Adaptive Morphological Operator on Graph Space

MA Shu-liang; WANG Jun-ping; DENG Cheng; FENG Yu-ying

doi:10.3969/j.issn.0372-2112.2018.01.017

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Adaptive Morphological Operator on Graph Space

更新时间：2025-07-16

- Adaptive Morphological Operator on Graph Space
- Acta Electronica Sinica Vol. 46, Issue 1, Pages: 118-126(2018)
- 作者机构：
  
  西安电子科技大学通信工程学院,陕西,西安,710071
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61173088);Xi'an Industrial Technology Innovation Project of Shaanxi Province (No.CX1248⑤)
- DOI：10.3969/j.issn.0372-2112.2018.01.017
  CLC： TP391.4
- Published Online：25 January 2018，
  
  Published：2018
- 稿件说明：
移动端阅览
MA Shu-liang, WANG Jun-ping, DENG Cheng, et al. Adaptive Morphological Operator on Graph Space[J]. Acta Electronica Sinica, 2018, 46(1): 118-126.
DOI：

MA Shu-liang, WANG Jun-ping, DENG Cheng, et al. Adaptive Morphological Operator on Graph Space[J]. Acta Electronica Sinica, 2018, 46(1): 118-126. DOI： 10.3969/j.issn.0372-2112.2018.01.017.

摘要

为了解决现有图空间上形态学应用中固定选取结构元素的问题，在图空间上提出了相似权的概念，定义了自适应结构图，对结构图的性质进行了证明.在此基础上提出一种图空间上自适应形态学算子，并从理论上验证了该算子的完备性.新算子不仅考虑了图像像素点的局部特征，同时考虑了连续像素的全局特征.实验结果表明，新算子不仅在保存彩色信息的完整及关联性方面优于现有的彩色形态学，而且可以根据图像的特征自适应的选取阈值和结构元素，在更精细的图像处理方面具有良好的应用前景.

Abstract

In order to solve the problem of fixed structure element in traditional mathematical morphology on graph space

the concept of similarity weight on graph space is put forward

and the adaptive structure graph is defined. The property of structure graph is analyzed and proved. The new adaptive morphological operator on graph space is advanced on this basis and the properties of the operator are put forward and analyzed theoretically. The new operator considers not only the local feature of image pixels but also the global features of continuous pixels. The experimental results show that the new operator is superior to existing color morphology in maintaining integrity and correlation of the image information

and can select threshold value and structure element according to the characteristics of the image

thus it has a broad application prospect in more sophisticated image processing aspects.

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