基于非消差小波变换的多尺度边缘检测

V. Kitanovski, D. Taskovski, L. Panovski
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引用次数: 9

摘要

提出了一种基于非消差Haar小波变换的多尺度边缘检测方法。与经典的抽取Haar小波变换相比,使用未消去变换提高了检测边缘的定位。该方法对存在于多个二元尺度上的边缘进行跟踪,有利于较大尺度上的边缘。在四个可能的方向上进行非极大值抑制,并结合迟滞阈值提取边缘点。实验结果表明,该方法与经典边缘检测方法相比具有一定的竞争力。这种多尺度方法对噪声具有鲁棒性,而未消差变换的冗余保证了良好的边缘定位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-scale Edge Detection Using Undecimated Wavelet Transform
This paper presents multi-scale edge detection method using an undecimated Haar wavelet transform. The use of undecimated transform improves the localization of detected edges when compared to the classical, decimated Haar wavelet transform. The presented method tracks for edges that exist at several dyadic scales, favoring edges at larger scales. Edge points are obtained by non-maximum suppression in four possible directions, combined with hysteresis thresholding. The experimental results show that this method is competitive to classical edge detection methods. This multi-scale approach brings robustness to noise, while the redundancy from the undecimated transform ensures good edge localization.
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