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The main scope of this paper is evaluating performance of cameras integrated UAV for geomatic applications by the way of Digital Elevation Model (DEM) generation in a small area (approximately 5 ha).
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During the process of camera calibration, nonlinear optimization technique is crucial to obtain the best performance of camera parameters.
The major causes to make these differences are (1) the performance of camera motion cancellation and (2) the sizes of objects or motions in video clips.
In these events, the foreground objects are often in the center part in a video clip and accordingly, the performance of camera motion cancellation is higher than other events.
But there is nonetheless an intrinsic difference, even an incommensurable gulf between the performance on camera of scenes of such deep and volatile intimacy and the filming of them from behind the camera.
To test the feasibility and the performance of SiPM cameras, a focal plane camera prototype module, upgraded with High Density NUV - SiPMs, produced by FBK, with a micro cell of 30 μm x 30 μm and 6 mm x 6 mm area, is being assembled.
Finally the optical performance of the cameras was assessed and the data collected was used to perform fine adjustments to obtain focus uniformity and optical axis alignment.
Moreover, the variation of the weather condition affects the performance of traffic cameras severely.
Objective methods for characterizing the performance of digital cameras can be based on test-targets or algorithms.
In the result, we found that MTF and NNPS are effective and novel standards to evaluate imaging performance of gamma cameras instead of conventional NEMA standards.
In this paper, a novel precision synchronisation method is presented which exploits the similarity of behaviour and performance of matched cameras (or image sensors) by subjecting them to a common clock.
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