Atmospheric Turbulence Degraded-Image Restoration by Kurtosis Minimization

Atmospheric Turbulence Degraded-Image Restoration by Kurtosis Minimization

Atmospheric turbulence is caused by the random fluctuations of the refraction index of the medium. It can lead to blurring in images acquired from a long distance away. Since the degradation is often not completely known, the problem is viewed as blind image deconvolution or blur identification. Our...

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Veröffentlicht in:IEEE geoscience and remote sensing letters 2009-04, Vol.6 (2), p.244-247
Hauptverfasser: Dalong Li, Simske, S.
Format: Artikel
Sprache:eng
Schlagworte:
Atmospheric modeling
Atmospheric turbulence
Autoregressive processes
blur identification
Blurring
Deconvolution
Degradation
Fluctuations
Image restoration
Kurtosis
Minimization
Minimization methods
Optical imaging
Optical refraction
Optimization
Random processes
Refraction
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Zusammenfassung:Atmospheric turbulence is caused by the random fluctuations of the refraction index of the medium. It can lead to blurring in images acquired from a long distance away. Since the degradation is often not completely known, the problem is viewed as blind image deconvolution or blur identification. Our previous work has observed that blurring increases kurtosis and introduced a new blur identification method based on kurtosis minimization (KM). In this letter, this observation has been studied using phase correlation. The KM method is compared with two other signal processing methods. The limitation of the method is also discussed.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2008.2011569