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Sensing and Actuation: A Case for Multidisciplinary Engineering Education Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Application in Image Denoising Using Fractional Total Variation Theory

Authors : Guo Huang, Qing-li Chen, Tao Men, Xiu-Qiong Zhang, Hong-Ying Qin, Li Xu

Published in: The Proceedings of the International Conference on Sensing and Imaging

Publisher: Springer International Publishing

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Abstract

Aiming at the existing problems that the image denoising algorithm based on integer-order partial differential equation could lost part of edge and texture information. This image denoising algorithm based on fractional variational theory was proposed by the theory of fractional calculus and partial differential equation. The denoising model proposed in this paper introduces and implements the numeric computation of the fractional variation partial differential equations by constructing the fractional differential mask operators along eight directions of image. The simulation data prove that the image denoising algorithm based on fractional variation theory compared with the traditional image denoising algorithm could better retain the edge and texture detail information, obtain visual effect, and properly improve the signal-to-noise ratio.

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previous chapter An Enhanced Unscented Kalman Filter Method Based on the Covariance Intersection Algorithm
next chapter Total Variation with Overlapping Group Sparsity for Removing Mixed Noise
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Metadata
Title
Application in Image Denoising Using Fractional Total Variation Theory
Authors
Guo Huang
Qing-li Chen
Tao Men
Xiu-Qiong Zhang
Hong-Ying Qin
Li Xu
Copyright Year
2019
Book
The Proceedings of the International Conference on Sensing and Imaging

Print ISBN: 978-3-319-91658-3

Electronic ISBN: 978-3-319-91659-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-91659-0_15