分数阶高斯微分边缘检测算子
Novel Edge Detection Operator Based On Fractional Gaussian Differential
本文提出了一种改进的边缘检测算法.该方法将高斯平均算子与1-2阶分数阶微分法相结合,利用高斯算子的去噪性能和分数阶微分算子保留图像细节信息的特性,使图像边缘检测效果得到明显改善.本文对该方法做了理论分析和实验验证,结果表明：该方法能够有效地提取图像的边缘信息,对边缘附近的细部细节能够进行部分保留,对有噪声图像的边缘检测显示出较强的抗噪性.
his paper presents an improved algorithm for edge detection. The algorithm combines the Gaussian average operator with 1-2 order fractional differential.Gaussian average operatorhas outstanding performance in image denoising and 1-2 order fractional differential retain more detailed imageinformation during sharping. It has been proved by theoretical analysis and experimental verificationsthat this method could extract image edge information effectively and reserve partial near edgedetails, and shows better noise immunity in edge detection.
韩其睿、刘克
数学
分数阶微分边缘检测滤波图像增强
Edge detection Fractional differential Gaussian averaging
韩其睿,刘克.分数阶高斯微分边缘检测算子[EB/OL].(2014-05-15)[2025-08-10].http://www.paper.edu.cn/releasepaper/content/201405-237.点此复制
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