标题:
基于ROF模型的修正半光滑牛顿法The Modified Semismooth Newton Algorithm Based on the ROF Model
作者:
庞志峰, 吕军成
关键字:
图像去噪, 全变差, 半光滑牛顿法: Image Denoising; Total Variation; Semismooth Newton Algorithm
期刊名称:
《Pure Mathematics》, Vol.1 No.1, 2011-04-15
摘要:
本文基于ROF去噪模型的对偶算法提出一个修正的半光滑牛顿法。文中证明了该算法具有Q超线性收敛,同时指出选取适当的参数α可以提高数值计算效率。实验表明,建议的修正算法既能较好的复原图像,又具有较快的收敛速度。
In this paper, based on the dual algorithm of ROF model, we propose a modified semismooth Newton algorithm. Furthermore, we prove that the proposed algorithm converges Q-superlinearly, and also refer that this algorithm can improve the computational efficiency by choosing a suitable parameter α. The simulations show that the new modified algorithm can perfectly restore image and keep the faster conver-gence rate.