Signal, Image and Video Processing

, Volume 10, Issue 8, pp 1543–1550 | Cite as

Efficiency of texture image filtering and its prediction

  • Oleksii Rubel
  • Vladimir Lukin
  • Sergey Abramov
  • Benoit Vozel
  • Karen Egiazarian
  • Oleksiy Pogrebnyak
Original Paper


Textures are typical elements of natural scene images widely used in pattern recognition and image classification. Noise, often being present in acquired images, deteriorates texture features (characteristics), and it is desirable both to suppress it and to preserve a texture. This task is quite difficult even for the most advanced filters, and the resulting denoising efficiency can be quite low. Due to this, it is desirable to predict a denoising efficiency before filtering to decide whether it is worth filtering a given image or not. In this paper, we analyze several quantitative criteria (metrics) that can characterize filtering efficiency. Prediction strategy is described and its accuracy is studied. Several modern filtering techniques are analyzed and compared. Based on this, practical recommendations are given.


Filtering efficiency Noise suppression Image enhancement Visual quality 



This work was partially supported by Instituto Politecnico Nacional as a part of research Project 20161173.


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Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  • Oleksii Rubel
    • 1
  • Vladimir Lukin
    • 1
  • Sergey Abramov
    • 1
  • Benoit Vozel
    • 2
  • Karen Egiazarian
    • 3
  • Oleksiy Pogrebnyak
    • 4
  1. 1.Department of Receivers, Transmitters and Signal ProcessingNational Aerospace UniversityKharkovUkraine
  2. 2.IETR UMR CNRS 6164University of Rennes 1Enssat LannionFrance
  3. 3.Department of Signal ProcessingTampere University of TechnologyTampereFinland
  4. 4.Instituto Politecnico NacionalMexicoMexico

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