In this paper we present a new technique for texturing a Digital Surface Map (DSM) formed using a series of texel images (fused digital image/lidar) taken from a low-cost small unmanned aerial vehicle (UAV). In previous algorithms, an orthonormal view and a single beam had been used to texture the output DSM. The problem of using orthorectified texture obtained from such a view and a lidar scanner with multiple beams is addressed, and a new technique is described where the texture is selected based on the orientation of the triangular mesh formed by tessellating the 3D points from the lidar point cloud. This paper demonstrates the improvement in quality of the output textured DSM when viewed from various viewpoints in a 3D viewer. The stretched pixels are reduced and the texture of the side of objects is greatly improved. The final output textured DSM is shown and the improvement over the previous method is reported.
Methods for the creation of Textured Digital Surface Models (TDSM), which are a 3D representation of a terrain surface, are of increasing interest. This paper investigates the prospects for the generation of higher resolution TDSMs using texel images taken from a low cost unmanned aerial system (UAS). Coarse measurements for attitude and position are obtained from a low cost GPS/IMU fitted into the UAS. Using these coarse measurements and the data from the texel image, the error in the camera position and attitude is reduced which helps in producing an accurate TDSM. The main reason for using texel images is that these images contain both 2D image data and 3D lidar data. Despite having many texel images as input, the out- put TDSM reported previously only has approximately same resolution as the input texel image. In this pa- per, we propose a method to combine these low resolution texel images to produce a TDSM with high resolution texture using multi-frame Wiener filter super- resolution. The final image has the resolution at the sub-pixel level instead of pixel level and because of this, the TDSM looks visually better. The improvement pro- vided by implementing super-resolution on the texture is reported and the final registered TDSM results are shown.
Formation of a Textured Digital Elevation Model (TDEM) has been useful in many applications in the fields of agriculture, disaster response, terrain analysis and more. Use of a low-cost small UAV system with a texel camera (fused lidar/digital imagery) can significantly reduce the cost compared to conventional aircraft-based methods. This paper reports continued work on this problem reported in a previous paper by Bybee and Budge, and reports improvements in performance. A UAV fitted with a texel camera is flown at a fixed height above the terrain and swaths of texel image data of the terrain below is taken continuously. Each texel swath has one or more lines of lidar data surrounded by a narrow strip of EO data. Texel swaths are taken such that there is some overlap from one swath to its adjacent swath. The GPS/IMU fitted on the camera also give coarse knowledge of attitude and position. Using this coarse knowledge and the information from the texel image, the error in the camera position and attitude is reduced which helps in producing an accurate TDEM. This paper reports improvements in the original work by using multiple lines of lidar data per swath. The final results are shown and analyzed for numerical accuracy.
KEYWORDS: 3D image processing, Image registration, 3D modeling, LIDAR, 3D metrology, Image restoration, Digital imaging, Cameras, Image processing, Image sensors
The importance of creating 3D imagery is increasing and has many applications in the field of disaster response, digital elevation models, object recognition, and cultural heritage. Several methods have been proposed to register texel images, which consist of fused lidar and digital imagery. The previous methods were limited to registering up to two texel images or multiple texel swaths having only one strip of lidar data per swath. One area of focus still remains to register multiple texel images to create a 3D model. The process of creating true 3D images using multiple texel images is described. The texel camera fuses the 2D digital image and calibrated 3D lidar data to form a texel image. The images are then taken from several perspectives and registered. The advantage of using multiple full frame texel images over 3D- or 2D-only methods is that there will be better registration between images because of the overlapping 3D points as well as 2D texture used in the joint registration process. The individual position and rotation mapping to a common world coordinate frame is calculated for each image and optimized. The proposed methods incorporate bundle adjustment for jointly optimizing the registration of multiple images. Sparsity is exploited as there is a lack of interaction between parameters of different cameras. Examples of the 3D model are shown and analyzed for numerical accuracy.
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