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New Class of Topological Textural Multifractal Descriptors and Their Application for Processing Low-Contrast Radar and Optical Images

  • THEORY AND METHODS OF SIGNAL PROCESSING
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Abstract

The issues of joint estimation of the scaling, singular, multifractal, and anisotropic properties of image texture are considered. A technique for forming a fundamentally new class of topological textural-multifractal descriptors for joint estimation of various fractal properties of a texture is described. The efficiency of segmentation of real radar and optical images by the Fuzzy c-means clustering algorithms in the space of the proposed class of descriptors is estimated. Based on the results and their comparison with the accuracy of segmentation by the existing descriptor, the conclusion about the higher informativity of the new class of topological fractal descriptors is made.

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Authors and Affiliations

  1. Kotelnikov Institute of Radio Engineering and Electronics, Russian Academy of Sciences, 125009, Moscow, Russia

    A. A. Potapov

  2. Russian Air Force Military Educational and Scientific Center Zhukovsky and Gagarin Air Force Academy, 394064, Voronezh, Russia

    V. A. Kuznetsov & A. N. Pototskii

Authors
  1. A. A. Potapov
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  2. V. A. Kuznetsov
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  3. A. N. Pototskii
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Correspondence to A. A. Potapov, V. A. Kuznetsov or A. N. Pototskii.

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Translated by E. Bondareva

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Potapov, A.A., Kuznetsov, V.A. & Pototskii, A.N. New Class of Topological Textural Multifractal Descriptors and Their Application for Processing Low-Contrast Radar and Optical Images. J. Commun. Technol. Electron. 66, 581–590 (2021). https://doi.org/10.1134/S1064226921050090

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  • DOI: https://doi.org/10.1134/S1064226921050090

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