As the need for automating registration techniques is recognized, we feel that there is a need to survey all the registration methods which may be applicable to Earth and space science problems and to evaluate their performances on alarge variety of existing remote sensing data as well as on simulated data of soon-to-be-flown instruments. In this paper we present the first steps towards this quantitative evaluation: a few automatic image registration algorithms are described and first results of their evaluation are presented for three different datasets.
Digital image registration is very important in many applications, such as medical imagery, robotics, visual inspection, and remotely sensed data processing. NASA s Mission To Planet Earth (MTPE) program will be producing enormous Earth global change data, reaching hundreds of Gigabytes per day, that are collected form different spacecrafts and different perspectives using many sensors with diverse resolutions and characteristics. The analysis of such data requires integration, therefore, accurate registration of these data. Image registration is defined as the process which determines the most accurate relative orientation between two or more images, acquired at the same or different times by different or identical sensors. Registration can also provide the absolute orientation between an image and a map.
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