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Using the Canny edge detector and mathematical morphology operators to detect vegetation patches

机译:使用Canny边缘检测器和数学形态学算子检测植被斑块

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摘要

Numbers and areas and locations of vegetation community patch are the important parameters for vegetation function and structure researches. In this paper, these parameters of vegetation patches are detected using the Canny edge detector and mathematical morphology operators. Firstly, part of a SPOT 5 fusion-ready color image is transformed into the gray image, then, stretched according to the histogram of the gray image in order to enhance the interesting vegetation patches. Secondly, using the Wiener filter to remove the noise and Canny edge detector to find the edges of the targets in the gray image. Finally, vegetation patches are detected based on the mathematical morphology criterion of circle and ellipse object and the centers of the patches are located. The experiments show that integration the Canny edge detector with the algorithms for extracting circle and ellipse object based on mathematical morphology are simple and effective for detecting vegetation patches.
机译:植被群落斑块的数量,面积和位置是植被功能和结构研究的重要参数。在本文中,使用Canny边缘检测器和数学形态学运算符检测植被斑块的这些参数。首先,将SPOT 5融合就绪彩色图像的一部分转换为灰度图像,然后根据灰度图像的直方图进行拉伸,以增强有趣的植被斑块。其次,使用维纳滤波器去除噪声,并使用Canny边缘检测器在灰度图像中找到目标的边缘。最后,根据圆形和椭圆形物体的数学形态学准则检测植被斑块,并确定斑块的中心。实验表明,将Canny边缘检测器与基于数学形态学的圆形和椭圆形物体提取算法集成在一起,可以简便,有效地检测植被斑块。

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