Riesz transform associated with the fractional Fourier transform and applications in image edge detection

被引:30
作者
Fu, Zunwei [1 ]
Grafakos, Loukas [2 ]
Lin, Yan [3 ]
Wu, Yue [1 ]
Yang, Shuhui [3 ]
机构
[1] Linyi Univ, Sch Math & Stat, Linyi 276000, Peoples R China
[2] Univ Missouri, Dept Math, Columbia, MO 65211 USA
[3] China Univ Min & Technol, Sch Sci, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
Fractional Fourier transform; Fractional Riesz transform; Edge detection; Chirp Hardy space; Fractional multiplier; SPACES;
D O I
10.1016/j.acha.2023.05.003
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The fractional Hilbert transform was introduced by Zayed [30, Zayed, 1998] and has been widely used in signal processing. In view of its connection with the fractional Fourier transform, Chen, the first, second and fourth authors of this paper in [6, Chen et al., 2021] studied the fractional Hilbert transform and other fractional multiplier operators on the real line. The present paper is concerned with a natural extension of the fractional Hilbert transform to higher dimensions: this extension is the fractional Riesz transform and is given by multiplication which a suitable chirp function on the fractional Fourier transform side. In addition to a thorough study of the fractional Riesz transform, in this work we also investigate the boundedness of singular integral operators with chirp functions on rotation invariant spaces, chirp Hardy spaces and their relation to chirp BMO spaces, as well as applications of the theory of fractional multipliers in partial differential equations. Through numerical simulation, we provide physical and geometric interpretations of high-dimensional fractional multipliers. Finally, we present an application of the fractional Riesz transforms in edge detection which verifies a hypothesis insinuated in [26, Xu et al., 2016]. In fact our numerical implementation confirms that amplitude, phase, and direction information can be simultaneously extracted by controlling the order of the fractional Riesz transform. & COPY; 2023 Elsevier Inc. All rights reserved.
引用
收藏
页码:211 / 235
页数:25
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