Iterative solvers for image denoising with diffusion models: A comparative study

被引：10
|
作者：
Jain, Subit K. [1 ]
Ray, Rajendra K. [1 ]
Bhavsar, Arnav [2 ]
机构：
[1] Indian Inst Technol Mandi, Sch Basic Sci, Pin 175001, India
[2] Indian Inst Technol Mandi, Sch Comp & Elect Engn, Pin 175001, India
来源：
COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2015年 / 70卷 / 03期
关键词：
Perona-Malik; Bilateral filter; Crank-Nicolson scheme; Successive-over-relaxation; Hybrid bi-conjugate gradient stabilized method; Denoising; OPTIMAL STOPPING TIME; EDGE;
D O I：
10.1016/j.camwa.2015.04.009
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper we propose and compare the use of two iterative solvers using the Crank-Nicolson finite difference method, to address the task of image denoising via partial differential equations (PDEs) models such as Regularized Perona-Malik equation or C-model and Bazan model (Bilateral-filter-based model). The solvers which are considered in this paper are the Successive-over-Relaxation (SOR) and an advanced solver known as Hybrid Bi-Conjugate Gradient Stabilized (Hybrid BiCGStab) method. From numerical experiments, it is found that the Crank-Nicolson method with hybrid BiCGStab iterative solver produces better results and is more efficient than SOR and already existing, in terms of MSSIM and PSNR. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：191 / 211
页数：21
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