کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4944412 | 1437993 | 2017 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An adaptive fixed-point proximity algorithm for solving total variation denoising models
ترجمه فارسی عنوان
الگوریتم تقریبی همجوشی ثابت برای حل مدل های تناوب کل
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
We study an adaptive fixed-point proximity algorithm to solve the total variation denoising model. The objective function is a sum of two convex functions and one of them is composed by an affine transformation, which is usually a regularization term. By decoupling and splitting, the problem is changed into two subproblems. Due to the nonsmooth and nondifferentiability of the subproblem, we solve its proximity minimization problem instead of the original one. To overcome the “staircase” effect during the process of denoising, an adaptive criterion on proximity parameters is put forward. At last we apply the improved algorithm to solve the isotropic total variation denoising model. The numerical results are given to illustrate the efficiency of the algorithm.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 402, September 2017, Pages 69-81
Journal: Information Sciences - Volume 402, September 2017, Pages 69-81
نویسندگان
Jin-He Wang, Fan-Yun Meng, Li-Ping Pang, Xing-Hua Hao,