Abstract

Image registration is concerned with the problem of how to combine data and/or information from multiple sensors in order to achieve improved accuracies and better inference about the environment than could be attained through the use of a single sensor. Registration of imagery and information from multiple sources is essential for a variety of applications in remote sensing, medical diagnosis, computer vision, and pattern recognition. In general, an image registration methodology must deal with four issues. First, a decision has to be made regarding the choice of primitives for the registration procedure. The second issue is concerned with establishing the registration transformation function that mathematically relates geometric attributes of corresponding primitives. Then, a similarity measure should be devised to ensure the correspondence of conjugate primitives. Finally, a matching strategy has to be designed and implemented as a controlling framework that utilizes the primitives, the similarity measure, and the transformation function to solve the registration problem. This paper outlines a comprehensive investigation and implementation of the involved issues in a semi-automatic registration procedure capable of handling multi-source satellite imagery with varying geometric resolutions.

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