmetric co-occurrence matrix was constructed by an adaptive filter method to improve the relative entropy thresholding segmentation method, which is better adapted to the noise images segmentation. hhe segmentation experiment results show that this method can reduce the noise interferes more effectively, and get the more complete objectives and the more distinct edge.

Key words: Image segmentation, Relative entropy, Co-occurrence matrix, Minimum variance filtering

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