Earticle

초록

영어

Rician noise pollutes Magnetic Resonance Imaging (MRI) image and makes later work worse. In allusion to remove noise while lessen the loss of details as low as possible, this paper proposed an filter algorithm which comprehensive utilize Genetic Algorithm (GA), PDE and TV, based on 4th order Partial Differential Equations (PDE) and Total Variation (TV) theory. First, it calculates the Total Variation(TV) and the 4th order PDE of kth image, and gives them weight coefficients. Then, it finds the optimal Standard deviation of image of kth image by adjusting weight coefficients based on GA algorithm. Third, it compares PSNR of kth image and PSNR of k+1th image to find whether the algorithm is over. Experimental results show that our new algorithm presented in this paper is more effective in removing Rician noise and giving better Peak Signal Noise Ratio (PSNR) gains without manual intervention in comparison with other traditional filters.

목차

Abstract
 1. Introduction
 2. Related Works
  2.1. Rician Noise
  2.2. Total Variation Minimization (TVM)
  2.3. Fourth-order PDEs
 3. Proposed Model
  3.1. Target Function
  3.2. Workflow
 4. Experimental Results and Analysis
  4.1. Evaluation Index
  4.2. Experimental Results
 5. Conclusions
 Acknowledgments
 References

키워드

저자

• Zhiyong Fan [ Nanjing University of Science & Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China ]
• Quansen Sun [ Nanjing University of Science & Technology, Nanjing 210000, China ]
• Zexuan Ji [ Nanjing University of Science & Technology, Nanjing 210000, China ]
• Feng Ruan [ Nanjing University of Information Science & Technology, Nanjing 210044, China ]
• Liling Zhao [ Nanjing University of Science & Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605