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A robust tensor-based edge detection method for noisy remote sensing images

机译:一种用于嘈杂的遥感图像的鲁棒张力的边缘检测方法

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Traditional gradient based edge detection methods such as Sobel, Laplacian of Gaussian and Canny detectors which have charming applications in common images are not satisfactory in dealing with noisy remote sensing images. Aiming to solve this problem, we introduce the trace of the nonlinear local structure tensor to sort edges out of noises. Then we extracted the contours of the trace and fill the gaps in the contours. At last, edge thinning is applied to the contour map to suppress the non-maximum pixels. Experiment results demonstrate that our robust tensor-based edge detection algorithm is effective under noisy condition.
机译:基于传统的基于梯度的边缘检测方法,如Sobel,Laplacian的高斯和罐头探测器,在常见图像中具有迷人的应用程序在处理嘈杂的遥感图像方面不令人满意。 旨在解决这个问题,我们介绍了非线性局部结构张量的迹迹,以将边缘排序出噪声。 然后我们提取了迹线的轮廓并填补轮廓中的空隙。 最后,边缘变薄应用于轮廓图以抑制非最大像素。 实验结果表明,我们的强大的张量的边缘检测算法在嘈杂的情况下有效。

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