Registration techniques for multimodal images and its application

Registration between multimodal images is carried out using mutual information (MI) as a similarity measure. MI registration does not require linearity between two images; therefore, this method is effective in registration between multimodal images. First, corresponding points between multiband images are obtained in sub-pixel level. We evaluated the sub-pixel registration errors between two images. In this case, MI shows more accurate performance than sum square distance (SSD) and normalized cross-correlation (NCC). This result shows that the technique is robust with respect to variants of illumination or wavelength of observation band. Second, image-to-map registration is also successful. These results proved the potential of MI to build GIS with satellite images and map data.