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Stochastic and analytic modeling of atmospheric turbulence in image processing

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00326211" target="_blank" >RIV/68407700:21230/18:00326211 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21340/18:00326211

  • Result on the web

    <a href="https://doi.org/10.1117/12.2321199" target="_blank" >https://doi.org/10.1117/12.2321199</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1117/12.2321199" target="_blank" >10.1117/12.2321199</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Stochastic and analytic modeling of atmospheric turbulence in image processing

  • Original language description

    Modeling of atmospheric turbulence through Kolmogorov theorem belongs to traditional applications of 2D Fourier Transform (2D FT). It is based on Point Spread Function (PSF) in the spatial domain and its frequency domain image known as Optical Transfer Function (OTF). The latter is available in the explicit form. It enables to create an artificial fog effect in traditional image processing using 2D Discrete Fourier Transform (2D DFT). Exact knowledge of the Optical Transfer Function allows performing the image deblurring as deconvolution through Wiener method. The difference between the reference image and the deconvolution outcome can be quantified using SNR in traditional and rank modification. However, the real star image is a result of a stochastic process which is driven by 2D alpha-stable distribution. There is an efficient method how to generate a pseudorandom sample from the alpha-stable distribution. The distribution then enables to simulate the photon distribution following the theoretical PSF, i.e. convergence according to distribution is guaranteed. The comparison of both models and optimal parameter setting of Wiener deconvolution are studied for various exposure times and CCD camera noise levels. Obtained results can be generalized and applied to turbulent noise suppression.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

    <a href="/en/project/GA17-05840S" target="_blank" >GA17-05840S: Multicriteria Optimization of Shift-Variant Imaging System Models</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings Volume 10752 - Applications of Digital Image Processing XLI

  • ISBN

    9781510620759

  • ISSN

    0277-786X

  • e-ISSN

    1996-756X

  • Number of pages

    9

  • Pages from-to

  • Publisher name

    SPIE

  • Place of publication

    Bellingham

  • Event location

    San Diego

  • Event date

    Aug 19, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000450861700088