26 October 2011 A first reference dataset for the evaluation of geometric correction methods under the scope of remote sensing applications
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Abstract
The geometric correction of images under the scope of remote sensing applications is still mostly a manual work. This is a time and effort consuming task associated with an intra- and inter-operator subjectivity. One of the main reasons may be the lack of a proper evaluation of the different available automatic image registration (AIR) methods, since some of them are only adequate for certain types of applications/data. In order to fulfill a gap in this context, a first reference dataset of pairs of images comprising some types of geometric distortions was created, different spatial and spectral resolutions, and divided according to the Level 1 of CORINE Land Cover nomenclature (European Environment Agency). This dataset will allow for gaining perception of the abilities and limitations of some AIR methods. Some AIR methods were evaluated in this work, including the traditional correlation-based method and the SIFT approach, for which a set of measures for an objective evaluation of the geometric correction process quality was computed for every combination of pair of images/AIR method. The reference dataset is available from an internet address, being expected that it becomes a channel of interaction among the remote sensing community interested in this field.
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Hernâni Gonçalves, Hernâni Gonçalves, Ana C. Teodoro, Ana C. Teodoro, José A. Gonçalves, José A. Gonçalves, Luís Corte Real, Luís Corte Real, } "A first reference dataset for the evaluation of geometric correction methods under the scope of remote sensing applications", Proc. SPIE 8181, Earth Resources and Environmental Remote Sensing/GIS Applications II, 81811P (26 October 2011); doi: 10.1117/12.897976; https://doi.org/10.1117/12.897976
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