Registration of Radar and Optical Satellite Images Using Multiscale Filter Technique and Information Measure

Since a spectacular series of missions in the context of the Earth Observing System (EOS) by NASA beginning from the late 1990’s, the significance of the satellite remote sensing has been recognized all over the world (Kafatos & Qu, 2007; Kaufman et al., 1998). In particular, the applications on hazard mitigation and resource exploration have been widely regarded as one of basic approaches over the past years (e.g., Barrett et al., 1991; Chuvieco, 2008; Fu et al., 2004; Ninomiya et al., 2005; 2006; Realmuto, 2000; Sato et al., 2006; Teeuw, 2007; Urai et al., 2007). In general, remote sensing, from different points of view, includes many branches, or exactly speaking many application fields, such as environmental and ecological remote sensing, geological remote sensing, and military remote sensing. In this chapter, we focus our research on geological applications. However, the proposed algorithms and approaches might be applicable to every fields associated with image registration processing. Although remotely sensed optical images from satellite sensors can meet most needs in the practical applications, considerable weather-dependence limits its functional deployment under some circumstances. For instance, during the period of the devastating Ms 8.0 Wenchuan earthquake in the summer of 2008 (Fu et al., 2009), the most optical images from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) (Yamaguchi et al., 1998) sensors on the NASA’s Terra satellite can hardly be used to do some refined applications just because of heavy clouds contaminated. However, SAR (Synthetic Aperture RADAR) images are not influenced by climate and time. In practical applications, the optical satellite images, in particular with high resolutions from sensors such as SPOT (Chevrel et al., 1981) and IKONOS (Tanaka & Sugimura, 2001), provides excellent legibility, but they may be affected by the clouds and weather conditions. On the other hand, SAR images are not influenced by climate and they can be obtained day-and-night, but they suffer from a serious intrinsic speckle noise (Franceschetti & Lanari, 1999; Lampropoulos & Boulter, 1997). 24