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RWRM: Residual Wasserstein regularization model for image restoration

Ruiqiang He, School of Mathematics and Statistics, Xidian University, Xi'an 710126, China, Xiangchu Feng, Xiaolong Zhu, Hua Huang, Bingzhe Wei, Department of Mathematics, Xinzhou Teachers University, Xinzhou 034000, China
<span title="">2020</span> <i title="American Institute of Mathematical Sciences (AIMS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/axidtgwpanf6rabcadvwl4axum" style="color: black;">Inverse Problems and Imaging</a> </i> &nbsp;
In this paper, we propose a residual Wasserstein regularization model (RWRM), in which a residual histogram constraint is subtly embedded into a type of variational minimization problems.  ...  Furthermore, the RWRM unifies the residual Wasserstein regularization and image prior regularization to improve image restoration performance.  ...  The authors would like to thank the anonymous reviewers for their valuable comments. This paper is supported by the National Natural Science  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3934/ipi.2020069">doi:10.3934/ipi.2020069</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gekg3ho5qzgrzdr72avio4e3vm">fatcat:gekg3ho5qzgrzdr72avio4e3vm</a> </span>
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