Mobile mapping systems that detect and geo-reference road markings almost always consist of a stereo camera system integrated with a global positioning system/inertial navigation system. The data acquired by this navigational system allows features detected in the stereo images to be assigned global co-ordinates. An essential step in this process is the calibration of the cameras, as it relates the pose of the two cameras to each other and a world co-ordinate system. In Europe, road markings must be evaluated from a 35 m range, so the cameras are required to have a wide field of view. Traditional calibration methods supposedly require a calibration object that would fill most of the calibration images. This large field of view would require a calibration object of substantial size that would be impractical for the purposes of this portable system. This study explores the theory of camera calibration and then details two camera calibration techniques (using portable 3D and 2D calibration objects). The accuracy of these methods is then evaluated using a ground-truth experiment.

Compact polarimetry (compact-pol) architecture is a new hybrid mode for synthetic aperture radar (SAR) and is proposed for the future Canadian Radarsat Constellation Mission (RCM) and the future Japanese ALOS-2 mission. The Compact-pol mode transmits single circular polarization (left/right) and receives simultaneous coherent orthogonal linear polarizations. In this paper, we use Radarsat-2 C-band quad polarization (quad-pol) data to simulate RCM compactpol data, introduce useful compact-pol parameters using compact-pol decomposition theories, and show that the compact-pol mode is capable of maintaining important polarimetric information on forest structure and changes, even though there is the loss of information through projection of the complex scattering matrix of quad-pol on a single-pixel level. Examples are given to illustrate how to use the compact decomposition parameters for forestry applications. (4 pages)

Nowadays, the 3D radar is vigorous in the radar field. The data collected by those radars, such as SAR, is quite valuable. However, there are some problems in image interpretation. In order to analyse the SAR image more accurately, 3D visualization is a necessary assistant technology. The traditional visualization method visualizes the data by OpenGL's fixed pipelines with optical models, which not only work on a different reflection principle from microwave models, but also change the raw value of SAR data. This paper presents a novel method to enhance 3D visualization of SAR data, which generates the visual and shadow effects with microwave scattering models, and also reserves the raw information. The method is based on OpenGL's programmable pipelines. It takes advantage of geometry information from digital elevation model (DEM) and scattering information from simulated SAR image to realize the 3D visualization with OpenGL Shading Language (GLSL). In the end of this paper, we show the results using a terrain model with SAR data to create the surface and what's more, create a shadow without losing the scattering information of SAR data. (4 pages)

This paper researches on many kinds of 3D model data and city image data, based on the 3D virtual platform of UC-win/Road, to realize the 3D visualization of urban areas, interacting on real time, and rendering with the autonomous demo in many ways. We propose to utilize open access large-scale high-definition images based on Google Earth to realize seamless splice and coordinate matching in the platform. Moreover 3D terrain is then generated by using terrain patches to deal with elevation. For urban construction, infrastructure, trees and other common 3D models, we perform 3D model reconstruction by accessing massive model data resources from open 3D Warehouse. Based on the platform of UC-win/Road, the reconstructed 3D models can be saved and recalled models with large quantities of city auxiliary models being generated for these 3D scenes. Our system can construct urban lakes and rivers, and generate rain, snow, fog and other typical weather phenomena dynamically. Moreover, a variety of ways can be chosen, based on scripting, to realize roam and real-time interaction, and build automatic playback system, while outputting recorded video files.