Earticle

초록

영어

Developing a variational model that is capable of restoring both smooth (no edges) and non-smooth (with edges) images is still a valid challenge at the image processing. In this paper, we present two methods for image denoising problems based on the use of the LLT model (see [14]) and TV model (see [20]). The idea of our methods is, add the texture which is separated from the cartoon and noisy, back to the original noisy image or the texture plus noisy part, and the sum then processed. In order to obtain the texture, we first separate texture plus noise from cartoon by LLT model, and then use TV model to remove some noisy from texture. Numerical experiments show our method is able to maintain some important information such as small details in the image, and at the same time to get a better visualization.

목차

Abstract
 1. Introduction
 2. Iterated regularization method
 3. Iterated regularization methods based on LLT model and TV model
  3.1. Algorithm 1
  3.2. Algorithm 2
 4. Numerical experiments and discussions
  4.1. Comparisons of our algorithms with the TV model and the LLT model
  4.2. Comparison of Algorithm 1 with the Mean Curvature Model
  4.3. Comparison of Algorithm 1 with the convex combination method
  4.4. Comparisons of Algorithm 1 with some other methods
 5. Conclusions
 References

키워드

저자

• Fengqi Zhou [ School of Basic Science, East China Jiaotong University, Nanchang, 330013, China ]
• Yu Xiao [ School of Basic Science, East China Jiaotong University, Nanchang, 330013, China ]
• Zhigang Yan [ Accounting School, Jiangxi University of Finance and Economics, Nanchang, 330013, China ]
• Fenlin Yang [ College of Mathematics and Statistics, Jishou University, Jishou, 416000, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605