DocumentCode :
2498803
Title :
Texture analysis by universal multifractal features in a polarimetric SAR image
Author :
Martinez, P. ; Schertzer, D. ; Pham, K.
Author_Institution :
Thomson-CSF, Bagneux, France
Volume :
1
fYear :
1996
fDate :
27-31 May 1996
Firstpage :
37
Abstract :
Multifractal features have been widely used in geophysics to characterize natural phenomena but seldom in image processing. Therefore, in this study, the authors show that these features can also be efficient in texture classification. They assume that a natural image texture is the result of a specific two-dimensional multifractal cascade process and so, according to the universal multifractal theory, few parameters are enough to entirely describe this process and therefore the texture. As the multifractal parameters are quite linearly separable, a very simple and fast algorithm is run for the supervised segmentation. In practice, the authors have computed these features on a SIR-C L-band polarimetric SAR image, and used them to segment this image into five classes (sea, shore, forest, urban areas and cultivated fields)
Keywords :
fractals; geophysical signal processing; geophysical techniques; image classification; image segmentation; image texture; radar imaging; radar polarimetry; radar signal processing; remote sensing by radar; spaceborne radar; synthetic aperture radar; L-band; SAR imagery; SIR-C; UHF radar; cultivated fields; forest; fractal; geophysical measurement technique; image classification; image processing; image texture analysis; land surface; natural image texture; radar imaging; radar polarimetry; radar remote sensing; supervised segmentation; terrain mapping; two-dimensional multifractal cascade process; universal multifractal features; universal multifractal theory; urban area; vegetation mapping; Anisotropic magnetoresistance; Clouds; Fractals; Frequency estimation; Geophysics; Image analysis; Image segmentation; Image texture; Image texture analysis; L-band;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International
Conference_Location :
Lincoln, NE
Print_ISBN :
0-7803-3068-4
Type :
conf
DOI :
10.1109/IGARSS.1996.516237
Filename :
516237
Link To Document :
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