Terahertz metamaterials on flexible polypropylene substrate

The final publication is available at Springer via http://dx.doi.org/10.1007/s11468-014-9724-1In this work, we present a metamaterial working at terahertz frequencies made over a flexible polypropylene sub-strate. The experimental measurements, in accordance with the numerical calculations, show the metamaterial reliance on the impinging electric field polarization. The structure s symmetry yields purely electrical resonant responses eliminating bianisotropy effects. The widely used bendable polypropylene polymer may promote the insertion of metamaterial-based structures with special electromagnetic response in a number of objects of our daily lives such as textiles, automotive components, and sensingThis work was supported by the Spanish MICINN under contracts CONSOLIDER EMET CSD2008-00066 and TEC2011-28664-C02-02 and by the Universitat Politecnica de Valencia under the program INNOVA 2011.Ortuño Molinero, R.; García Meca, C.; Martínez Abietar, AJ. (2014). 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QUALITY ASSESSMENT OF BUILDING TEXTURES EXTRACTED FROM OBLIQUE AIRBORNE THERMAL IMAGERY

Thermal properties of the building hull became an important topic of the last decade. Combining the thermal data with building models makes it possible to analyze thermal data in a 3D scene. In this paper we combine thermal images with 3D building models by texture mapping. We present a method for texture extraction from oblique airborne thermal infrared images. We put emphasis on quality assessment of these textures and evaluation of their usability for thermal inspections. The quality measures used for assessment are divided to resolution, occlusion and matching quality

Alignment of 3D Building Models and TIR Video Sequences with Line Tracking

Thermal infrared imagery of urban areas became interesting for urban climate investigations and thermal building inspections. Using a flying platform such as UAV or a helicopter for the acquisition and combining the thermal data with the 3D building models via texturing delivers a valuable groundwork for large-area building inspections. However, such thermal textures are useful for further analysis if they are geometrically correctly extracted. This can be achieved with a good coregistrations between the 3D building models and thermal images, which cannot be achieved by direct georeferencing. Hence, this paper presents methodology for alignment of 3D building models and oblique TIR image sequences taken from a flying platform. In a single image line correspondences between model edges and image line segments are found using accumulator approach and based on these correspondences an optimal camera pose is calculated to ensure the best match between the projected model and the image structures. Among the sequence the linear features are tracked based on visibility prediction. The results of the proposed methodology are presented using a TIR image sequence taken from helicopter in a densely built-up urban area. The novelty of this work is given by employing the uncertainty of the 3D building models and by innovative tracking strategy based on a priori knowledge from the 3D building model and the visibility checking

Identification of Errors in 3D Building Models by a Robust Camera Pose Estimation

This paper presents a method for identification of errors in 3D building models which are results of inaccurate creation process. Error detection is carried out within the camera pose estimation. As observations, parameters of the building corners and of the line segments detected in the image are used and conditions for the coplanarity of corresponding edges are defined. For the estimation, the uncertainty of the 3D building models and image features are taken into account

QUALITY ASSESSMENT OF MAPPING BUILDING TEXTURES FROM INFRARED IMAGE SEQUENCES

Generation and texturing of building models is a fast developing field of research. Several techniques have been developed to extract building geometry and textures from multiple images and image sequences. In this paper, these techniques are discussed and extended to automatically add new textures from infrared (IR) image sequences to existing building models. In contrast to existing work, geometry and textures are not generated together from the same dataset but the textures are extracted from the image sequence and matched to an existing geo-referenced 3D building model. The texture generation is divided in two main parts. The first part deals with the estimation and refinement of the exterior camera orientation. Feature points are extracted in the images and used as tie points in the sequence. A recorded exterior orientation of the camera s added to these homologous points and a bundle adjustment is performed starting on image pairs and combining the hole sequence. A given 3d model of the observed building is additionally added to introduce further constraint as ground control points in the bundle adjustment. The second part includes the extraction of textures from the images and the combination of textures from different images of the sequence. Using the reconstructed exterior camera orientation for every image of the sequence, the visible facades are projected into the image and texture is extracted. These textures normally contain only parts of the facade. The partial textures extracted from all images are combined to one facade texture. This texture is stored with a 3D reference to the corresponding facade. This allows searching for features in textures and localising those features in 3D space. It will be shown, that the proposed strategy allows texture extraction and mapping even for big building complexes with restricted viewing possibilities and for images with low optical resolution

Line-Based Registration of DSM and Hyperspectral Images

Data fusion techniques require a good registration of all the used datasets. In remote sensing, images are usually geo-referenced using the GPS and IMU data. However, if more precise registration is required, image processing techniques can be employed. We propose a method for multi-modal image coregistration between hyperspectral images (HSI) and digital surface models (DSM). The method is divided in three parts: object and line detection of the same object in HSI and DSM, line matching and determination of transformation parameters. Homogeneous coordinates are used to implement matching and adjustment of transformation parameters. The common object in HSI and DSM are building boundaries. They have apparent change in height and material, that can be detected in DSM and HSI, respectively. Thus, before the matching and transformation parameter computation, building outlines are detected and adjusted in HSI and DSM. We test the method on a HSI and two DSM, using extracted building outbounds and for comparison also extracted lines with a line detector. The results show that estimated building boundaries provide more line assignments, than using line detector

Detection of windows in building textures from airborne and terrestrial infrared image sequences

Infrared (IR) images depict thermal radiation of physical objects. Imaging the building façades and the roofs with an IR camera, thermal inspections of the buildings can be carried out. In such inspections a spatial correspondence between IR-images and the existing 3D building models can be helpful. Texturing 3D building models with IR images this spatial correspondence can be created. Furthermore in textures heat leakages can be detected and the heat bridges can be stored together with 3D building data. However, before extracting leakages, the windows should be located. In IR images glass reflects the surrounding and shows false results for the temperature measurements. Consequently, the windows should be detected in IR images and excluded for the inspection. The most common algorithms for window detection were developed for the images in the visual band. In this paper, an algorithm for window detection in textures extracted from terrestrial IR images is proposed. In the first step, small objects have to be removed by scaling down the image (texture). Then in the scaled image, regions are detected using a local dynamic threshold. Morphological operations are used to remove false detections and unify substructures of the windows. For every extracted region, which is a candidate for a window, the center of gravity is calculated. It is assumed that windows on façades are ordered in regular rows and columns. First the points are grouped into rows using histogram of height created from extracted gravity centers. Then masked correlation is used to detect the position and size of the windows. Finally, the gaps in the grid of windows are completed. For the first experiments we use a dataset from densely build urban area captured in Munich, Germany. The IR image sequences were taken from a vehicle driving on the street around the test area. Camera was directed to the building in oblique view. According to the acquisition geometry, no façade could be completely seen in one frame. Therefore, we combine the textures from many frames. To these textures we applied our algorithm for window detection. First results are promising. Applying the method for our test dataset, 79% completeness and 80% correctness could be achieved

Photogrammetry and Remote Sensing in the MSc Program "ESPACE" at Technische Universitaet Muenchen

ESPACE is an interdisciplinary Master's study programme of Technische Universitaet Muenchen (TUM) positioned at the interface between space technology and the engineering and natural science-based use of satellite data. It combines the technical aspects of the satellite and observation systems with scientific and commercial applications. A core topic beside space engineering and satellite applications engineering is satellite and remote sensing data analysis. This paper explains the background and goals of the Masters's study programme, addresses the target groups and qualification profile, and gives an overview about the specialization fields. The special role of Photogrammetry and Remote Sensing is further explained in this context. The structure and embedding of international alliances by a double degree program with Wuhan University is shown