Abstract
A new pyramidal approach for aerial image matching is proposed. Challenges associated with aerial imagery, such as the complexity and diversity, variations with time, and large data size, have led to exploration of various techniques. One method uses orientation code matching, which together with a pyramidal approach can achieve efficient wide-area aerial image matching. However, as the pyramid levels deepen, the matching success rate tends to decrease. To avoid this problem, we classify aerial imagery broadly into two types of scenes, and define different methods that are appropriate to respective scenes. The proposed technique produces two orientation code pyramids, from which the appropriate one can be selected adaptively. Therefore, we can obtain robust and efficient matching for any scene. Experimental results obtained using both urban and mountainous scenes demonstrate that the matching success rate at the upper pyramid levels is superior to that obtained when using only one generation method.
