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融合小波变换与数学形态学的图像边缘检测
引用本文:朱士虎.融合小波变换与数学形态学的图像边缘检测[J].现代计算机,2011(24):38-41.
作者姓名:朱士虎
作者单位:徐州师范大学物理与电子工程学院
基金项目:江苏省高校自然科学研究计划资助项目(No.08KJB140010);江苏省徐州师范大学自然科学基金资助项目(No.09XLA04)
摘    要:针对传统图像边缘检测方法抗噪能力不足、边缘定位不精确等缺点,提出一种融合小波变换和数学形态学的图像边缘检测算法。先将图像进行小波分解,高频部分利用小波模极大值算法进行边缘检测,可以有效提取高频边缘;低频部分采用形态学多结构元算法进行边缘检测,能够检测出低频边缘;最后对两种方法得到的边缘图像进行融合。实验结果表明,该算法能有效抑制噪声,提高边缘精度并且定位准确。

关 键 词:小波变换  边缘检测  多结构元  图像融合

An Image Edge Detection Algorithm Based on Wavelet Transform and Mathematical Morphology
ZHU Shi-hu.An Image Edge Detection Algorithm Based on Wavelet Transform and Mathematical Morphology[J].Modem Computer,2011(24):38-41.
Authors:ZHU Shi-hu
Affiliation:ZHU Shi-hu (School of Physics & Electronic Engineering,Xuzhou Normal University.Xuzhou 221116)
Abstract:Considering the disadvantages in the traditional image edge detection methods,such as emergence of noises edges and inaccurate edge location,proposes a fusion edge detection algorithm based on the combination of wavelet transform with the mathematical morphology to solve the problems above.The image is divided by wavelets,and then the algorithm of the wavelet module maximum coefficients is applied to the high frequency part of the image,so noises can be suppressed effectively.The multi-elements mathematical morphology algorithm is applied to the low frequency part of the image,so weak edges can be detected with high quality.Finally,the two images mentioned above are fused.The result shows that the proposed algorithm can suppress noises efficiently,improve the accuracy of image edges and accurate location.
Keywords:Wavelet Transform  Edge Detection  Multi-Scale Elements  Image Fusion
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