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A Robust Edge Detection Algorithm Based on CR-DSmT

机译：基于CR-DSmT的鲁棒边缘检测算法

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摘要

By employing the single scale edge detection operators, a small difference between the real edges and the measurement of noise spots for detecting from the reality leads to the problems that the small features may be doped with the noise, and that the efficiency of detecting edge is low. As to the problems, the robust edge detection algorithm based on CR-DSmT is presented. First of all, the multi-scale edge detections of the image are detected and extracted. Then the measures are fused according to the evidence reasoning. Basic Belief Assignment (BBA) construction technique of bidirectional exponential edge detection is offered, which is employed to adjust the belief assignment differences between the real edges and noise by the significant coefficient-, to fuse by the CR-DSmT combination technique, and to determine the final edge pixel by the bi-threshold technique accordingly. Simulation experiments show that it suppresses noise and maintain the detail information in the process of detecting edge.
机译：通过采用单尺度边缘检测算子，真实边缘与用于从现实中检测的噪声点的测量之间的微小差异导致了以下问题：小特征可能被噪声掺杂，并且检测边缘的效率不高。低。针对这些问题，提出了一种基于CR-DSmT的鲁棒边缘检测算法。首先，检测并提取图像的多尺度边缘检测。然后根据证据推理对措施进行融合。提供了双向指数边缘检测的基本信念分配（BBA）构造技术，该技术可通过有效系数来调整真实边缘与噪声之间的信念分配差异，并通过CR-DSmT组合技术进行融合，并确定最终边缘像素采用双阈值技术。仿真实验表明，该算法在边缘检测过程中能够抑制噪声并保持细节信息。

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