Edge-preserving denoising method using variation approach and gradient distribution

@article{Cho2014EdgepreservingDM,
  title={Edge-preserving denoising method using variation approach and gradient distribution},
  author={Wanhyun Cho and SeongChae Seo and Jinho You},
  journal={2014 International Conference on Big Data and Smart Computing (BIGCOMP)},
  year={2014},
  pages={139-144}
}
This paper proposed an image denoising technique that can enhance the quality of image by using a variational approach and image gradient distribution. First, in order to remove the noise, we consider the variational approach for the energy functional that satisfies an edge-preserving regularization property. Here, we propose a new variational functional that can be implemented by adding a new gradient distribution term in a given energy functional that locally controls the extent of denoising… CONTINUE READING

Citations

Publications citing this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 14 REFERENCES

Texture Enhanced Image Denoising via Gradient Histogram Preservation

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition
  • 2013
VIEW 1 EXCERPT

Image Restoration by Matching Gradient Distributions

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2011
VIEW 1 EXCERPT

A comprehensive review of image enhancement techniques

R. Maini, H. H. Aggarwel
  • Journal of Computing,
  • 2010

A review of image denoising algorithms with a new one ” , Multiscale Model

B. Coll A. Buades, J. M. Morel
  • Edge - Preserving Noise Removal , Part 1 : Second - Order Anistorpic Diffusion
  • 2005

An Algorithm for Total Variation Minimization and Applications

  • Journal of Mathematical Imaging and Vision
  • 2004
VIEW 1 EXCERPT

Similar Papers

Loading similar papers…