Classifying Microwave Radar Images Using Decision Based Data Fusion

Four different data fusion methods for classifying SAR images with different spatial resolutions were tested and compared. Test area was Helsinki region in Southern Finland and test data 14 ERS-1/2 Tandem pairs. The best method was a method where a posteriori probabilities of lower spatial resolution classification are used as a priori probabilities of higher resolution classification. The increase of overall accuracy was 7-14 %-units depending on date and 10.4% on average when compared to original Tandem pairs. Median filtering increased classification accuracy, but not that much when data fusion methods were used. This means that the need of spatial filtering can be at least partially compensated using data fusion of different spatial resolution images.