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2017 | OriginalPaper | Chapter

A Double Recursion Algorithm to Image Restoration from Random Limited Frequency Data

Authors : Xiaoman Liu, Jijun Liu

Published in: Image and Graphics

Publisher: Springer International Publishing

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Abstract

One of the main tasks in image restoration is to catch the picture characteristics such as interfaces and textures from incomplete noisy frequency data. For the cost functional with data matching term in frequency domain and the total variation together with Frobenius norm penalty terms in spatial domain, the properties of the minimizer of cost functional and the error estimates on the regularizing solution are established. Then we propose an algorithm with double recursion to restore piecewise smooth image. The Bregman iteration with lagged diffusivity fixed point method is used to solve the corresponding nonlinear Euler-Lagrange equation. By implementing recursion algorithms a few times, the satisfactory reconstructions can be obtained using random band sampling data. Numerical implementations demonstrate the validity of our proposed algorithm with good edge-preservations.

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next chapter RGB-D Saliency Detection with Multi-feature-fused Optimization
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Metadata
Title
A Double Recursion Algorithm to Image Restoration from Random Limited Frequency Data
Authors
Xiaoman Liu
Jijun Liu
Copyright Year
2017
Book
Image and Graphics

Print ISBN: 978-3-319-71597-1

Electronic ISBN: 978-3-319-71598-8

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-71598-8_1

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