Stochastic and analytic modeling of atmospheric turbulence in image processing

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F18%3A43915671" target="_blank" >RIV/60461373:22340/18:43915671 - isvavai.cz</a>

Result on the web

<a href="https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10752/107522N/Stochastic-and-analytic-modeling-of-atmospheric-turbulence-in-image-processing/10.1117/12.2321199.short?SSO=1" target="_blank" >https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10752/107522N/Stochastic-and-analytic-modeling-of-atmospheric-turbulence-in-image-processing/10.1117/12.2321199.short?SSO=1</a>

DOI - Digital Object Identifier

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

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

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

20201 - Electrical and electronic engineering

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)

Publication year

2018

Confidentiality

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

Article name in the collection

Proceedings of SPIE Volume 10752 Applications of Digital Image Processing XLI

ISBN

978-1-5106-2076-6

ISSN

0277-786X

e-ISSN

1996-756X

Number of pages

9

Pages from-to

"107522N-1"-"107522N-9"

Publisher name

SPIE Society of Photo-Optical Instrumentation Engineers

Place of publication

Washington

Event location

San Diego

Event date

Aug 20, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000450861700088