An Effective Weighted Hybrid Regularizing Approach for Image Noise Reduction

An Effective Weighted Hybrid Regularizing Approach for Image Noise Reduction Circuits Syst Signal Process https://doi.org/10.1007/s00034-018-0853-1 An Effective Weighted Hybrid Regularizing Approach for Image Noise Reduction 1 2 Md. Robiul Islam · Chen Xu · 1 2 Rana Aamir Raza · Yu Han Received: 27 August 2017 / Revised: 15 May 2018 / Accepted: 17 May 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Digital images are mostly noised due to transmission and capturing distur- bances. Hence, denoising becomes a notable issue because of the necessity of removing noise before its use in any application. In denoising, the important challenge is to remove the noise while protecting true information and avoiding undesirable mod- ification in the images. The performance of classical denoising methods including convex total variation or some nonconvex regularizers is not effective enough. Thus, it is still an ongoing research toward better denoising result. Since edge preservation is a tricky issue during denoising process, designing an appropriate regularizer for a given fidelity is a mostly crucial matter in real-world problems. Therefore, we attempt to design a robust smoothing term in energy functional so that it can reduce the possibil- ity of discontinuity and distortion of image edge details. In this work, we introduce a http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Circuits, Systems and Signal Processing Springer Journals

An Effective Weighted Hybrid Regularizing Approach for Image Noise Reduction

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Circuits and Systems; Electrical Engineering; Signal,Image and Speech Processing; Electronics and Microelectronics, Instrumentation
ISSN
0278-081X
eISSN
1531-5878
D.O.I.
10.1007/s00034-018-0853-1
Publisher site
See Article on Publisher Site

Abstract

Circuits Syst Signal Process https://doi.org/10.1007/s00034-018-0853-1 An Effective Weighted Hybrid Regularizing Approach for Image Noise Reduction 1 2 Md. Robiul Islam · Chen Xu · 1 2 Rana Aamir Raza · Yu Han Received: 27 August 2017 / Revised: 15 May 2018 / Accepted: 17 May 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Digital images are mostly noised due to transmission and capturing distur- bances. Hence, denoising becomes a notable issue because of the necessity of removing noise before its use in any application. In denoising, the important challenge is to remove the noise while protecting true information and avoiding undesirable mod- ification in the images. The performance of classical denoising methods including convex total variation or some nonconvex regularizers is not effective enough. Thus, it is still an ongoing research toward better denoising result. Since edge preservation is a tricky issue during denoising process, designing an appropriate regularizer for a given fidelity is a mostly crucial matter in real-world problems. Therefore, we attempt to design a robust smoothing term in energy functional so that it can reduce the possibil- ity of discontinuity and distortion of image edge details. In this work, we introduce a

Journal

Circuits, Systems and Signal ProcessingSpringer Journals

Published: May 30, 2018

References

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