Noise removal using smoothed normals and surface fitting

IEEE Trans Image Process. 2004 Oct;13(10):1345-57. doi: 10.1109/tip.2004.834662.

Abstract

In this work, we use partial differential equation techniques to remove noise from digital images. The removal is done in two steps. We first use a total-variation filter to smooth the normal vectors of the level curves of a noise image. After this, we try to find a surface to fit the smoothed normal vectors. For each of these two stages, the problem is reduced to a nonlinear partial differential equation. Finite difference schemes are used to solve these equations. A broad range of numerical examples are given in the paper.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Validation Study

MeSH terms

  • Algorithms*
  • Cluster Analysis
  • Computer Simulation
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods
  • Information Storage and Retrieval / methods*
  • Models, Statistical
  • Numerical Analysis, Computer-Assisted*
  • Pattern Recognition, Automated*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted
  • Stochastic Processes
  • Subtraction Technique*