@inproceedings{22283e7098ea4880b190351fade30ee6,
title = "On the Convex Model of Speckle Reduction",
abstract = "Speckle reduction is an important issue in image processing realm. In this paper, we propose a novel model for restoring degraded images with multiplicative noise which follows a Nakagami distribution. A general penalty term based on the statistical property of the speckle noise is used to guarantee the convexity of the denoising model. Moreover, to deal with the minimizing problem, a generalized Bermudez-Moreno algorithm is adopted and its convergence is analysed. The experimental results on some images subject to multiplicative noise as well as comparisons to other state-of-the-art methods are also presented. The results can verify that the new model is reasonable.",
author = "Faming Fang and Yingying Fang and Tieyong Zeng",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2018.; International conference on Imaging, Vision and Learning Based on Optimization and PDEs, IVLOPDE 2016 ; Conference date: 29-08-2016 Through 02-09-2016",
year = "2018",
doi = "10.1007/978-3-319-91274-5\_6",
language = "英语",
isbn = "9783319912738",
series = "Mathematics and Visualization",
publisher = "Springer Heidelberg",
pages = "121--141",
editor = "Xue-Cheng Tai and Egil Bae and Marius Lysaker",
booktitle = "Mathematics and Visualization",
address = "德国",
}