DocumentCode
1525701
Title
Statistical modelling of ocean SAR images
Author
Delignon, Y. ; Garello, R. ; Hillion, A.
Author_Institution
ENIC, Villeuve d´´Ascq, France
Volume
144
Issue
6
fYear
1997
fDate
12/1/1997 12:00:00 AM
Firstpage
348
Lastpage
354
Abstract
The paper considers the statistical modelling of fully developed backscattering in the case of SAR images of the ocean surface. According to the random-walk theory, the SAR image grey level is modelled as the product of a speckle noise and a variable which is dependent on the reflectivity of the illuminated surface and the radar-point-spread function. The purpose of the study is the statistical modelling of the latter variable. As nothing is known about these statistics, the authors propose the use of an estimation method based on a system of distributions. The set contains known density-probability functions with very flexible shapes that are supposed to fit its distribution. The associated image intensity distributions are processed and form a new system called KUBW, referring to the special functions used to generate the distributions. The classical K law belongs to the new system of distributions. By using a statistical test on the intensity distribution, the authors assess the relevance of the system of distributions in comparison with the classical model. The paper concludes with a discussion of the merits of the method and its extension to the case of ocean SAR image applications
Keywords
backscatter; electromagnetic wave reflection; image texture; noise; oceanographic techniques; optical transfer function; radar imaging; random processes; remote sensing by radar; speckle; statistical analysis; synthetic aperture radar; K law; KUBW; backscattering; classical model; density-probability functions; estimation method; grey level; illuminated surface reflectivity; image intensity distributions; ocean SAR images; ocean surface; radar point spread function; random-walk theory; scene texture; speckle noise; statistical modelling; statistical test; system of distributions;
fLanguage
English
Journal_Title
Radar, Sonar and Navigation, IEE Proceedings -
Publisher
iet
ISSN
1350-2395
Type
jour
DOI
10.1049/ip-rsn:19971497
Filename
646937
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