Variational Image Restoration and Decomposition with Curvelet Shrinkage

@article{Jiang2007VariationalIR,
  title={Variational Image Restoration and Decomposition with Curvelet Shrinkage},
  author={Lingling Jiang and Xiangchu Feng and Haiqing Yin},
  journal={Journal of Mathematical Imaging and Vision},
  year={2007},
  volume={30},
  pages={125-132}
}
The curvelet is more suitable for image processing than the wavelet and able to represent smooth and edge parts of image with sparsity. Based on this, we present a new model for image restoration and decomposition via curvelet shrinkage. The new model can be seen as a modification of Daubechies-Teschke’s model. By replacing the B p,q β term by a G p,q β term, and writing the problem in a curvelet framework, we obtain elegant curvelet shrinkage schemes. Furthermore, the model allows us to… CONTINUE READING
Highly Cited
This paper has 28 citations. REVIEW CITATIONS
10 Citations
12 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 12 references

Frame decomposition of decomposition spaces

  • L. Borup, M. Nielsen
  • J. Fourier Anal. Appl. 13(1), 39–70
  • 2007
Highly Influential
4 Excerpts

Oscillating Patterns in Image Processing and Nonlinear Evolution Equations

  • Y. Meyer
  • University Lecture Series, vol. 22. American…
  • 2001
Highly Influential
3 Excerpts

An iterative thresholding algorithm for linear inverse problems with a sparsity constraint

  • I. Daubechies, M. Defrise, C. DeMol
  • Commun. Pure Appl. Math. 57, 1413–1541
  • 2004
1 Excerpt

Similar Papers

Loading similar papers…