Abstract:

According to the image fusion of optical and SAR(Synthetic Aperture Radar), the multimodal and multiscale features including pixel features, texture features and edge features were analyzed in order to improve the traditional homologous image registration and fusion algorithm. Then the improved SURF(Speeded Up Robust Features) operator, texture analysis and contour extraction algorithm were adopted to obtain the multimodal and multiscale features of the heterologous images. By standardization algorithm of the fuzzy scale and dimension, the differences between the feature pairs of the heterologous images were overcome, which made the matching of the feature pairs available. The accuracy of registration and fusion were ensured through the method of fuzzy
correlation coefficient, and the registration and fusion of optical-SAR images were completed. Finally, the modified algorithm was verified and compared with the traditional fusion methods. Experimental results show that the multimodal registration and fusion algorithm can improve the precision and adaptability of optical-SAR registration. The average accuracy rate of registration and fusion can reach to 87. 7%, which can satisfy the requirement of high precision registration and fusion.

Key words: image registration, synthetic aperture radar(SAR), multimodal features, fuzzy clustering