6533b7d6fe1ef96bd1265ce5

RESEARCH PRODUCT

SAR Image Classification Combining Structural and Statistical Methods

Janvier FotsingEmmanuel TonyeAlbert DipandaNarcisse Talla Tankam

subject

010504 meteorology & atmospheric sciencesContextual image classificationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)Pattern recognition02 engineering and technology01 natural sciencesFractal dimensionImage (mathematics)Range (mathematics)Matrix (mathematics)Fractal[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceVariogrambusinessComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesMathematics

description

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.

https://hal.archives-ouvertes.fr/hal-00936390