Combination of feature-based and area-based image registration technique for high resolution remote sensing image

Image registration is the process of geometrically aligning one image to another image of the same scene taken from different viewpoints or by different sensors. High resolution remote sensing images have made it more convenient for people to study the earth; however, they also create challenges for traditional research methods. In terms of image registration, there are a number of problems with using current image registration techniques for high resolution images. This study proposes a new image registration technique, which is based on the combination of feature-based matching (FBM) and area-based matching (ABM). A wavelet-based feature extraction technique, normalized cross-correlation matching and relaxation-based image matching techniques are employed in this new method. Two pairs of data sets, panchromatic images of IKONOS and a panchromatic image of IKONOS with a multispectral image of Quickbird, are used to evaluate the proposed image registration algorithm. The experiment results show that the proposed algorithm can select enough control points to reduce the local distortions caused by terrain relief.