A Wavelet-Based Image Edge Detection and Estimation Method with Adaptive Scale Selection
A Wavelet-Based Image Edge Detection and Estimation Method with Adaptive Scale Selection
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DOI：
10.1142/s0219691310003547
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发表时间：
2010-05
期刊：
影响因子：
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通讯作者：
Shengfei Shi;Yanning Zhang;Yuening Hu
中科院分区：
文献类型：
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作者：
Shengfei Shi;Yanning Zhang;Yuening Hu
提出了一种基于小波变换的尺度自适应边缘检测方法。该方法综合了小波域多尺度上的边缘信息，不仅定位了每个边缘点的位置，而且估计了其幅值，识别了其奇异性类型，即阶跃边缘和脊状边缘。此外，对于脊边点，该方法可以估计出脊线的宽度。与传统的边缘检测方法不同，该方法自适应地为每个边缘点选择两个最优尺度来定位和估计其方向。结果表明，该算法在定位和边缘方向估计方面取得了较好的效果。对合成图像和真实图像的实验证明了该方法的有效性。
A scale-adaptive edge detection scheme based on wavelet transform is proposed in this paper. This scheme incorporates the edge information in multiple scales of the wavelet domain, and it not only locates the position of each edge point, but also estimates its amplitude and identifies its singularity type, namely, step edge and ridge edge. Moreover, for a ridge edge point, the proposed scheme could estimate the width of the ridge. Unlike traditional edge detectors, this method adaptively selects two optimal scales for each edge point to locate it and estimate its direction. As a result, better performances in localization and edge direction estimation are achieved. Experiments on both synthetic and real images demonstrate the effectiveness of the proposed method.