Earticle

초록

영어

In this paper we present an adaptive multilevel total variational (TV) method for image denoising which utilizes TV partial differential equation (PDE) models and exploits the multiresolution properties of wavelets. The adaptive multilevel TV method provides fast adaptive wavelet-based solvers for the TV model. Our approach employs a wavelet collocation method applied to the TV model using two-dimensional anisotropic tensor product of Daubechies wavelets. The algorithm inherently combines the denoising property of wavelet compression algorithms with that of the TV model, and produces results superior to each method when implemented alone. It exploits the edge preservation property of the TV model to reduce the oscillations that may be generated around the edges in wavelet compression. In contrast with previous work combining TV denoising with wavelet compression, the method presented in this paper treats the numerical solution in a novel way which decreases the computational cost associated with the solution of the TV model. We present a detailed description of our method and results which indicate that a combination of wavelet based denoising techniques with the TV model produces superior results, for a fraction of the computational cost.

목차

Abstract
 1. Introduction
 2. The TV Model
 3. Wavelet Multilevel Methods
  3.1. Daubechies-based Wavelet Approximation
  3.2. Wavelets in Two Spatial Dimensions
  3.3. The Adaptive Multilevel TV Method
 4. Numerical Experiments
 5. Conclusion
 References

키워드

저자

• Kossi Edoh [ Department of Mathematics NC A&T State University Greensboro, NC, USA ]
• John Paul Roop [ Department of Mathematics NC A&T State University Greensboro, NC, USA ]

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