A combined image matching method for Chinese optical satellite imagery

Image matching is one of the key technologies for digital Earth. This paper presents a combined image matching method for Chinese satellite images. This method includes the following four steps: (1) a modified Wallis-type filter is proposed to determine parameters adaptively while avoiding over-enhancement; (2) a mismatch detection procedure based on a global-local strategy is introduced to remove outliers generated by the Scale-invariant feature transform algorithm, and geometric orientation with bundle block adjustment is employed to compensate for the systematic errors of the position and attitude observations; (3) we design a novel similarity measure (distance, angle and the Normalized Cross-Correlation similarities, DANCC) which considers geometric similarity and textural similarity; and (4) we introduce a hierarchical matching strategy to refine the matching result level by level. Four typical image pairs acquired from Mapping Satellite-1, ZY-1 02C, ZY-3 and GeoEye-1, respectively, are used for experimental analysis. A comparison with the two current main matching algorithms for satellite imagery confirms that the proposed method is capable of producing reliable and accurate matching results on different terrains from not only Chinese satellite images, but also foreign satellite images.