期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B4
页码：927-932
出版社：Copernicus Publications
摘要：The enormous increase in the volume of remotely sensed data, which might be in different formats and relative to different reference frames, has created the need for robust data processing techniques that can fuse data observed by different acquisition systems. This need is motivated by the fact that collected data by these sensors are complementary in nature. Therefore, simultaneous utilization of the collected data would guarantee full understanding of the object/phenomenon under consideration. In this regard, a registration procedure can be defined as being 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 multi-source imagery captured under different conditions is a challenging problem. The difficulty is attributed to the varying radiometric and geometric resolutions of the acquired imagery. In general, an automatic image registration methodology must deal with four issues; registration primitives, transformation function, similarity measure and matching strategy. This paper outlines a comprehensive image registration paradigm that can handle multi-source imagery with varying geometric and radiometric properties. The most appropriate primitives, transformation function, and similarity measure have been incorporated in a matching strategy to solve the registration problem. Experimental results using real data proved the feasibility and the robustness of the suggested paradigm
