bluuebunny/crossref_metadata_2025 huggingface dataset:
AN ACCURACY ASSESSMENT OF AUTOMATED PHOTOGRAMMETRIC TECHNIQUES FOR 3D MODELING OF COMPLEX INTERIORS
Authors: Georgantas A. , Brédif M. , Pierrot-Desseilligny M.
Published: August 2012

Abstract. This paper presents a comparison of automatic photogrammetric techniques to terrestrial laser scanning for 3D modelling of complex interior spaces. We try to evaluate the automated photogrammetric techniques not only in terms of their geometric quality compared to laser scanning but also in terms of cost in money, acquisition and computational time. To this purpose we chose as test site a modern building’s stairway. APERO/MICMAC ( ©IGN )which is an Open Source photogrammetric software was used for the production of the 3D photogrammetric point cloud which was compared to the one acquired by a Leica Scanstation 2 laser scanner. After performing various qualitative and quantitative controls we present the advantages and disadvantages of each 3D modelling method applied in a complex interior of a modern building.
MULTI TIMES IMAGES FUSION BASED ON WAVELET THEORY
Authors: Rokhsari S. , Abed-Elmdoust A. , Karimi M.
Published: August 2012

Abstract. The development of new monitoring systems and the increasing interest of researchers in obtaining reliable measurements have leaded to the development of automatic monitoring moving objects. One way to ensure monitoring object is to use multi time's image fusion. Image fusion is a sub area of the more general topic of data fusion. Image fusion can be roughly defined as the process of combining multiple input images into an image, which contains the "relevant" information from the inputs. The aim of image fusion is to integrate complementary and redundant information from multiple images to create a composite that contains a better fused image than any of the individual source images. Main purpose of the former is to increase both the spectral and spatial resolution of images by combining multiple images. In this paper we tried to use this theory for moving object tracking, so with the usage of multi images that are obtained in different times and combination of them with this theory we identify the path of movement of moving object so this result could help us to implement automatic systems that that could monitor objects automatically without human interventation. So in this paper first we will discuss the principal of fusion and its famous method (wavelet theory) and all process that involved for doing a fusion process.
KINECT-BASED REAL-TIME RGB-D IMAGE FUSION METHOD
Authors: Guo W. , Du T. , Zhu X. , Hu T.
Published: August 2012

Abstract. 3D reconstruction of indoor environments based on vision has been developed vigorously. However, the algorithm's complexity and requirements of professional knowledge make it restricted in practical application. With the proposition of the concept of Volunteered Geographic Information (VGI), the traditional method is no longer suitable for VGI. So in this work we utilize consumer depth cameras – Kinect to enable non-expert users to reconstruct 3D model of indoor environment with RGB-D data. Considering the possibility of camera tracking failure we propose a method to perform automatic relocalization.
AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE
Authors: Kwak E. , Al-Durgham M. , Habib A.
Published: August 2012

Abstract. Digital Building Model is an important component in many applications such as city modelling, natural disaster planning, and aftermath evaluation. The importance of accurate and up-to-date building models has been discussed by many researchers, and many different approaches for efficient building model generation have been proposed. They can be categorised according to the data source used, the data processing strategy, and the amount of human interaction. In terms of data source, due to the limitations of using single source data, integration of multi-senor data is desired since it preserves the advantages of the involved datasets. Aerial imagery and LiDAR data are among the commonly combined sources to obtain 3D building models with good vertical accuracy from laser scanning and good planimetric accuracy from aerial images. The most used data processing strategies are data-driven and model-driven ones. Theoretically one can model any shape of buildings using data-driven approaches but practically it leaves the question of how to impose constraints and set the rules during the generation process. Due to the complexity of the implementation of the data-driven approaches, model-based approaches draw the attention of the researchers. However, the major drawback of model-based approaches is that the establishment of representative models involves a manual process that requires human intervention. Therefore, the objective of this research work is to automatically generate building models using the Minimum Bounding Rectangle algorithm and sequentially adjusting them to combine the advantages of image and LiDAR datasets.
A NEW APPROACH OF DIGITAL BRIDGE SURFACE MODEL GENERATION
Authors: Ju H.
Published: August 2012

Abstract. Bridge areas present difficulties for orthophotos generation and to avoid “collapsed” bridges in the orthoimage, operator assistance is required to create the precise DBM (Digital Bridge Model), which is, subsequently, used for the orthoimage generation. In this paper, a new approach of DBM generation, based on fusing LiDAR (Light Detection And Ranging) data and aerial imagery, is proposed. The no precise exterior orientation of the aerial image is required for the DBM generation. First, a coarse DBM is produced from LiDAR data. Then, a robust co-registration between LiDAR intensity and aerial image using the orientation constraint is performed. The from-coarse-to-fine hybrid co-registration approach includes LPFFT (Log-Polar Fast Fourier Transform), Harris Corners, PDF (Probability Density Function) feature descriptor mean-shift matching, and RANSAC (RANdom Sample Consensus) as main components. After that, bridge ROI (Region Of Interest) from LiDAR data domain is projected to the aerial image domain as the ROI in the aerial image. Hough transform linear features are extracted in the aerial image ROI. For the straight bridge, the 1st order polynomial function is used; whereas, for the curved bridge, 2nd order polynomial function is used to fit those endpoints of Hough linear features. The last step is the transformation of the smooth bridge boundaries from aerial image back to LiDAR data domain and merge them with the coarse DBM. Based on our experiments, this new approach is capable of providing precise DBM which can be further merged with DTM (Digital Terrain Model) derived from LiDAR data to obtain the precise DSM (Digital Surface Model). Such a precise DSM can be used to improve the orthophoto product quality.
A SEMIAUTOMATIC APPROACH FOR GENERATION OF SITE MODELS FROM CARTOSAT-2 MULTIVIEW IMAGES
Authors: Mahapatra A. , Pandey S. , Sudheer Reddy D. , Subramanyam P. S. , Das B. K. , Radhadevi P. V. , Saibaba J. , Varadan G.
Published: August 2012

Abstract. In the last decade there has been a paradigm shift in creating, viewing and utilizing geospatial data for planning, navigation and traffic management of urban areas. Realistic, three-dimensional information is preferred over conventional two dimensional maps. The paper describes objectives, methodology and results of an operational system being developed for generation of site model from Cartosat-2 multiview images. The system is designed to work in operational mode with varying level of manual interactivity. A rigorous physical sensor model based on collinearity condition models the "step n stare" mode of image acquisition of the satellite. The relative orientation of the overlapping images is achieved using coplanarity condition and conjugate points. A procedure is developed to perform digitization in mono and stereo modes. A technique for refining manually digitized boundaries is developed. The conjugate points are generated by establishing a correspondence between the points obtained on refined edges to analogous points on the images obtained with view angles ±26 deg. It is achieved through geometrically constrained image matching method. The results are shown for a portion of multi-view images of Washington City obtained from Cartosat-2. The scheme is generic to accept very high resolution stereo images from other satellites as input.
A NOVEL 3D CITY MODELLING APPROACH FOR SATELLITE STEREO DATA USING 3D ACTIVE SHAPE MODELS ON DSMS
Authors: Sirmacek B. , Taubenboeck H. , Reinartz P.
Published: August 2012

Abstract. Since remote sensing provides new sensors and techniques to accumulate stereo data on urban regions, three-dimensional (3D) repre- sentation of these regions gained much interest for various applications. 3D urban region representation can e.g. be used for detailed urban monitoring, change and damage detection purposes. In order to obtain 3D representation, one of the easiest and cheapest way is to use Digital Surface Models (DSMs) which are generated from very high resolution stereo satellite images using stereovision tech- niques. Unfortunately after applying the DSM generation process, we cannot directly obtain a full 3D urban region representation. In the DSM which is generated using only one stereo image pair, generally noise, matching errors, and uncertainties on building wall loca- tions are very high. These undesirable effects prevents a DSM to provide a realistic 3D city representation. Therefore, some automatic techniques should be applied to obtain real 3D city models using DSMs as input. In order to bring a solution to the existing problems in this field, herein we propose a fully automated approach based on the usage of a novel 3D active shape model. Our experimental results on DSMs of Munich city which are obtained from different satellite (Cartosat-1, Ikonos, WorldView-2) and airborne sensors (3K camera, HRSC, and LIDAR) indicate possible usage of the algorithm to obtain 3D city representation results automatically.
RETRIEVING SURFACE SOIL MOISTURE FROM MODIS AND AMSR-E DATA: A CASE STUDY IN TAIWAN
Authors: Chen C. F. , Lin Y. J. , Chang L. Y. , Son N. T.
Published: August 2012

Abstract. Soil moisture is a key factor that controls the exchange of water between land surface evaporation and plant transpiration. Information on surface soil moisture variations in both time and spatial domains is important for numerous applications, especially agricultural and environmental monitoring. This study aimed at retrieving surface soil moisture from daily MODIS and AMSR-E (Advanced Microwave Scanning Radiometer – Earth Observing System) data. A case study was conducted in Taiwan for 2009. Data were processed using the Temperature Vegetation Dryness Index (TVDI). This index is developed based on an empirical analysis of the relationship between land surface temperature (LST) and normalized difference vegetation index (NDVI) data. The comparison between the TVDI results and the daily precipitation data collected from meteorological stations throughout the study area indicated that there were close relationships between the two datasets. The TDVI results (values range from 0 to 1) were converted to the same unit with the AMSR-E soil moisture data (i.e., g cm-3) by linear regression analysis between these two datasets. The results achieved by this analysis were soil moisture maps that had a better spatial resolution (1 km × 1 km) than the AMSE-E soil moisture data (25 km × 25 km). The soil moisture achieved by TVDI – AMSR-E regression analysis showed the comparable spatial patterns with those from the AMSR-E soil moisture data. A quantitative analysis between the soil moisture (deduced from TVDI-AMSR-E analysis) and the AMSR-E soil moisture data also reaffirmed significant correlations between the two datasets. This study has demonstrated a method of surface soil moisture retrieval from MODIS and AMSR-E data.
QUALITY ASSESSMENT OF MAPPING BUILDING TEXTURES FROM INFRARED IMAGE SEQUENCES
Authors: Hoegner L. , Iwaszczuk D. , Stilla U.
Published: August 2012

Abstract. 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.
A REFINING METHOD FOR BUILDING OBJECT AGGREGATION AND FOOTPRINT MODELLING USING MULTI-SOURCE DATA
Authors: Li Y. , Zhu L. , Shimamura H. , Tachibana K.
Published: August 2012

Abstract. Automatically detection, extraction and re-construction of 3D building modelling are difficult yet potentially high-payoff challenges for photogrammetric applications. Solution usually requires integrating various sources, including LIDAR, imagery, and digital surface models (DSM). However, highly automated and robust geometric modelling remains unsolved. We will present a 2D modelling technique which represents a building’s outline in an as-is way. It gives visually accurate corners and lines for buildings. Aerial remotely sensed imagery and a DSM are used to detect and segment building masks. A refining footprint modelling is implemented through line modelling, edge refining, and segment merging and generating. A district grouping based main orientation algorithm is proposed. This approach has the ability of successive improvement, moving from a prototype to a subtle end product. Experiments with Japanese data show that the models generated automatically fit the manual models very well.
REAL TIME SPEED ESTIMATION FROM MONOCULAR VIDEO
Authors: Temiz M. S. , Kulur S. , Dogan S.
Published: August 2012

Abstract. In this paper, detailed studies have been performed for developing a real time system to be used for surveillance of the traffic flow by using monocular video cameras to find speeds of the vehicles for secure travelling are presented. We assume that the studied road segment is planar and straight, the camera is tilted downward a bridge and the length of one line segment in the image is known. In order to estimate the speed of a moving vehicle from a video camera, rectification of video images is performed to eliminate the perspective effects and then the interest region namely the ROI is determined for tracking the vehicles. Velocity vectors of a sufficient number of reference points are identified on the image of the vehicle from each video frame. For this purpose sufficient number of points from the vehicle is selected, and these points must be accurately tracked on at least two successive video frames. In the second step, by using the displacement vectors of the tracked points and passed time, the velocity vectors of those points are computed. Computed velocity vectors are defined in the video image coordinate system and displacement vectors are measured by the means of pixel units. Then the magnitudes of the computed vectors in the image space are transformed to the object space to find the absolute values of these magnitudes. The accuracy of the estimated speed is approximately ±1 – 2 km/h. In order to solve the real time speed estimation problem, the authors have written a software system in C++ programming language. This software system has been used for all of the computations and test applications.
A STEP TOWARDS DYNAMIC SCENE ANALYSIS WITH ACTIVE MULTI-VIEW RANGE IMAGING SYSTEMS
Authors: Weinmann M. , Jutzi B.
Published: August 2012

Abstract. Obtaining an appropriate 3D description of the local environment remains a challenging task in photogrammetric research. As terrestrial laser scanners (TLSs) perform a highly accurate, but time-dependent spatial scanning of the local environment, they are only suited for capturing static scenes. In contrast, new types of active sensors provide the possibility of simultaneously capturing range and intensity information by images with a single measurement, and the high frame rate also allows for capturing dynamic scenes. However, due to the limited field of view, one observation is not sufficient to obtain a full scene coverage and therefore, typically, multiple observations are collected from different locations. This can be achieved by either placing several fixed sensors at different known locations or by using a moving sensor. In the latter case, the relation between different observations has to be estimated by using information extracted from the captured data and then, a limited field of view may lead to problems if there are too many moving objects within it. Hence, a moving sensor platform with multiple and coupled sensor devices offers the advantages of an extended field of view which results in a stabilized pose estimation, an improved registration of the recorded point clouds and an improved reconstruction of the scene. In this paper, a new experimental setup for investigating the potentials of such multi-view range imaging systems is presented which consists of a moving cable car equipped with two synchronized range imaging devices. The presented setup allows for monitoring in low altitudes and it is suitable for getting dynamic observations which might arise from moving cars or from moving pedestrians. Relying on both 3D geometry and 2D imagery, a reliable and fully automatic approach for co-registration of captured point cloud data is presented which is essential for a high quality of all subsequent tasks. The approach involves using sparse point clouds as well as a new measure derived from the respective point quality. Additionally, an extension of this approach is presented for detecting special objects and, finally, decoupling sensor and object motion in order to improve the registration process. The results indicate that the proposed setup offers new possibilities for applications such as surveillance, scene reconstruction or scene interpretation.
CO-REGISTRATION BETWEEN MULTISOURCE REMOTE-SENSING IMAGES
Authors: Wu J. , Chang C. , Tsai H.-Y. , Liu M.-C.
Published: August 2012

Abstract. Image registration is essential for geospatial information systems analysis, which usually involves integrating multitemporal and multispectral datasets from remote optical and radar sensors. An algorithm that deals with feature extraction, keypoint matching, outlier detection and image warping is experimented in this study. The methods currently available in the literature rely on techniques, such as the scale-invariant feature transform, between-edge cost minimization, normalized cross correlation, leasts-quares image matching, random sample consensus, iterated data snooping and thin-plate splines. Their basics are highlighted and encoded into a computer program. The test images are excerpts from digital files created by the multispectral SPOT-5 and Formosat-2 sensors, and by the panchromatic IKONOS and QuickBird sensors. Suburban areas, housing rooftops, the countryside and hilly plantations are studied. The co-registered images are displayed with block subimages in a criss-cross pattern. Besides the imagery, the registration accuracy is expressed by the root mean square error. Toward the end, this paper also includes a few opinions on issues that are believed to hinder a correct correspondence between diverse images.
TEXTURE ANALYSIS FOR CLASSIFICATION OF RISAT-II IMAGES
Authors: Chakraborty D. , Thakur S. , Jeyaram A. , Krishna Murthy Y. V. N. , Dadhwal V. K.
Published: August 2012

Abstract. RISAT-II or Radar Imaging satellite – II is a microwave-imaging satellite lunched by ISRO to take images of the earth during day and night as well as all weather condition. This satellite enhances the ISRO's capability for disaster management application together with forestry, agricultural, urban and oceanographic applications. The conventional pixel based classification technique cannot classify these type of images since it do not take into account the texture information of the image. This paper presents a method to classify the high-resolution RISAT-II microwave images based on texture analysis. It suppress the speckle noise from the microwave image before analysis the texture of the image since speckle is essentially a form of noise, which degrades the quality of an image; make interpretation (visual or digital) more difficult. A local adaptive median filter is developed that uses local statistics to detect the speckle noise of microwave image and to replace it with a local median value. Local Binary Pattern (LBP) operator is proposed to measure the texture around each pixel of the speckle suppressed microwave image. It considers a series of circles (2D) centered on the pixel with incremental radius values and the intersected pixels on the perimeter of the circles of radius r (where r = 1, 3 and 5) are used for measuring the LBP of the center pixel. The significance of LBP is that it measure the texture around each pixel of the image and computationally simple. ISODATA method is used to cluster the transformed LBP image. The proposed method adequately classifies RISAT-II X band microwave images without human intervention.
ON LAND SLIDE DETECTION USING TERRASAR-X OVER EARTHEN LEVEES
Authors: Mahrooghy M. , Aanstoos J. , Prasad S. , Younan N. H.
Published: August 2012

Abstract. Earthen levees have an important role to protect large areas of inhabited and cultivated land in the US from flooding. Failure of the levees can threaten the loss of life and property. One of the problems which can lead to a complete failure during a high water event is a slough slide. In this research, we are trying to detect such slides using X-band SAR data. Our methodology consists of the following four steps: 1) segmentation of the levee area from background; 2) extracting features including backscatter features and texture features; 3) training a back propagation neural network classifier using ground-truth data; and 4) testing the area of interest and validation of the results using ground truth data. A dual-polarimetric X-band image is acquired from the German TerraSAR-X satellite. Ground-truth data include the slides and healthy area. The study area is an approximately 1 km stretch of levee along the lower Mississippi River in the United States. The output classification shows the two classes of healthy and slide areas. The results show classification accuracies of approximately 67% for detecting the slide pixels.
ACCURACY TEST OF MICROSOFT KINECT FOR HUMAN MORPHOLOGIC MEASUREMENTS
Authors: Molnár B. , Toth C. K. , Detrekői A.
Published: August 2012

Abstract. The Microsoft Kinect sensor, a popular gaming console, is widely used in a large number of applications, including close-range 3D measurements. This low-end device is rather inexpensive compared to similar active imaging systems. The Kinect sensors include an RGB camera, an IR projector, an IR camera and an audio unit. The human morphologic measurements require high accuracy with fast data acquisition rate. To achieve the highest accuracy, the depth sensor and the RGB camera should be calibrated and co-registered to achieve high-quality 3D point cloud as well as optical imagery. Since this is a low-end sensor, developed for different purpose, the accuracy could be critical for 3D measurement-based applications. Therefore, two types of accuracy test are performed: (1) for describing the absolute accuracy, the ranging accuracy of the device in the range of 0.4 to 15 m should be estimated, and (2) the relative accuracy of points depending on the range should be characterized. For the accuracy investigation, a test field was created with two spheres, while the relative accuracy is described by sphere fitting performance and the distance estimation between the sphere center points. Some other factors can be also considered, such as the angle of incidence or the material used in these tests. The non-ambiguity range of the sensor is from 0.3 to 4 m, but, based on our experiences, it can be extended up to 20 m. Obviously, this methodology raises some accuracy issues which make accuracy testing really important.
3D CAPABILITIES OF PLEIADES SATELLITE
Authors: Bernard M. , Decluseau D. , Gabet L. , Nonin P.
Published: August 2012

Abstract. End of 2011 a new optical satellite, called Pléiades, was launched by the French space agency (CNES). It provides 20 km x 20 km images at 0.5 meters. This agile acquisition system is able to relocate very rapidly and scan the earth in any direction. The agility of the system offers the ability to acquire multi viewing angle images of the same area during the same orbit. This ability to capture, from a single stereoscopic pair, to a sequence of 25 images, allows enhancing the quality and the completeness of automatically extracted 3D maps. The aim of the study is to validate and quantify the capacity of the Pléiades system to perform 3D mapping. The analysis explores the advantages in terms of quality and automatism to use more than 2 stereoscopic images. In the last 10 years, automatic 3D processing of digital images became more and more popular and efficient. Thanks to aerial images with very large overlap and very high resolution satellite images, new methodologies and algorithms have been implemented to improve the quality and accuracy of automatic 3D processing. We propose to experiment the same type of approaches using Pléiades images to produce digital elevation models (DEM). A focus is made on analysing the 3D processing using video like (multi viewing) acquisitions. Different reference sites with very accurate 3D control points are used to quantify the quality of the Pléiades DEM. Different acquisition modes are explored from a single stereo pair to a sequence of 17 images.
PLÉIADES: RESPONSIVENESS, FLEXIBILITY, REACTIVITY
Authors: Gabriel-Robez C. , Lees R. , Bernard M.
Published: August 2012

Abstract. By the end of 2011, Astrium GEO-Information Services launched Pléiades 1, the first of two identical optical imaging satellites that will be operated on a phased orbit. This satellite system, designed by the French Space Agency, CNES, based upon French Defense specifications, will provide 50-cm products in record time. The overall aim of this paper is to describe the benefits of the innovative features of Pléiades 1 and its operations, so as to assess their combined potential in emergency situations, crisis recovery, regular monitoring or large area mapping. Specific care will be brought to describe the reactivity enabled by the system. Based on real-life examples, the paper will lead the analysis on the two main components of the system. On the one hand, the space segment will be presented through the following characteristics: revisit capacity, agility, acquisition capacity and acquisition scenarios (target, single-pass mosaics, stereo, tristereo, linear monitoring, persistent surveillance). On the other hand, the flexibility of the ground segment will be assessed. The benefits of multiple tasking plans per day, direct tasking capacity, automated processing and on-line ordering and delivering will be illustrated, tested and qualified for applications requiring a high level of responsiveness and reactivity. The presentation will end with a summary of the benefits of the space segment features and the flexibility of the ground segment, fine-tuned to answer both military and civilian / commercial needs. The analysis will be extended in the perspective of the second Pléiades' launch, highlighting the advantages of having two satellites operating on a phased orbit, affording a daily revisit anywhere on Earth, with very high resolution.
IMAGE-BASED NAVIGATION OF FOREST HARVESTERS
Authors: Schulze M.
Published: August 2012

Abstract. The focus of this paper the use of multi-image matching techniques in forestry applications. Background of the study is the problem of navigating heavy harvesters through skidder trails on their way to harvesting individual trees. Maneuvering these heavy vehicles over unprotected forest ground leads to irreversible soil compression and degradation effects. Therefore, harvester operators strive to navigate in a way that exactly the same (already compressed) path is used when they enter a skidder trail for a second time. For this task, vehicle navigation on a decimeter accuracy level is required. Data of existing techniques, such as GPS, IMU and/or odometry are error prone, because of difficulties like fluctuating signal strength of satellites caused by dense plant canopy, drift of IMU without update, and slippery, rough ground for wheel decoding. A camera, as a passive sensor, may avoid these problems, as it is largely independent to those outer influences.
SIFT FOR DENSE POINT CLOUD MATCHING AND AERO TRIANGULATION
Authors: Tsay J. R. , Lee M. S.
Published: August 2012

Abstract. This paper presents a new method for dense point cloud matching and aero triangulation based on the well-known scale invariant feature transform (SIFT) technique. The modern digital cameras can take high resolution aerial images with high end lap between contiguous images in a strip and, if needed, also with high side lap between images on neighboring strips. Therefore, automation on image matching for generation of high density of 3D object points becomes applicable. A new method is thus developed to perform the processing. Moreover, it can do an aero triangulation and automatic tie point measurement without the need on the input data such as block and strip data for providing image overlap information. In order to increase the effectiveness of the method for simultaneously processing a large number of aerial images with large image format in a block area, both schemes of Quality Filtering (QF) and Affine Transformation Prediction (AFTP) are proposed for automatic tie point extraction and measurement with a better and satisfactory efficiency. Tests are done by using aerial images taken with the RMK DX camera in Taiwan. Also, high precision ground check points are adopted to evaluate the quality of the results. They show that a high density of 3D object points are extracted and determined. Furthermore, the automatic tie point selection and measurement is done efficiently even under the circumstance that no priori-knowledge on image overlap is available. Also, ground check points show that the accuracy of photo coordinates is 0.21 pixels, namely it reaches a subpixel level.
KNOWLEDGE-BASED OBJECT DETECTION IN LASER SCANNING POINT CLOUDS
Authors: Boochs F. , Karmacharya A. , Marbs A.
Published: August 2012

Abstract. Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This “understanding” enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists’ knowledge of the scene and algorithmic processing.
SATELLITE 'CANOPUS-V' IMAGE PROCESSING TECHNOLOGY DEVELOPMENT FOR CARTOGRAPHY PURPOSES BASED ON PRELAUNCH SIMULATION
Authors: Nekrasov V. V. , Makusheva E.
Published: August 2012

Abstract. “Canopus-V” satellite payload consists of two cameras – one of them panchromatic with 2.1 m GSD, another multispectral with 10 m GSD. Navigation system accuracy provides georeference accuracy about 70-80 m without using of control points. The peculiarities of high-resolution panchromatic camera built with micro-frames technology requires to design surveying technology processing for obtaining continuous coverage. Automatic technology of searching tie points in overlapped areas of micro-frames was developed by authors. Block adjustment is done automatic. Rational polynomial coefficients (RPC) calculates after block adjustment for using in standard photogrammetric software. For “Canopus-V” sensors was developed mathematic model and software package for RPC calculating. Searching for tie points use combination of feature and area matching algorithms in overlapped areas of micro-frames. Process of satellite sensors shooting was simulated with use of calibration data (orthophoto, digital elevation model – DEM, control points for test area used as check points). Subpixel accuracy was achieved for block adjustment. Accuracy for resulting orthophoto was checked with control points and was 35-55 m. Using of two control points for block increases resulting orthophoto accuracy two times. Simulation results and accuracy estimation shows that “Canopus-V” panchromatic camera data can be recommended to modify maps for the scales 1:25000. “Canopus-V” multispectral camera data can be used to modify maps for the scales 1:100000.
ROAD EXTRACTION FROM HIGH RESOLUTION SATELLITE IMAGES
Authors: Özkaya M.
Published: August 2012

Abstract. Roads are significant objects of an infrastructure and the extraction of roads from aerial and satellite images are important for different applications such as automated map generation and change detection. Roads are also important to detect other structures such as buildings and urban areas. In this paper, the road extraction approach is based on Active Contour Models for 1-meter resolution gray level images. Active Contour Models contains Snake Approach. During applications, the road structure was separated as salient-roads, non-salient roads and crossings and extraction of these is provided by using Ribbon Snake and Ziplock Snake methods. These methods are derived from traditional snake model. Finally, various experimental results were presented. Ribbon and Ziplock Snake methods were compared for both salient and non-salient roads. Also these methods were used to extract roads in an image. While Ribbon snake is described for extraction of salient roads in an image, Ziplock snake is applied for extraction of non-salient roads. Beside these, some constant variables in literature were redefined and expressed in a formula as depending on snake approach and a new approach for extraction of crossroads were described and tried.
ACCURACY IMPROVEMENT OF DEM FOR GENERATING ORTHOPHOTO BY REVERSE PROJECTION METHOD
Authors: Sugiyama F. , Chikatsu H.
Published: August 2012

Abstract. The generation of orthophotos using digital aerial photography is performed for the maintenance of spatial information data for wide areas at the mid-scale.For orthophoto generation, a digital elevation model (DEM) based on stereo matching methods is widely used, the accuracy of which should be effectively improved by removing mismatched points created during the stereo matching process for efficient orthophoto generation.With this motive in mind, a new method called the “Reverse-Projection Method” is proposed to remove mismatched points from DEM generation. The most remarkable points of this method are its ability to detect mismatched points and improve the accuracy of a DEM using only stereo models on the previous and following strips and restricting the higherresolution stage in the coarse-to-fine approach using the Digital Terrain Model as a reference. The effectiveness of the method is discussed in this paper.
AN INNOVATION APPROACH FOR DEVELOPING A 3D MODEL BY REGISTERING A MONO IMAGE ON A DTM
Authors: Homainejad A. S.
Published: August 2012

Abstract. This paper is reflecting a study on developing and reconstructing a 3D model from registering an aerial image on a point clouds or a DTM. The point clouds has been chosen as the main data for reconstructing a 3D model. For achieving the aspects of the study, all objects were individually detected and extracted from the point clouds and captured in a particular layer in a CAD environment. Then each object will be converted to a raster format and will be registered on the image. This process is called the reverse registration in this study. Since the object segmentation and detection from a digital image is a complex process, the reverse registration is implemented in order to assist the process of the object detection from the image. This paper will discuss two methods of object detection from point clouds for the reverse registration. These methods were proposed and implemented for this study. Also, the paper will discuss the reverse registration and how this method improves the process of the object detection and extraction from the image. Discussion of reconstructing a 3D model from registering the digital image on a DTM or DSM (both of which developed from the point clouds data) is another goal of this paper.
OPENWEBGLOBE – AN OPEN SOURCE SDK FOR CREATING LARGE-SCALE VIRTUAL GLOBES ON A WEBGL BASIS
Authors: Loesch B. , Christen M. , Nebiker S.
Published: August 2012

Abstract. This paper introduces the OpenWebGlobe project (
TRUE 3D IMAGES AND THEIR APPLICATIONS
Authors: Wang Z. ,   zheng.wang@hzgeospace.
Published: August 2012

Abstract. A true 3D image is a geo-referenced image. Besides having its radiometric information, it also has true 3Dground coordinates XYZ for every pixels of it. For a true 3D image, especially a true 3D oblique image, it has true 3D coordinates not only for building roofs and/or open grounds, but also for all other visible objects on the ground, such as visible building walls/windows and even trees. The true 3D image breaks the 2D barrier of the traditional orthophotos by introducing the third dimension (elevation) into the image. From a true 3D image, for example, people will not only be able to read a building’s location (XY), but also its height (Z). true 3D images will fundamentally change, if not revolutionize, the way people display, look, extract, use, and represent the geospatial information from imagery. In many areas, true 3D images can make profound impacts on the ways of how geospatial information is represented, how true 3D ground modeling is performed, and how the real world scenes are presented. This paper first gives a definition and description of a true 3D image and followed by a brief review of what key advancements of geospatial technologies have made the creation of true 3D images possible. Next, the paper introduces what a true 3D image is made of. Then, the paper discusses some possible contributions and impacts the true 3D images can make to geospatial information fields. At the end, the paper presents a list of the benefits of having and using true 3D images and the applications of true 3D images in a couple of 3D city modeling projects.
EXTRACTING PRECISE AND AFFORDABLE DEMS DESPITE OF THE CLOUDS. AJAX: THE JOINING OF RADAR AND OPTICAL STRENGTHS
Authors: Cunin L. , Nonin P. , Janoth J. , Bernard M.
Published: August 2012

Abstract. On the one hand, onboard SPOT 5, the HRS instrument systematically collects stereopairs around the Globe since 2002. Each stereopair can encompass an area up to 600 km x 120 km within a single pass (i.e. 72 000 km² stereoscopic strips). Covering now more than 120 millions sq.km of the Earth landmasses, SPOT 5 stereoscopic imagery has become one of main satellite data sources for accurate DEM extraction, at least where the cloud coverage leaves a chance to do so ! On the other hand, the TerraSAR-X satellite, launched in June 2007, is able to collect radar data through the clouds in several modes. An approach to extract height information by radargrammetry was developed, and the commercial distribution of Digital Elevation Models based on TerraSAR-X StripMap and SpotLight Modes (resp. 3m and 1m resolution) has started in 2010. To improve the overall height accuracy of the DEM, acquisitions from both orbit directions are utilised, each point on the ground being thus imaged at least 4 times by TerraSAR-X. Since 2002, Spot Image and French National Cartographic Institute (IGN) are building a worldwide database called Elevation30/Reference3D™, which includes a Digital Elevation Model at 1-arc-second resolution (DTED level 2) extracted from HRS stereopairs. To answer the wide demand of precise DEMs over Tropical and Northern areas, frequently covered by clouds, a study was performed to integrate StripMap radargrammetric TerraSAR-X data into the Reference3D process, and two prototype products were issued, over Colombia and Congo areas. During this experiment, efforts have been made to stick to technical steps that could be integrated within a standardized production process, in order to keep offering affordable prices while maintaining a high standard of horizontal and vertical accuracy. The DEMs extracted from TerraSAR-X and HRS proved extremely consistent with each other, showing a mean difference of 0.80m. This allows to propose a unified Elevation30 product to the users, with a guaranteed accuracy materialized into the product through a dedicated vertical Accuracy Commitment Mask.
REMOVAL OF TREE OFFSETS FROM SRTM AND OTHER DIGITAL SURFACE MODELS
Authors: Gallant J. C. , Read A. M. , Dowling T. I.
Published: August 2012

Abstract. The recently completed 1 second Digital Elevation Models (DEMs) for Australia are based on the 1 second Shuttle Radar Topographic Mission (SRTM) elevation data. The SRTM data was corrected by removing voids, striping, tree offsets and random noise and finally by integrating mapped drainage lines. This paper describes the removal of the tree offsets, which was a crucial step in the production of a credible bare-earth elevation model and was one of the most technically challenging aspects of the project, and the possible application of the methods to other digital surface model (DSM) sources. Methods for the removal of tree offsets rely on maps of tree presence/absence from sources such as remotely-sensed imagery, and the height offsets are computed from the DEM at the boundaries of tree patches. Tree offsets over most of Australia were successfully removed, but were underestimated in areas of extensive forest cover and poorly estimated where the mapping of tree patches did not match the patterns of offsets in the SRTM elevations. The tree offset removal methods could be applied to the near-global SRTM DSM to produce a near-global bare-earth product, provided that a suitable map of tree presence or density can be compiled from satellite remote sensing and other sources. The process could be improved by using supplementary tree-height information from ICESat or other sources. High resolution global DEMs other than SRTM are becoming available, notably ASTER GDEM and TANDEM-X. Both those products are subject to offsets due to vegetation in the same way as SRTM. The tree offset removal methods developed for SRTM could be adapted to the characteristics of these and other DSMs to provide a largely automated processing system to derive bareearth DEMs from new sources.
THE USE OF EXISTING GLOBAL ELEVATION DATASET FOR ABSOLUTE ORIENTATION OF HIGH RESOLUTION IMAGE WITHOUT GCPS
Authors: Jeong J. , Kim T.
Published: August 2012

Abstract. For precise mapping using high resolution satellite images, various ways to eliminate the need of ground control points have been proposed. DEM matching, a technique to match two different surfaces by adjusting their position and attitude, is also one way of them. Our previous study demonstrated that DEM matching can be used for bias compensation of rigorous pushbroom sensor models. In this paper, we exploit the DEM matching technique further using existing global elevation dataset for absolute orientation of high resolution satellite image without ground control points. In particular, we investigated how the existing global DEM available worldwide can substitute ground control points when DEM matching is applied to linear pushbroom imagery. We used Spot-5 HRG with 2.5m ground sampling distance(GSD) as high resolution satellite images and used SRTM-derived DEMs(DTEDs) with gird spacing of 30m and 90m as existing elevation dataset. We firstly established relative orientation and generated a relative DEM without use of ground control points. DEM matching was then applied between the relative DEM and the DTED. We applied DEM matching based on linear pushbroom images. Through DEM matching, accuracy of about 2 GSD or better could be achieved with in the horizontal and in the vertical direction, respectively. We confirmed automatic DEM matching processing can be accomplished for absolute orientation of pushbroom image and as results, absolute DEM can be achieved from relative DEM. We tested the applicability of 90m existing global dataset for DEM matching. Our experimental results showed the potential of existing DEM for precise mapping without ground control points. This is very encouraging in terms of applicability of the existing global elevation data. This paper will contribute to understanding of DEM matching for linear pushbroom images and of solution to precise mapping without ground control points.