DocumentCode :
2318802
Title :
Fast evaluation for speckle feature in urban SAR images
Author :
Xiaojun, Wang ; Cangzeng, Meng ; Shusheng, Yan ; Helei, Wang ; Yang, Liu
Author_Institution :
Land-Based Warning & Surveillance Equipments, Dep. Air Force Radar Acad., Wuhan, China
fYear :
2009
fDate :
20-22 May 2009
Firstpage :
1
Lastpage :
5
Abstract :
Coherent speckle is an important feature in Synthetic Aperture Radar (SAR) image. Testing the property of speckle is effective for urban SAR image performance evaluation. Through correlation analysis for speckle measures, this paper proposes a measurement for speckle feature based on parametric hypothesis test. Firstly selects homogeneous areas in tested SAR image with manual mode and estimates the ENL of each area. In contrast with the speckle feature in sampled image from population, secondly utilizes the u-parametric hypothesis test to measure the quality of speckle. Finally obtains the result that accepts the null hypothesis or rejects it. Experiments of Japan Pi-SAR and East China Research Institute of Electronic Engineering (ECRIEE) SAR images in urban areas show the measurement could distinguish those tested images where speckle property is in accordance with the coherent imaging principle, which is one of the vital requirements for post processing technology of SAR imagery.
Keywords :
image processing; remote sensing by radar; speckle; synthetic aperture radar; ECRIEE; East China Research Institute of Electronic Engineering; Japan; M-parametric hypothesis test; Pi-SAR experiments; SAR image performance evaluation; Synthetic Aperture Radar; coherent imaging principle; correlation analysis; manual mode; null hypothesis; post processing technology; speckle feature evaluation; urban SAR images; Fading; Filters; Radar imaging; Radar measurements; Radar remote sensing; Radar scattering; Spaceborne radar; Speckle; Synthetic aperture radar; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Urban Remote Sensing Event, 2009 Joint
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3460-2
Electronic_ISBN :
978-1-4244-3461-9
Type :
conf
DOI :
10.1109/URS.2009.5137492
Filename :
5137492
Link To Document :
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