Abstract:

SAR has the ability to work all weather, and can provide high resolution remote sensing images, so it is an important direction to study. The SAR image classification is a key step for SAR processing. At present, the study on SAR image classification is mostly based on singlechannel data, multichannel data has greatly enriched the information amount of ground target features, taking use of multichannel data to carry out SAR image classification is an important development direction. In the paper, the classification method of composing multichannel data classification results is proposed. Firstly, the method is to use different channel data to classify separately by SVM, then composes different classification results based on granularity composition theory. The paper mainly focuses on the basic flow and steps of this method. In the end, an experiment of using singlechannel data to classify and merging multichannel data features to classify is done, the result proves the method of this paper is viable.

Key words: multichannel data, SAR, image classification, SVM, quotient space granularity composition