학술논문

A weighted split Bregman iteration for adaptive fractional order total variation model
Document Type
Conference
Source
2019 Chinese Control And Decision Conference (CCDC) Control And Decision Conference (CCDC), 2019 Chinese. :2036-2041 Jun, 2019
Subject
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Fractional calculus
Image denoising
Signal processing algorithms
Computational modeling
Adaptation models
Split Bregman iteration
AFOTV
Language
ISSN
1948-9447
Abstract
Image denoising is an important branch in the process of image processing which has been widely used in various fields. This paper proposes a weighted split Bregman iteration (WSBI) algorithm for adaptive fractional order total variation model, which provides an effective method to deal with the image denoising problem. A weight coefficient w is added to the split Bregman iteration (SBI) algorithm. Compared with the ordinary SBI algorithm, this improved algorithm can achieve faster convergence and higher (PSNR) of the image by experiments. This algorithm also can well preserve the texture details of the image and avoid the staircase artifact.