DocumentCode
2895217
Title
SAR Image Classification Combining Structural and Statistical Methods
Author
Tankam, Narcisse Talla ; Dipanda, Albert ; Fotsing, Janvier ; Tonye, Emmanuel
Author_Institution
Comput. Sci. Dept., Univ. of Dschang (IUTFV-UDs), Bandjoun, Cameroon
fYear
2011
fDate
Nov. 28 2011-Dec. 1 2011
Firstpage
468
Lastpage
475
Abstract
The main objective of this paper is to develop a new technique of SAR image classification. This technique combines structural parameters, including the Sill, the slope, the fractal dimension and the range, with statistical methods in a supervised image classification. Thanks to the range parameter, we define the suitable size of the image window used in the proposed approach of supervised image classification. This approach is based on a new way of characterising different classes identified on the image. The first step consists in determining relevant area of interest. The second step consists in characterising each area identified, by a matrix. The last step consists in automating the process for image classification.
Keywords
fractals; image classification; learning (artificial intelligence); statistical analysis; SAR image classification; fractal dimension; image window; statistical methods; structural method; supervised image classification; Educational institutions; Equations; Fractals; Image classification; Mathematical model; Statistical analysis; Structural engineering; SAR image; structural parameter; supervised classification; variogram;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal-Image Technology and Internet-Based Systems (SITIS), 2011 Seventh International Conference on
Conference_Location
Dijon
Print_ISBN
978-1-4673-0431-3
Type
conf
DOI
10.1109/SITIS.2011.13
Filename
6120689
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