Short response Hilbert transform for edge detection

S. Pei, Jian-Jiun Ding, Jiun-De Huang, Guo-Cyuan Guo
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引用次数: 12

Abstract

In this paper, we define the short-response Hilbert transform (SRHLT) and use it for edge detection. The SRHLT has a parameter b. When b = 0, it becomes the Hilbert transform (HLT). When b is infinite, it becomes differentiation. Many edge detection algorithms are based on differentiation. However, they are sensitive to noise. By contrast, when using the HLT for edge detection, the noise is reduced but the resolution is poor. The proposed SRHLT in this paper can compromise the advantages of differentiation and HLTs. It is robust to noise and can simultaneously distinguish edges from non-edge regions very successfully.
边缘检测的短响应希尔伯特变换
在本文中,我们定义了短响应希尔伯特变换(SRHLT)并将其用于边缘检测。SRHLT有一个参数b,当b = 0时,它成为希尔伯特变换(Hilbert transform, HLT)。当b是无穷时,它变成微分。许多边缘检测算法都是基于微分的。然而,它们对噪音很敏感。相比之下,当使用HLT进行边缘检测时,噪声有所降低,但分辨率较差。本文提出的SRHLT可以折衷区分和hlt的优点。该方法对噪声具有较强的鲁棒性,并能很好地同时区分边缘和非边缘区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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