Earticle

초록

영어

In the past decades, many nonlinear partial differential equation (PDE) based denosing methods have been suggested, among which the curvature-preserving PDE image denosing method is one of the outstanding models. To effectively preserve image edge well, a tensor driven linear integral convolutions based Image Denosing Method is proposed, which employ total variation flow based nonlinear structure tensor to analysis different integral curve. It is a new implementation of our former work [10]. Experimental results show that the new method can achieve better denosing results in a variety of standard test images, and the new approach shows superior performance on edge and curvature preserving face image and texture image.

목차

Abstract
 1. Introduction
 2. Tensor Driven Linear Integral Convolutions Denosing methods
 3. Results and Discussion
 4. Conclusions
 Acknowledgements
 References

키워드

저자

• Shenghua Gu [ Division of Science & technology, Nanjing University of Information Science & Technology ]
• Lu Liu [ College of Computer & Software, Nanjing University of Information Science & Technology ]
• Yuhui Zheng [ College of Computer & Software, Nanjing University of Information Science & Technology ]
• Shunfeng Wang [ College of Bin Jiang, Nanjing University of Information Science & Technology ]

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