On the comparison of different kernel functionals and neighborhood geometry for nonlocal means filtering View Full Text


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Article Info

DATE

2018-01

AUTHORS

José I. de la Rosa, Jesús Villa-Hernández, Joaquín Cortez, Hamurabi Gamboa, José G. Arceo, Efrén González

ABSTRACT

The present work proposes a review and comparison of different Kernel functionals and neighborhood geometry for Nonlocal Means (NLM) in the task of digital image filtering. Some different alternatives to change the classical exponential kernel function used in NLM methods are explored. Moreover, some approaches that change the geometry of the neighborhood and use dimensionality reduction of the neighborhood or patches onto principal component analysis (PCA) are also analyzed, and their performance is compared with respect to the classic NLM method. Mainly, six approaches were compared using quantitative and qualitative evaluations, to do this an homogeneous framework has been established using the same simulation platform, the same computer, and same conditions for the initializing parameters. According to the obtained comparison, one can say that the NLM filtering could be improved when changing the kernel, particularly for the case of the Tukey kernel. On the other hand, the excellent performance given by recent hybrid approaches such as NLM SAP, NLM PCA (PH), and the BM3D SAPCA lead to establish that significantly improvements to the classic NLM could be obtained. Particularly, the BM3D SAPCA approach gives the best denoising results, however, the computation times were the longest. More... »

PAGES

1205-1235

References to SciGraph publications

  • 2012-06. Non-local Methods with Shape-Adaptive Patches (NLM-SAP) in JOURNAL OF MATHEMATICAL IMAGING AND VISION
  • 1997-12. Universal smoothing factor selection in density estimation: theory and practice in TEST
  • 2013-12. An adaptive bandwidth nonlocal means image denoising in wavelet domain in EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING
  • 2008-03. A Robust and Fast Non-Local Means Algorithm for Image Denoising in JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
  • 2008-02. Nonlocal Image and Movie Denoising in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11042-016-4322-1

    DOI

    http://dx.doi.org/10.1007/s11042-016-4322-1

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    42 schema:description The present work proposes a review and comparison of different Kernel functionals and neighborhood geometry for Nonlocal Means (NLM) in the task of digital image filtering. Some different alternatives to change the classical exponential kernel function used in NLM methods are explored. Moreover, some approaches that change the geometry of the neighborhood and use dimensionality reduction of the neighborhood or patches onto principal component analysis (PCA) are also analyzed, and their performance is compared with respect to the classic NLM method. Mainly, six approaches were compared using quantitative and qualitative evaluations, to do this an homogeneous framework has been established using the same simulation platform, the same computer, and same conditions for the initializing parameters. According to the obtained comparison, one can say that the NLM filtering could be improved when changing the kernel, particularly for the case of the Tukey kernel. On the other hand, the excellent performance given by recent hybrid approaches such as NLM SAP, NLM PCA (PH), and the BM3D SAPCA lead to establish that significantly improvements to the classic NLM could be obtained. Particularly, the BM3D SAPCA approach gives the best denoising results, however, the computation times were the longest.
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