This will count as one of your downloads.
You will have access to both the presentation and article (if available).
This study aims at evaluating metrics for the measurement of camera vibrations in image sequences considering triangles and bars as test patterns. The focus are objective metrics for video stabilization, which are designed to objectively evaluate whether video stabilization was able to eliminate objectionable visual movement.
The metrics are evaluated for simulated image sequences captured by an artificially moved camera. The sequences vary in different properties such as the sensor noise of the camera, as well as the and temporal frequency of the camera vibrations. We analyze the effect of these properties on the metrics behavior. First results using recorded data of thermal imagers are presented as well. The findings will provide insights into the efficacy of different video stabilization metrics on simulated sequences with varying properties.
In this work, performance assessments for TOD models and YOLO-based models are compared. Known image databases as well as synthetic images with triangles and natural backgrounds are degraded according to a unified device description with blur and image noise. The blur caused by optical diffraction and detector footprint is varied by multiple aperture diameters and detector sizes through the application of modulation transfer functions, while the image noise is varied by multiple noise error levels as Gaussian sensor noise. The TOD models are evaluated for the degraded images with triangles, while the YOLO models are applied to the degraded variants of the image databases. For different degradation parameters, the model precisions of the TOD models are compared to figures of merit of the YOLO models such as the mean average precision (mAP). Statistical uncertainties of the performance ranking for different degradation parameters of cameras and both TOD and YOLO models are investigated.
In the first part, we outline the experimental setup of our testbed. It allows for mimicking infrared imaging of real scenes in a controlled laboratory environment. We describe the process of dynamic infrared scene generation as well as the physical limitations of our scene projection setup.
A second part discusses ongoing and future applications. This testbed extends our standard lab measurements for thermal imagers by a image based performance analysis method. Scene based methods are necessary to investigate and assess advanced digital signal processing (ADSP) algorithms which are becoming an integral part of thermal imagers. We use this testbed to look into inferences of unknown proprietary ADSP algorithms by choosing suitable test scenes.
Furthermore, we investigate the influence of dazzling on thermal imagers by coupling infrared laser radiation into the projected scene. The studies allow to evaluate the potential and hazards of infrared dazzling and to describe correlated effects. In a future step, we want to transfer our knowledge of VIS/NIR laser protection into the infrared regime.
View contact details
No SPIE Account? Create one
