Fractional spectral graph wavelets and their applications
Computer Vision and Pattern Recognition
2019-02-28 v1
Abstract
One of the key challenges in the area of signal processing on graphs is to design transforms and dictionaries methods to identify and exploit structure in signals on weighted graphs. In this paper, we first generalize graph Fourier transform (GFT) to graph fractional Fourier transform (GFRFT), which is then used to define a novel transform named spectral graph fractional wavelet transform (SGFRWT), which is a generalized and extended version of spectral graph wavelet transform (SGWT). A fast algorithm for SGFRWT is also derived and implemented based on Fourier series approximation. The potential applications of SGFRWT are also presented.
Cite
@article{arxiv.1902.10471,
title = {Fractional spectral graph wavelets and their applications},
author = {Jiasong Wu and Fuzhi Wu and Qihan Yang and Youyong Kong and Xilin Liu and Yan Zhang and Lotfi Senhadji and Huazhong Shu},
journal= {arXiv preprint arXiv:1902.10471},
year = {2019}
}
Comments
27 pages, 4 figures, 1 table