Unmanned aerial vehicles (UAV) are increasingly used for topographic mapping. The camera calibration for UAV image blocks can be performed a priori or during the bundle block adjustment (self-calibration). For an area of interest with flat scene and corridor configuration, the focal length of camera is highly correlated with the height of the camera. Furthermore, systematic errors of camera calibration accumulate on the longer dimension and cause deformation. Therefore, special precautions must be taken when estimating camera calibration parameters. In order to better investigate the impact of camera calibration errors, a synthetic, error-free aerial image block is generated to simulate several issues of interest. Firstly, the erroneous focal length in the case of camera pre-calibration is studied. Nadir images are not able to prevent camera poses from drifting to compensate for the erroneous focal length, whereas the inclusion of oblique images brings significant improvement. Secondly, the case where the focal length varies gradually (e.g., when the camera subject to temperature changes) is investigated. The neglect of this phenomenon can substantially degrade the 3D measurement accuracy. Different flight configurations and flight orders are analyzed, the combination of oblique and nadir images shows better performance. At last, the rolling shutter effect is investigated. The influence of camera rotational motion on the final accuracy is negligible compared to that of the translational motion. The acquisition configurations investigated are not able to mitigate the degradation introduced by the rolling shutter effect. Other solutions such as correcting image measurements or including camera motion parameters in the bundle block adjustment should be exploited.

<p><strong>Abstract.</strong> Unmanned aerial vehicles (UAV) are increasingly used for topographic mapping. The camera calibration for UAV image blocks can be performed <i>a priori</i> or during the bundle block adjustment (self-calibration). For an area of interest with flat, corridor configuration, the focal length of camera is highly correlated with the height of camera. Furthermore, systematic errors of camera calibration accumulate on the longer dimension and cause deformation. Therefore, special precautions must be taken when estimating camera calibration parameters. In this paper, a simulated, error-free aerial image block is generated. error is then added on camera calibration and given as initial solution to bundle block adjustment. Depending on the nature of the error and the investigation purpose, camera calibration parameters are either fixed or re-estimated during the bundle block adjustment. The objective is to investigate how certain errors in the camera calibration impact the accuracy of 3D measurement without the influence of other errors. All experiments are carried out with <i>Fraser</i> camera calibration model being employed. When adopting a proper flight configuration, an error on focal length for the initial camera calibration can be corrected almost entirely during bundle block adjustment. For the case where an erroneous focal length is given for pre-calibration and not re-estimated, the presence of oblique images limits the drift on camera height hence gives better camera pose estimation. Other than that, the error on focal length when neglecting its variation during the acquisition (e.g., due to camera temperature increase) is also investigated; a bowl effect is observed when one focal length is given in camera pre-calibration to the whole image block. At last, a local error is added in image space to simulate camera flaws; this type of error is more difficult to be corrected with the <i>Fraser</i> camera model and the accuracy of 3D measurement degrades substantially.</p>

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l’information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N-th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work.

After 10 years of pioneering aerial digital camera development, IGN’s CAMv2 project began in 2006 with the main goal of upgrading the then current system. This had been used for research applications since 1996 in more than six different configurations and in production since 2003 configured with four coloured channels. The new system is still highly modular, enabling combinations of several “basic components”, each consisting of one digital camera head with its storage and control unit. The new camera head was developed around the Kodak KAF‐39 000, 39‐megapixel array sensor (7216 × 5412 pixels). The system is also very versatile thanks to the possible choice of more than 10 different lenses (from 35 mm up to 180 mm focal length) and interchangeable spectral filters. The mechanical and electronic designs have been reduced in size so as to permit many different configurations including multiple camera heads on the same gyro‐stabilised mount. The combination of the performance of camera heads and control and storage units allows a frame rate of one image per 2 s with storage redundancy and 1 s without, leading to a minimum ground sample distance (GSD) of about 9 cm with 60% overlap at an airspeed of 100 m/s. In order to use the new system to best advantage, the adjustment and calibration processes had to be improved. During the summer of 2009, three systems configured for colour imagery, each using four nadir‐viewing camera heads (RGB and NIR), were used to acquire images for IGN production work. In January 2009, an eight‐camera‐head configuration was tested in order to achieve 155‐megapixel pan‐sharpened images with a pan‐sharpening ratio of 2 × 2, and a final swath width of about 14 400 pixels. At that time this configuration needed two windows in the aircraft, but it is now installed on a single, bigger mount.

Ces dernières années, l'IGN a participé à des expériences de photogrammétrie très haute résolution au coursdesquelles des appareils photo numérique (APN) ont été utilisés sur différents types de drones. Cela nous a permisd'affiner les caractéristiques techniques importantes que devrait proposer une nouvelle caméra photogrammétrique ultralégèreet de très haute résolution dédiée à ce type d'application. Le LOEMI, laboratoire en instrumentation de l’IGN, fortde l'expérience qu'il a acquise en concevant et réalisant les caméras aériennes numériques de l'IGN, s'est lancé dans laconception de ce nouvel imageur en 2012 après avoir étudié les possibilités offertes par le marché en termes de capteuret de composant "cerveau" de la caméra. La caméra sera basée sur un capteur CMOS et son électronique d'acquisitionet de traitements sur un SoC+FPGA de la société Xilinx. Grâce à la conception modulaire du dispositif, on pourradisposer, en fonction du porteur utilisé, de configurations plus ou moins autonomes et donc plus ou moins lourdes, ouavec plus ou moins de connectivité ou de capteurs annexes. La configuration la plus légère sera constituée du seul"étage imageur" dont une version est, en ce début 2014, en cours de test. Les premiers prototypes fonctionnelsdevraient être réalisés d'ici la fin de l'année 2014.