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
Circuits, Systems and Signal Processing – Springer Journals
Published: May 30, 2018
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