Earticle

초록

영어

Because the traditional partial differential exist image blur, information read errors and large error defects, this thesis proposes the image registration of differential equations. This theory is based on differential equations to classify different classification, to build the model for different types for differential equations based on the application of image registration, and finally to take simulation experiments for different application of differential equations according to different images. Simulation results show that: the model of partial differential equations in this paper is easier to extract and recognize image information extraction, so it is good for reading, but also more clearly and accurately to achieve an effective registration.

목차

Abstract
 1. Introduction
 2. Partial Differential Equations
  2.1 Theory of Partial Differential Equations
  2.2 Heat Partial Differential Equation
  2.3 Partial Differential Wave Equation
  2.4 Partial Differential Value Calculation
 3. PDE-based Self-adaption Anisotropy Registration Model
  3.1. Image Registration Model of Partial Differential
  3.2. Self-adaption Anisotropy Regular Term
  3.3. Contour Model of Partial Differential
  3.4. Self-adaption Anisotropic Registration and Solution Based on Partial Differential Equations
 4. Experimental Simulation and Analysis
  4.1 Registration Evaluation
  4.2 Optical Flow Experimental of Rubik Chart
  4.3 Brain MR Image Registration
  4.4 Different Pictures of multi-modal human Brain
  4.5 Registration of Human Face Images
 5. Conclusion
 References

키워드

저자

• Li Peize [ Department of Mathematics, Tianjin Polytechnic University, Tianjin, 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