Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Finding the Parameters of a Nonlinear Diffusion Denoising Method by Ridge Analysis

Finding the Parameters of a Nonlinear Diffusion Denoising Method by Ridge Analysis Noise-suppression (denoising) methods depend on the parameters that regulate filtering intensity. The noise-free image is inaccessible in practice, and we have to choose optimal parameters that use only the original noisy image and a filtered image. Image quality can be measured in the presence of ridge structures (ridges and valleys) by analyzing difference frames. A method for filtering quality assessment is proposed: it evaluates the mutual information between the values of the difference frame points where ridge structures are present. Ridge structures are detected by analyzing the Hessian, which produces the directions and the characteristic width of the ridges and the valleys. The method has been tested for the Perona–Malik nonlinear diffusion on noisy images from the BSDS500 database. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computational Mathematics and Modeling Springer Journals

Finding the Parameters of a Nonlinear Diffusion Denoising Method by Ridge Analysis

Download PDF
10 pages

Loading next page...
 
/lp/springer_journal/finding-the-parameters-of-a-nonlinear-diffusion-denoising-method-by-Ll53t0Vh2H
Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Mathematics; Mathematical Modeling and Industrial Mathematics; Computational Mathematics and Numerical Analysis; Applications of Mathematics; Optimization
ISSN
1046-283X
eISSN
1573-837X
DOI
10.1007/s10598-018-9413-6
Publisher site
See Article on Publisher Site

Abstract

Noise-suppression (denoising) methods depend on the parameters that regulate filtering intensity. The noise-free image is inaccessible in practice, and we have to choose optimal parameters that use only the original noisy image and a filtered image. Image quality can be measured in the presence of ridge structures (ridges and valleys) by analyzing difference frames. A method for filtering quality assessment is proposed: it evaluates the mutual information between the values of the difference frame points where ridge structures are present. Ridge structures are detected by analyzing the Hessian, which produces the directions and the characteristic width of the ridges and the valleys. The method has been tested for the Perona–Malik nonlinear diffusion on noisy images from the BSDS500 database.

Journal

Computational Mathematics and Modeling – Springer Journals

Published: May 31, 2018

References

  • Rank algorithms for picture processing
    Yaroslavsky, LP; Kim, V
  • A review of image denoising algorithms, with a new one
    Buades, A; Coll, B; Morel, J
  • No-reference image quality assessment in the spatial domain
    Mitta, A; Moorthy, AK; Bovik, AC
  • Blind image quality assessment: from scene statistics to perceptual quality
    Moorthy, AK; Bovik, AC
  • Blind image quality assessment: a natural scene statistics approach in the DCT domain
    Saad, MA; Bovik, AC
  • Ridges in Image and Data Analysis
    Eberly, D