Earticle

초록

영어

It is assumed in the traditional total variation(neighbor domain, ND) algorithm that the pixel points are located at the edge and an edge-preserving model is set up. In the algorithm, pixels in flat regions of the image diffuse along the edge direction, leading to insufficient noise suppression and even presence of false edges. To carry on the edge-saving feature of neighbor domain algorithm and to make up its deficiency in omitting the image edge direction, this paper introduces direction neighborhood to the total variation algorithm so that edge points diffuse along the direction neighborhood. It changes the mode where edge points in the traditional ND algorithm diffuse along the multi-neighborhood, maximizing the smoothness along the edge direction and minimizing that at the vertical edge direction. The experimental results show that the image denoising method based on vector neighbor domain effectively addresses the drawbacks existing in the traditional ND algorithm and provides faster convergence efficiency, achieving both denoising and edge-preserving and improving PSNR and visual effects of the image.

목차

Abstract
 1. Introduction
 2. Extraction of Direction Neighborhood
 3. Total Variation Denoising of Direction Neighborhood
 4. Analysis of Experimental Results
 5. Conclusion
 References

키워드

저자

• Liu Hongping [ Educational Technology Center, Changsha Normal University, Changsha, 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