Abstract
Real-time image georeferencing is essential to the prompt generation of spatial information such as orthoimages from the image sequence acquired by an airborne multi-sensor system. It is mostly based on direct georeferencing using a GPS/INS system, but its accuracy is limited by the quality of the GPS/INS data. More accurate results can be acquired using traditional aerial triangulation (AT) combined with GPS/INS data, which can be performed only as a post-processing method due to intense computational requirements. In this study, we propose a sequential AT algorithm that can produce accurate results comparable to those from the simultaneous AT algorithm in real time. Whenever a new image is added, the proposed algorithm rapidly performs AT with minimal computation at the current stage using the computational results from the previous stage. The experimental results show that the georeferencing of an image sequence at any stage took less than 0.1 s and its accuracy was determined within ± 5 cm on the estimated ground points, which is comparable to the results of simultaneous AT. This algorithm may be used for applications requiring real-time image georeferencing such as disaster monitoring and image-based navigation.
Highlights
Real-time acquisition of spatial data such as DSMs or orthoimages is needed to provide appropriate and prompt countermeasures to situations such as natural disasters or accidents.For example, by monitoring the areas of forest fires and floods using the spatial data acquired by an airborne multi-sensor system, we can observe the situation, assess on-going damage, effectively decide how to evacuate people and restore damaged areas.Disaster monitoring systems based on airborne real-time acquisition of spatial data mostly consist of an aerial segment for data acquisition of the target areas and a ground segment for data processing and delivery [1,2,3,4]
The aerial triangulation (AT) results are verified in terms of exterior orientation parameters (EOP) positions, EOP attitudes, and ground points (GP)
The traditional AT algorithm can produce very accurate results, it cannot be employed for real-time georeferencing due to its computation time, which dramatically increases with the number of images
Summary
Real-time acquisition of spatial data such as DSMs (digital surface models) or orthoimages is needed to provide appropriate and prompt countermeasures to situations such as natural disasters or accidents.For example, by monitoring the areas of forest fires and floods using the spatial data acquired by an airborne multi-sensor system, we can observe the situation, assess on-going damage, effectively decide how to evacuate people and restore damaged areas.Disaster monitoring systems based on airborne real-time acquisition of spatial data mostly consist of an aerial segment for data acquisition of the target areas and a ground segment for data processing and delivery [1,2,3,4]. The image sequences acquired by such a system can be extremely useful for decision makers to establish effective countermeasures by comparing such images with existing spatial data such as 2D or 3D maps, city models, DSMs, and so on. Such a comparison is possible only if the images are rectified with the same coordinate system as the existing spatial data, which is mainly generated with an absolute ground coordinate system. In order to overlap the images on a 2D map, the images should be orthorectified with the same coordinate system as the map
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