Abstract: In this paper, we present a four-step ortho-rectification
procedure for real-time geo-referencing of video data from a low-cost
UAV equipped with a multi-sensor system. The basic procedures for
the real-time ortho-rectification are: (1) decompilation of the video
stream into individual frames; (2) establishing the interior camera
orientation parameters; (3) determining the relative orientation
parameters for each video frame with respect to each other; (4)
finding the absolute orientation parameters, using a self-calibration
bundle and adjustment with the aid of a mathematical model. Each
ortho-rectified video frame is then mosaicked together to produce a
mosaic image of the test area, which is then merged with a well
referenced existing digital map for the purpose of geo-referencing
and aerial surveillance. A test field located in Abuja, Nigeria was
used to evaluate our method. Video and telemetry data were collected
for about fifteen minutes, and they were processed using the four-step
ortho-rectification procedure. The results demonstrated that the
geometric measurement of the control field from ortho-images is
more accurate when compared with those from original perspective
images when used to pin point the exact location of targets on the
video imagery acquired by the UAV. The 2-D planimetric accuracy
when compared with the 6 control points measured by a GPS receiver
is between 3 to 5 metres.
Abstract: Advances technology in the field of photogrammetry
replaces analog cameras with reflection on aircraft GPS/IMU system
with a digital aerial camera. In this system, when determining the
position of the camera with the GPS, camera rotations are also
determined by the IMU systems. All around the world, digital aerial
cameras have been used for the photogrammetry applications in the
last ten years. In this way, in terms of the work done in
photogrammetry it is possible to use time effectively, costs to be
reduced to a minimum level, the opportunity to make fast and
accurate.
Geo-referencing techniques that are the cornerstone of the GPS /
INS systems, photogrammetric triangulation of images required for
balancing (interior and exterior orientation) brings flexibility to the
process. Also geo-referencing process; needed in the application of
photogrammetry targets to help to reduce the number of ground
control points. In this study, the use of direct and indirect georeferencing
techniques on the accuracy of the points was investigated
in the production of photogrammetric mapping.
Abstract: Aerial and satellite images are information rich. They are also complex to analyze. For GIS systems, many features require fast and reliable extraction of roads and intersections. In this paper, we study efficient and reliable automatic extraction algorithms to address some difficult issues that are commonly seen in high resolution aerial and satellite images, nonetheless not well addressed in existing solutions, such as blurring, broken or missing road boundaries, lack of road profiles, heavy shadows, and interfering surrounding objects. The new scheme is based on a new method, namely reference circle, to properly identify the pixels that belong to the same road and use this information to recover the whole road network. This feature is invariable to the shape and direction of roads and tolerates heavy noise and disturbances. Road extraction based on reference circles is much more noise tolerant and flexible than the previous edge-detection based algorithms. The scheme is able to extract roads reliably from images with complex contents and heavy obstructions, such as the high resolution aerial/satellite images available from Google maps.