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Edge detection method for remote sensing image based on morphological variable structuring element 被引量:4
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作者 yao li juan WANG Xiao peng +1 位作者 WANG Wei MA Wen gang 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2018年第3期233-240,共8页
There are problems such as incomplete edges and poor noise suppression when a single fixed morphological structuring element is used to detect the edges in remote sensing images. For this reason, a morphological edge ... There are problems such as incomplete edges and poor noise suppression when a single fixed morphological structuring element is used to detect the edges in remote sensing images. For this reason, a morphological edge detection method for remote sensing image based on variable structuring element is proposed. Firstly, the structuring elements with different scales and multiple directions are constructed according to the diversity of remote sensing imagery targets. In order to suppress the noise of the target background and highlight the edge of the image target in the remote sensing image by adaptive Top hat and Bottom hat transform, the corresponding adaptive morphological operations are constructed based on variable structuring elements; Secondly, adaptive morphological edge detection is used to obtain multiple images with different scales and directional edge features; Finally, the image edges are obtained by weighted summation of each direction edge, and then the least square is used to fit the edges for accurate location of the edge contour of the target. The experimental results show that the proposed method not only can detect the complete edge of remote sensing image, but also has high edge detection accuracy and superior anti-noise performance. Compared with classical edge detection and the morphological edge detection with a fixed single structuring element, the proposed method performs better in edge detection effect, and the accuracy of detection can reach 95 % 展开更多
关键词 edge detection remote sensing image variable structuring element least squares method
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