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改进Canny边缘检测的遥感影像分割

刘丽霞 李宝文 王阳萍 杨景玉

计算机工程与应用2019,Vol.55Issue(12):54-58,180,6.
计算机工程与应用2019,Vol.55Issue(12):54-58,180,6.DOI:10.3778/j.issn.1002-8331.1811-0180

改进Canny边缘检测的遥感影像分割

Remote Sensing Image Segmentation Based on Improved Canny Edge Detection

刘丽霞 1李宝文 2王阳萍 1杨景玉3

作者信息

  • 1. 兰州交通大学 电子与信息工程学院,兰州 730070
  • 2. 兰州铁路局 计划统计处,兰州 730000
  • 3. 甘肃省人工智能与图形图像处理工程研究中心,兰州 730070
  • 折叠

摘要

Abstract

In the image segmentation algorithm based on edge features, it is the premise and key to accurately detect the edge. Aiming at the shortcomings of remote sensing image segmentation algorithms, such as poor robustness, easy edge information loss and narrow application range, this paper proposes a remote sensing image segmentation algorithm based on improved Canny edge detection. For the traditional Canny Gaussian filter, the image is smoothed while smoothing the image, and the image is smoothed by the guidance filtering with the edge-preserving property. For the problem that the noise is sensitive to the derivative, the gradient template is added to calculate the image gradient and direction. For the lim-itation of setting the high and low thresholds by the traditional Canny operator, the Ostu algorithm is used to adaptively select the high and low thresholds according to the gray level of the image. In order to make full use of the advantages of multi-spectral images, band decomposition is performed in the edge detection, and processing is performed on a band-by-band basis, and then the edges are integrated into a result image, and finally region growth is performed. The experimental results show that compared with the traditional detection edge segmentation method, the proposed method achieves good results in remote sensing image segmentation.

关键词

图像分割/边缘检测/引导滤波/Canny算子

Key words

image segmentation/ edge detection/ guided filter/ Canny

分类

信息技术与安全科学

引用本文复制引用

刘丽霞,李宝文,王阳萍,杨景玉..改进Canny边缘检测的遥感影像分割[J].计算机工程与应用,2019,55(12):54-58,180,6.

基金项目

国家自然科学基金(No.41761082) (No.41761082)

甘肃省科技计划项目(No.18JR3RA104) (No.18JR3RA104)

甘肃省教育厅科技项目(No.2017D-08) (No.2017D-08)

兰州铁路局科研开发计划项目. ()

计算机工程与应用

OA北大核心CSCDCSTPCD

1002-8331

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