Science.gov

Sample records for aerial image model

  1. Aerial Image Systems

    NASA Astrophysics Data System (ADS)

    Clapp, Robert E.

    1987-09-01

    Aerial images produce the best stereoscopic images of the viewed world. Despite the fact that every optic in existence produces an aerial image, few persons are aware of their existence and possible uses. Constant reference to the eye and other optical systems have produced a psychosis of design that only considers "focal planes" in the design and analysis of optical systems. All objects in the field of view of the optical device are imaged by the device as an aerial image. Use of aerial images in vision and visual display systems can provide a true stereoscopic representation of the viewed world. This paper discusses aerial image systems - their applications and designs and presents designs and design concepts that utilize aerial images to obtain superior visual displays, particularly with application to visual simulation.

  2. Detection of object motion regions in aerial image pairs with a multilayer markovian model.

    PubMed

    Benedek, Csaba; Szirányi, Tamás; Kato, Zoltan; Zerubia, Josiane

    2009-10-01

    We propose a new Bayesian method for detecting the regions of object displacements in aerial image pairs. We use a robust but coarse 2-D image registration algorithm. Our main challenge is to eliminate the registration errors from the extracted change map. We introduce a three-layer Markov random field (L(3)MRF) model which integrates information from two different features, and ensures connected homogenous regions in the segmented images. Validation is given on real aerial photos.

  3. A featureless approach to 3D polyhedral building modeling from aerial images.

    PubMed

    Hammoudi, Karim; Dornaika, Fadi

    2011-01-01

    This paper presents a model-based approach for reconstructing 3D polyhedral building models from aerial images. The proposed approach exploits some geometric and photometric properties resulting from the perspective projection of planar structures. Data are provided by calibrated aerial images. The novelty of the approach lies in its featurelessness and in its use of direct optimization based on image rawbrightness. The proposed framework avoids feature extraction and matching. The 3D polyhedral model is directly estimated by optimizing an objective function that combines an image-based dissimilarity measure and a gradient score over several aerial images. The optimization process is carried out by the Differential Evolution algorithm. The proposed approach is intended to provide more accurate 3D reconstruction than feature-based approaches. Fast 3D model rectification and updating can take advantage of the proposed method. Several results and evaluations of performance from real and synthetic images show the feasibility and robustness of the proposed approach.

  4. A Featureless Approach to 3D Polyhedral Building Modeling from Aerial Images

    PubMed Central

    Hammoudi, Karim; Dornaika, Fadi

    2011-01-01

    This paper presents a model-based approach for reconstructing 3D polyhedral building models from aerial images. The proposed approach exploits some geometric and photometric properties resulting from the perspective projection of planar structures. Data are provided by calibrated aerial images. The novelty of the approach lies in its featurelessness and in its use of direct optimization based on image rawbrightness. The proposed framework avoids feature extraction and matching. The 3D polyhedral model is directly estimated by optimizing an objective function that combines an image-based dissimilarity measure and a gradient score over several aerial images. The optimization process is carried out by the Differential Evolution algorithm. The proposed approach is intended to provide more accurate 3D reconstruction than feature-based approaches. Fast 3D model rectification and updating can take advantage of the proposed method. Several results and evaluations of performance from real and synthetic images show the feasibility and robustness of the proposed approach. PMID:22346575

  5. Moving object detection using dynamic motion modelling from UAV aerial images.

    PubMed

    Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

    2014-01-01

    Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

  6. Model-based neural network algorithm for coffee ripeness prediction using Helios UAV aerial images

    NASA Astrophysics Data System (ADS)

    Furfaro, R.; Ganapol, B. D.; Johnson, L. F.; Herwitz, S.

    2005-10-01

    Over the past few years, NASA has had a great interest in exploring the feasibility of using Unmanned Aerial Vehicles (UAVs), equipped with multi-spectral imaging systems, as long-duration platform for crop monitoring. To address the problem of predicting the ripeness level of the Kauai coffee plantation field using UAV aerial images, we proposed a neural network algorithm based on a nested Leaf-Canopy radiative transport Model (LCM2). A model-based, multi-layer neural network using backpropagation has been designed and trained to learn the functional relationship between the airborne reflectance and the percentage of ripe, over-ripe and under-ripe cherries present in the field. LCM2 was used to generate samples of the desired map. Post-processing analysis and tests on synthetic coffee field data showed that the network has accurately learn the map. A new Domain Projection Technique (DPT) was developed to deal with situations where the measured reflectance fell outside the training set. DPT projected the reflectance into the domain forcing the network to provide a physical solution. Tests were conducted to estimate the error bound. The synergistic combination of neural network algorithms and DPT lays at the core of a more complex algorithm designed to process UAV images. The application of the algorithm to real airborne images shows predictions consistent with post-harvesting data and highlights the potential of the overall methodology.

  7. Detection of linear features in aerial images

    NASA Astrophysics Data System (ADS)

    Gao, Rui

    Over the past decades, considerable progress had been made to develop automatic image interpretation tools in remote sensing. However, there is still a gap between the results and the requirements for accuracy and robustness. Noisy aerial image interpretation, especially for low resolution images, is still difficult. In this thesis, we propose a fully automatic system for linear feature detection in aerial images. We present how the system works on the application of extraction and reconstruction of road and pipeline networks. The work in this thesis is divided by three parts: line detection, feature interpretation, and feature tracking. An improved Hough transform based on orientation information is introduced for the line detection. We explore the Markov random field model and Bayesian filtering for feature interpretation and tracking. Experimental results show that our proposed system is robust and effective to deal with low resolution aerial images.

  8. Aerial Photographs and Satellite Images

    USGS Publications Warehouse

    ,

    1997-01-01

    Photographs and other images of the Earth taken from the air and from space show a great deal about the planet's landforms, vegetation, and resources. Aerial and satellite images, known as remotely sensed images, permit accurate mapping of land cover and make landscape features understandable on regional, continental, and even global scales. Transient phenomena, such as seasonal vegetation vigor and contaminant discharges, can be studied by comparing images acquired at different times. The U.S. Geological Survey (USGS), which began using aerial photographs for mapping in the 1930's, archives photographs from its mapping projects and from those of some other Federal agencies. In addition, many images from such space programs as Landsat, begun in 1972, are held by the USGS. Most satellite scenes can be obtained only in digital form for use in computer-based image processing and geographic information systems, but in some cases are also available as photographic products.

  9. Aerial Video Imaging

    NASA Technical Reports Server (NTRS)

    1991-01-01

    When Michael Henry wanted to start an aerial video service, he turned to Johnson Space Center for assistance. Two NASA engineers - one had designed and developed TV systems in Apollo, Skylab, Apollo- Soyuz and Space Shuttle programs - designed a wing-mounted fiberglass camera pod. Camera head and angles are adjustable, and the pod is shaped to reduce vibration. The controls are located so a solo pilot can operate the system. A microprocessor displays latitude, longitude, and bearing, and a GPS receiver provides position data for possible legal references. The service has been successfully utilized by railroads, oil companies, real estate companies, etc.

  10. The Need of Nested Grids for Aerial and Satellite Images and Digital Elevation Models

    NASA Astrophysics Data System (ADS)

    Villa, G.; Mas, S.; Fernández-Villarino, X.; Martínez-Luceño, J.; Ojeda, J. C.; Pérez-Martín, B.; Tejeiro, J. A.; García-González, C.; López-Romero, E.; Soteres, C.

    2016-06-01

    Usual workflows for production, archiving, dissemination and use of Earth observation images (both aerial and from remote sensing satellites) pose big interoperability problems, as for example: non-alignment of pixels at the different levels of the pyramids that makes it impossible to overlay, compare and mosaic different orthoimages, without resampling them and the need to apply multiple resamplings and compression-decompression cycles. These problems cause great inefficiencies in production, dissemination through web services and processing in "Big Data" environments. Most of them can be avoided, or at least greatly reduced, with the use of a common "nested grid" for mutiresolution production, archiving, dissemination and exploitation of orthoimagery, digital elevation models and other raster data. "Nested grids" are space allocation schemas that organize image footprints, pixel sizes and pixel positions at all pyramid levels, in order to achieve coherent and consistent multiresolution coverage of a whole working area. A "nested grid" must be complemented by an appropriate "tiling schema", ideally based on the "quad-tree" concept. In the last years a "de facto standard" grid and Tiling Schema has emerged and has been adopted by virtually all major geospatial data providers. It has also been adopted by OGC in its "WMTS Simple Profile" standard. In this paper we explain how the adequate use of this tiling schema as common nested grid for orthoimagery, DEMs and other types of raster data constitutes the most practical solution to most of the interoperability problems of these types of data.

  11. Aerial Images from AN Uav System: 3d Modeling and Tree Species Classification in a Park Area

    NASA Astrophysics Data System (ADS)

    Gini, R.; Passoni, D.; Pinto, L.; Sona, G.

    2012-07-01

    The use of aerial imagery acquired by Unmanned Aerial Vehicles (UAVs) is scheduled within the FoGLIE project (Fruition of Goods Landscape in Interactive Environment): it starts from the need to enhance the natural, artistic and cultural heritage, to produce a better usability of it by employing audiovisual movable systems of 3D reconstruction and to improve monitoring procedures, by using new media for integrating the fruition phase with the preservation ones. The pilot project focus on a test area, Parco Adda Nord, which encloses various goods' types (small buildings, agricultural fields and different tree species and bushes). Multispectral high resolution images were taken by two digital compact cameras: a Pentax Optio A40 for RGB photos and a Sigma DP1 modified to acquire the NIR band. Then, some tests were performed in order to analyze the UAV images' quality with both photogrammetric and photo-interpretation purposes, to validate the vector-sensor system, the image block geometry and to study the feasibility of tree species classification. Many pre-signalized Control Points were surveyed through GPS to allow accuracy analysis. Aerial Triangulations (ATs) were carried out with photogrammetric commercial software, Leica Photogrammetry Suite (LPS) and PhotoModeler, with manual or automatic selection of Tie Points, to pick out pros and cons of each package in managing non conventional aerial imagery as well as the differences in the modeling approach. Further analysis were done on the differences between the EO parameters and the corresponding data coming from the on board UAV navigation system.

  12. Orientation Strategies for Aerial Oblique Images

    NASA Astrophysics Data System (ADS)

    Wiedemann, A.; Moré, J.

    2012-07-01

    Oblique aerial images become more and more distributed to fill the gap between vertical aerial images and mobile mapping systems. Different systems are on the market. For some applications, like texture mapping, precise orientation data are required. One point is the stable interior orientation, which can be achieved by stable camera systems, the other a precise exterior orientation. A sufficient exterior orientation can be achieved by a large effort in direct sensor orientation, whereas minor errors in the angles have a larger effect than in vertical imagery. The more appropriate approach is by determine the precise orientation parameters by photogrammetric methods using an adapted aerial triangulation. Due to the different points of view towards the object the traditional aerotriangulation matching tools fail, as they produce a bunch of blunders and require a lot of manual work to achieve a sufficient solution. In this paper some approaches are discussed and results are presented for the most promising approaches. We describe a single step approach with an aerotriangulation using all available images; a two step approach with an aerotriangulation only of the vertical images plus a mathematical transformation of the oblique images using the oblique cameras excentricity; and finally the extended functional model for a bundle block adjustment considering the mechanical connection between vertical and oblique images. Beside accuracy also other aspects like efficiency and required manual work have to be considered.

  13. Matching Aerial Images to 3d Building Models Based on Context-Based Geometric Hashing

    NASA Astrophysics Data System (ADS)

    Jung, J.; Bang, K.; Sohn, G.; Armenakis, C.

    2016-06-01

    In this paper, a new model-to-image framework to automatically align a single airborne image with existing 3D building models using geometric hashing is proposed. As a prerequisite process for various applications such as data fusion, object tracking, change detection and texture mapping, the proposed registration method is used for determining accurate exterior orientation parameters (EOPs) of a single image. This model-to-image matching process consists of three steps: 1) feature extraction, 2) similarity measure and matching, and 3) adjustment of EOPs of a single image. For feature extraction, we proposed two types of matching cues, edged corner points representing the saliency of building corner points with associated edges and contextual relations among the edged corner points within an individual roof. These matching features are extracted from both 3D building and a single airborne image. A set of matched corners are found with given proximity measure through geometric hashing and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on co-linearity equations. The result shows that acceptable accuracy of single image's EOP can be achievable by the proposed registration approach as an alternative to labour-intensive manual registration process.

  14. Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing.

    PubMed

    Jung, Jaewook; Sohn, Gunho; Bang, Kiin; Wichmann, Andreas; Armenakis, Costas; Kada, Martin

    2016-06-22

    A city is a dynamic entity, which environment is continuously changing over time. Accordingly, its virtual city models also need to be regularly updated to support accurate model-based decisions for various applications, including urban planning, emergency response and autonomous navigation. A concept of continuous city modeling is to progressively reconstruct city models by accommodating their changes recognized in spatio-temporal domain, while preserving unchanged structures. A first critical step for continuous city modeling is to coherently register remotely sensed data taken at different epochs with existing building models. This paper presents a new model-to-image registration method using a context-based geometric hashing (CGH) method to align a single image with existing 3D building models. This model-to-image registration process consists of three steps: (1) feature extraction; (2) similarity measure; and matching, and (3) estimating exterior orientation parameters (EOPs) of a single image. For feature extraction, we propose two types of matching cues: edged corner features representing the saliency of building corner points with associated edges, and contextual relations among the edged corner features within an individual roof. A set of matched corners are found with given proximity measure through geometric hashing, and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on collinearity equations. The result shows that acceptable accuracy of EOPs of a single image can be achievable using the proposed registration approach as an alternative to a labor-intensive manual registration process.

  15. Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing

    PubMed Central

    Jung, Jaewook; Sohn, Gunho; Bang, Kiin; Wichmann, Andreas; Armenakis, Costas; Kada, Martin

    2016-01-01

    A city is a dynamic entity, which environment is continuously changing over time. Accordingly, its virtual city models also need to be regularly updated to support accurate model-based decisions for various applications, including urban planning, emergency response and autonomous navigation. A concept of continuous city modeling is to progressively reconstruct city models by accommodating their changes recognized in spatio-temporal domain, while preserving unchanged structures. A first critical step for continuous city modeling is to coherently register remotely sensed data taken at different epochs with existing building models. This paper presents a new model-to-image registration method using a context-based geometric hashing (CGH) method to align a single image with existing 3D building models. This model-to-image registration process consists of three steps: (1) feature extraction; (2) similarity measure; and matching, and (3) estimating exterior orientation parameters (EOPs) of a single image. For feature extraction, we propose two types of matching cues: edged corner features representing the saliency of building corner points with associated edges, and contextual relations among the edged corner features within an individual roof. A set of matched corners are found with given proximity measure through geometric hashing, and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on collinearity equations. The result shows that acceptable accuracy of EOPs of a single image can be achievable using the proposed registration approach as an alternative to a labor-intensive manual registration process. PMID:27338410

  16. An Improved Snake Model for Refinement of Lidar-Derived Building Roof Contours Using Aerial Images

    NASA Astrophysics Data System (ADS)

    Chen, Qi; Wang, Shugen; Liu, Xiuguo

    2016-06-01

    Building roof contours are considered as very important geometric data, which have been widely applied in many fields, including but not limited to urban planning, land investigation, change detection and military reconnaissance. Currently, the demand on building contours at a finer scale (especially in urban areas) has been raised in a growing number of studies such as urban environment quality assessment, urban sprawl monitoring and urban air pollution modelling. LiDAR is known as an effective means of acquiring 3D roof points with high elevation accuracy. However, the precision of the building contour obtained from LiDAR data is restricted by its relatively low scanning resolution. With the use of the texture information from high-resolution imagery, the precision can be improved. In this study, an improved snake model is proposed to refine the initial building contours extracted from LiDAR. First, an improved snake model is constructed with the constraints of the deviation angle, image gradient, and area. Then, the nodes of the contour are moved in a certain range to find the best optimized result using greedy algorithm. Considering both precision and efficiency, the candidate shift positions of the contour nodes are constrained, and the searching strategy for the candidate nodes is explicitly designed. The experiments on three datasets indicate that the proposed method for building contour refinement is effective and feasible. The average quality index is improved from 91.66% to 93.34%. The statistics of the evaluation results for every single building demonstrated that 77.0% of the total number of contours is updated with higher quality index.

  17. Application of Technical Measures and Software in Constructing Photorealistic 3D Models of Historical Building Using Ground-Based and Aerial (UAV) Digital Images

    NASA Astrophysics Data System (ADS)

    Zarnowski, Aleksander; Banaszek, Anna; Banaszek, Sebastian

    2015-12-01

    Preparing digital documentation of historical buildings is a form of protecting cultural heritage. Recently there have been several intensive studies using non-metric digital images to construct realistic 3D models of historical buildings. Increasingly often, non-metric digital images are obtained with unmanned aerial vehicles (UAV). Technologies and methods of UAV flights are quite different from traditional photogrammetric approaches. The lack of technical guidelines for using drones inhibits the process of implementing new methods of data acquisition. This paper presents the results of experiments in the use of digital images in the construction of photo-realistic 3D model of a historical building (Raphaelsohns' Sawmill in Olsztyn). The aim of the study at the first stage was to determine the meteorological and technical conditions for the acquisition of aerial and ground-based photographs. At the next stage, the technology of 3D modelling was developed using only ground-based or only aerial non-metric digital images. At the last stage of the study, an experiment was conducted to assess the possibility of 3D modelling with the comprehensive use of aerial (UAV) and ground-based digital photographs in terms of their labour intensity and precision of development. Data integration and automatic photo-realistic 3D construction of the models was done with Pix4Dmapper and Agisoft PhotoScan software Analyses have shown that when certain parameters established in an experiment are kept, the process of developing the stock-taking documentation for a historical building moves from the standards of analogue to digital technology with considerably reduced cost.

  18. System for interactive management of aerial imaging campaigns

    NASA Astrophysics Data System (ADS)

    Wypych, Tom; Kuester, Falko

    We present a system to enable real time management of interchangeable imaging platforms aboard commodity unmanned aerial vehicles (UAVs) to improve interactivity during aerial imaging campaigns. We argue that this improvement in interactivity enables powerful immediate-mode inspection by the ground operator, and implements a more intuitive, flexible, and ultimately useful control interface to aerial imaging systems.

  19. Aerial photographs and satellite images

    USGS Publications Warehouse

    ,

    1995-01-01

    Because photographs and images taken from the air or from space are acquired without direct contact with the ground, they are referred to as remotely sensed images. The U.S. Geological Survey (USGS) has used remote sensing from the early years of the 20th century to support earth science studies and for mapping purposes.

  20. Investigating an Aerial Image First

    ERIC Educational Resources Information Center

    Wyrembeck, Edward P.; Elmer, Jeffrey S.

    2006-01-01

    Most introductory optics lab activities begin with students locating the real image formed by a converging lens. The method is simple and straightforward--students move a screen back and forth until the real image is in sharp focus on the screen. Students then draw a simple ray diagram to explain the observation using only two or three special…

  1. Large-Scale Aerial Image Categorization Using a Multitask Topological Codebook.

    PubMed

    Zhang, Luming; Wang, Meng; Hong, Richang; Yin, Bao-Cai; Li, Xuelong

    2016-02-01

    Fast and accurately categorizing the millions of aerial images on Google Maps is a useful technique in pattern recognition. Existing methods cannot handle this task successfully due to two reasons: 1) the aerial images' topologies are the key feature to distinguish their categories, but they cannot be effectively encoded by a conventional visual codebook and 2) it is challenging to build a realtime image categorization system, as some geo-aware Apps update over 20 aerial images per second. To solve these problems, we propose an efficient aerial image categorization algorithm. It focuses on learning a discriminative topological codebook of aerial images under a multitask learning framework. The pipeline can be summarized as follows. We first construct a region adjacency graph (RAG) that describes the topology of each aerial image. Naturally, aerial image categorization can be formulated as RAG-to-RAG matching. According to graph theory, RAG-to-RAG matching is conducted by enumeratively comparing all their respective graphlets (i.e., small subgraphs). To alleviate the high time consumption, we propose to learn a codebook containing topologies jointly discriminative to multiple categories. The learned topological codebook guides the extraction of the discriminative graphlets. Finally, these graphlets are integrated into an AdaBoost model for predicting aerial image categories. Experimental results show that our approach is competitive to several existing recognition models. Furthermore, over 24 aerial images are processed per second, demonstrating that our approach is ready for real-world applications.

  2. An improved dehazing algorithm of aerial high-definition image

    NASA Astrophysics Data System (ADS)

    Jiang, Wentao; Ji, Ming; Huang, Xiying; Wang, Chao; Yang, Yizhou; Li, Tao; Wang, Jiaoying; Zhang, Ying

    2016-01-01

    For unmanned aerial vehicle(UAV) images, the sensor can not get high quality images due to fog and haze weather. To solve this problem, An improved dehazing algorithm of aerial high-definition image is proposed. Based on the model of dark channel prior, the new algorithm firstly extracts the edges from crude estimated transmission map and expands the extracted edges. Then according to the expended edges, the algorithm sets a threshold value to divide the crude estimated transmission map into different areas and makes different guided filter on the different areas compute the optimized transmission map. The experimental results demonstrate that the performance of the proposed algorithm is substantially the same as the one based on dark channel prior and guided filter. The average computation time of the new algorithm is around 40% of the one as well as the detection ability of UAV image is improved effectively in fog and haze weather.

  3. D City Transformations by Time Series of Aerial Images

    NASA Astrophysics Data System (ADS)

    Adami, A.

    2015-02-01

    Recent photogrammetric applications, based on dense image matching algorithms, allow to use not only images acquired by digital cameras, amateur or not, but also to recover the vast heritage of analogue photographs. This possibility opens up many possibilities in the use and enhancement of existing photos heritage. The research of the original figuration of old buildings, the virtual reconstruction of disappeared architectures and the study of urban development are some of the application areas that exploit the great cultural heritage of photography. Nevertheless there are some restrictions in the use of historical images for automatic reconstruction of buildings such as image quality, availability of camera parameters and ineffective geometry of image acquisition. These constrains are very hard to solve and it is difficult to discover good dataset in the case of terrestrial close range photogrammetry for the above reasons. Even the photographic archives of museums and superintendence, while retaining a wealth of documentation, have no dataset for a dense image matching approach. Compared to the vast collection of historical photos, the class of aerial photos meets both criteria stated above. In this paper historical aerial photographs are used with dense image matching algorithms to realize 3d models of a city in different years. The models can be used to study the urban development of the city and its changes through time. The application relates to the city centre of Verona, for which some time series of aerial photographs have been retrieved. The models obtained in this way allowed, right away, to observe the urban development of the city, the places of expansion and new urban areas. But a more interesting aspect emerged from the analytical comparison between models. The difference, as the Euclidean distance, between two models gives information about new buildings or demolitions. As considering accuracy it is necessary point out that the quality of final

  4. HISTORIC IMAGE: AERIAL VIEW WITH THE CEMETERY IN BACKGROUND. PHOTOGRAPH ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    HISTORIC IMAGE: AERIAL VIEW WITH THE CEMETERY IN BACKGROUND. PHOTOGRAPH 29 OCTOBER 1959. NCA HISTORY COLLECTION. - Black Hills National Cemetery, 20901 Pleasant Valley Drive, Sturgis, Meade County, SD

  5. HISTORIC IMAGE: AERIAL VIEW WITH NEW EXPRESSWAY IN FOREGROUND. PHOTOGRAPH ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    HISTORIC IMAGE: AERIAL VIEW WITH NEW EXPRESSWAY IN FOREGROUND. PHOTOGRAPH 19 SEPTEMBER 1978. NCA HISTORY COLLECTION. - Black Hills National Cemetery, 20901 Pleasant Valley Drive, Sturgis, Meade County, SD

  6. Accuracy of Measurements in Oblique Aerial Images for Urban Environment

    NASA Astrophysics Data System (ADS)

    Ostrowski, W.

    2016-10-01

    Oblique aerial images have been a source of data for urban areas for several years. However, the accuracy of measurements in oblique images during this time has been limited to a single meter due to the use of direct -georeferencing technology and the underlying digital elevation model. Therefore, oblique images have been used mostly for visualization purposes. This situation changed in recent years as new methods, which allowed for a higher accuracy of exterior orientation, were developed. Current developments include the process of determining exterior orientation and the previous but still crucial process of tie point extraction. Progress in this area was shown in the ISPRS/EUROSDR Benchmark on Multi-Platform Photogrammetry and is also noticeable in the growing interest in the use of this kind of imagery. The higher level of accuracy in the orientation of oblique aerial images that has become possible in the last few years should result in a higher level of accuracy in the measurements of these types of images. The main goal of this research was to set and empirically verify the accuracy of measurements in oblique aerial images. The research focused on photogrammetric measurements composed of many images, which use a high overlap within an oblique dataset and different view angles. During the experiments, two series of images of urban areas were used. Both were captured using five DigiCam cameras in a Maltese cross configuration. The tilt angles of the oblique cameras were 45 degrees, and the position of the cameras during flight used a high grade GPS/INS navigation system. The orientation of the images was set using the Pix4D Mapper Pro software with both measurements of the in-flight camera position and the ground control points (measured with GPS RTK technology). To control the accuracy, check points were used (which were also measured with GPS RTK technology). As reference data for the whole study, an area of the city-based map was used. The archived results

  7. Calculation and uses of the lithographic aerial image

    NASA Astrophysics Data System (ADS)

    Flagello, Donis G.; Smith, Daniel G.

    2012-09-01

    Beginning with the seminal Dill papers of 1975, the aerial image has been essential for understanding the process of microlithography. From the aerial image, we can predict the performance of a given lithographic process in terms of depth of focus, exposure latitude, etc. As lithographic technologies improved, reaching smaller and smaller printed features, the sophistication of aerial image calculations has had to increase from simple incoherent imaging theory, to partial coherence, polarization effects, thin film effects at the resist, thick mask effects, and so on. This tutorial provides an overview and semihistorical development of the aerial image calculation and then provides a review of some of the various ways in which the aerial image is typically used to estimate the performance of the lithographic process.

  8. Deep person re-identification in aerial images

    NASA Astrophysics Data System (ADS)

    Schumann, Arne; Schuchert, Tobias

    2016-10-01

    Person re-identification is the problem of matching multiple occurrences of a person in large amounts of image or video data. In this work we propose an approach specifically tailored to re-identify people across different camera views in aerial video recordings. New challenges that arise in aerial data include unusual and more varied view angles, a moving camera and potentially large changes in environment and other in uences between recordings (i.e. between flights). Our approach addresses these new challenges. Due to their recent successes, we apply deep learning to automatically learn features for person re-identification on a number of public datasets. We evaluate these features on aerial data and propose a method to automatically select suitable pretrained features without requiring person id labels on the aerial data. We further show that tailored data augmentation methods are well suited to better cope with the larger variety in view angles. Finally, we combine our model with a metric learning approach to allow for interactive improvement of re-identification results through user feedback. We evaluate the approach on our own video dataset which contains 12 persons recorded from a UAV.

  9. An algorithm for approximate rectification of digital aerial images

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High-resolution aerial photography is one of the most valuable tools available for managing extensive landscapes. With recent advances in digital camera technology, computer hardware, and software, aerial photography is easier to collect, store, and transfer than ever before. Images can be automa...

  10. Detection of Aspens Using High Resolution Aerial Laser Scanning Data and Digital Aerial Images

    PubMed Central

    Säynäjoki, Raita; Packalén, Petteri; Maltamo, Matti; Vehmas, Mikko; Eerikäinen, Kalle

    2008-01-01

    The aim was to use high resolution Aerial Laser Scanning (ALS) data and aerial images to detect European aspen (Populus tremula L.) from among other deciduous trees. The field data consisted of 14 sample plots of 30 m × 30 m size located in the Koli National Park in the North Karelia, Eastern Finland. A Canopy Height Model (CHM) was interpolated from the ALS data with a pulse density of 3.86/m2, low-pass filtered using Height-Based Filtering (HBF) and binarized to create the mask needed to separate the ground pixels from the canopy pixels within individual areas. Watershed segmentation was applied to the low-pass filtered CHM in order to create preliminary canopy segments, from which the non-canopy elements were extracted to obtain the final canopy segmentation, i.e. the ground mask was analysed against the canopy mask. A manual classification of aerial images was employed to separate the canopy segments of deciduous trees from those of coniferous trees. Finally, linear discriminant analysis was applied to the correctly classified canopy segments of deciduous trees to classify them into segments belonging to aspen and those belonging to other deciduous trees. The independent variables used in the classification were obtained from the first pulse ALS point data. The accuracy of discrimination between aspen and other deciduous trees was 78.6%. The independent variables in the classification function were the proportion of vegetation hits, the standard deviation of in pulse heights, accumulated intensity at the 90th percentile and the proportion of laser points reflected at the 60th height percentile. The accuracy of classification corresponded to the validation results of earlier ALS-based studies on the classification of individual deciduous trees to tree species. PMID:27873799

  11. Automatic 3D Building Model Generation by Integrating LiDAR and Aerial Images Using a Hybrid Approach

    NASA Astrophysics Data System (ADS)

    Kwak, Eunju

    The development of sensor technologies and the increase in user requirements have resulted in many different approaches for efficient building model generation. Three-dimensional building models are important in various applications, such as disaster management and urban planning. Despite this importance, generation of these models lacks economical and reliable techniques which take advantage of the available multi-sensory data from single and multiple platforms. Therefore, this research develops a framework for fully-automated building model generation by integrating data-driven and model-driven methods as well as exploiting the advantages of images and LiDAR datasets. The building model generation starts by employing LiDAR data for building detection and approximate boundary determination. The generated building boundaries are then integrated into a model-based image processing strategy, because LiDAR derived planes show irregular boundaries due to the nature of LiDAR point acquisition. The focus of the research is generating models for the buildings with right-angled-corners, which can be described with a collection of rectangles (e.g., L-shape, T-shape, U-shape, gable roofs, and more complex building shapes which are combinations of the aforementioned shapes), under the assumption that the majority of the buildings in urban areas belong to this category. Therefore, by applying the Minimum Bounding Rectangle (MBR) algorithm recursively, the LiDAR boundaries are decomposed into sets of rectangles for further processing. At the same time the quality of the MBRs are examined to verify that the buildings, from which the boundaries are generated, are buildings with right-angled-corners. These rectangles are preliminary model primitives. The parameters that define the model primitives are adjusted using detected edges in the imagery through the least-squares adjustment procedure, i.e., model-based image fitting. The level of detail in the final Digital Building Model

  12. HISTORIC IMAGE: AERIAL VIEW OF CEMETERY AND ITS ENVIRONS. PHOTOGRAPH ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    HISTORIC IMAGE: AERIAL VIEW OF CEMETERY AND ITS ENVIRONS. PHOTOGRAPH 15 SEPTEMBER 1950. NCA HISTORY COLLECTION. - San Francisco National Cemetery, 1 Lincoln Boulevard, San Francisco, San Francisco County, CA

  13. Use of simulated neural networks of aerial image classification

    NASA Technical Reports Server (NTRS)

    Medina, Frances I.; Vasquez, Ramon

    1991-01-01

    The utility of one layer neural network in aerial image classification is examined. The network was trained with the delta rule. This method was shown to be useful as a classifier in aerial images with good resolution. It is fast, it is easy to implement, because it is distribution-free, nothing about statistical distribution of the data is needed, and it is very efficient as a boundary detector.

  14. Land cover mapping using aerial and VHR satellite images for distributed hydrological modelling of periurban catchments: Application to the Yzeron catchment (Lyon, France)

    NASA Astrophysics Data System (ADS)

    Jacqueminet, C.; Kermadi, S.; Michel, K.; Béal, D.; Gagnage, M.; Branger, F.; Jankowfsky, S.; Braud, I.

    2013-04-01

    SummaryThe rapid progression of urbanization in periurban areas affects the hydrological cycle of periurban rivers. To quantify these changes, distributed hydrological modelling tools able to simulate the hydrology of periurban catchments are being developed. Land cover information is one of the data sources used to define the model mesh and parameters. The land cover in periurban catchments is characterized by a very large heterogeneity, where the vegetated and the artificial surfaces are finely overlapping. The study is conducted in the Yzeron catchment (150 km2), close to the city of Lyon, France. We explore the potential of very high-resolution (VHR) optical images (0.50-2.50 m) for retrieving information useful for those distributed hydrological models at two scales. For detailed object-oriented models, applicable to catchments of a few km2, where hydrological units are based on the cadastral units, manual digitizing based on the 0.5 m resolution image, was found to be the most accurate to provide the required information. For larger catchments of about 100 km2, three semi-automated mapping procedures (pixel based and object-oriented classifications), applied to aerial images (BD-Ortho®IGN), and two satellite images (Quickbird and Spot 5) were compared. We showed that each image/processing provided some interesting and accurate information about some of the land cover classes. We proposed to combine them into a synthesis map, taking profit of the strength of each image/processing in identifying the land cover classes and their physical properties. This synthesis map was shown to be more accurate than each map separately. We illustrate the interest of the derived maps in terms of distributed hydrological modelling. The maps were used to propose a classification of the Yzeron sub-catchments in terms of dominant vegetation cover and imperviousness. We showed that according to the image processing and images characteristics, the calculated imperviousness rates

  15. Advanced Image Processing of Aerial Imagery

    NASA Technical Reports Server (NTRS)

    Woodell, Glenn; Jobson, Daniel J.; Rahman, Zia-ur; Hines, Glenn

    2006-01-01

    Aerial imagery of the Earth is an invaluable tool for the assessment of ground features, especially during times of disaster. Researchers at the NASA Langley Research Center have developed techniques which have proven to be useful for such imagery. Aerial imagery from various sources, including Langley's Boeing 757 Aries aircraft, has been studied extensively. This paper discusses these studies and demonstrates that better-than-observer imagery can be obtained even when visibility is severely compromised. A real-time, multi-spectral experimental system will be described and numerous examples will be shown.

  16. Automated updating of road databases from aerial images

    NASA Astrophysics Data System (ADS)

    Baltsavias, Emmanuel; Zhang, Chunsun

    2005-03-01

    This paper presents a practical system for automated 3-D road network reconstruction from aerial images using knowledge-based image analysis. The system integrates processing of color image data and information from digital spatial databases, extracts and fuses multiple object cues, takes into account context information, employs existing knowledge, rules and models, and treats each road subclass accordingly. The key of the system is the use of knowledge as much as possible to increase success rate and reliability of the results, working in 2-D images and 3-D object space, and use of 2-D and 3-D interaction when needed. Another advantage of the developed system is that it can correctly and reliably handle problematic areas caused by shadows and occlusions. This work is part of a project to improve and update the 1:25,000 vector maps of Switzerland. The system was originally developed to processed stereo images. Recently, it has been modified to work also with single orthoimages. The system has been implemented as a stand-alone software package, and has been tested on a large number of images with different landscape. In this paper, various parts of the developed system are discussed, and the results of our system in the tests conducted independently by our project partner in Switzerland, and the test results with orthoimages in a test site in The Netherlands are presented together with the system performance evaluation.

  17. Design and realization of an image mosaic system on the CCD aerial camera

    NASA Astrophysics Data System (ADS)

    Liu, Hai ying; Wang, Peng; Zhu, Hai bin; Li, Yan; Zhang, Shao jun

    2015-08-01

    It has long been difficulties in aerial photograph to stitch multi-route images into a panoramic image in real time for multi-route flight framing CCD camera with very large amount of data, and high accuracy requirements. An automatic aerial image mosaic system based on GPU development platform is described in this paper. Parallel computing of SIFT feature extraction and matching algorithm module is achieved by using CUDA technology for motion model parameter estimation on the platform, which makes it's possible to stitch multiple CCD images in real-time. Aerial tests proved that the mosaic system meets the user's requirements with 99% accuracy and 30 to 50 times' speed improvement of the normal mosaic system.

  18. HISTORIC IMAGE: AERIAL VIEW OF THE CEMETERY AND ITS ENVIRONS. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    HISTORIC IMAGE: AERIAL VIEW OF THE CEMETERY AND ITS ENVIRONS. PHOTOGRAPH TAKEN ON 6 APRIL 1968. NCA HISTORY COLLECTION. - Rock Island National Cemetery, Rock Island Arsenal, 0.25 mile north of southern tip of Rock Island, Rock Island, Rock Island County, IL

  19. A Low-Cost Imaging System for Aerial Applicators

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agricultural aircraft provide a readily available and versatile platform for airborne remote sensing. Although various airborne imaging systems are being used for research and commercial applications, most of these systems are either too expensive or too complex to be of practical use for aerial app...

  20. Coastline Extraction from Aerial Images Based on Edge Detection

    NASA Astrophysics Data System (ADS)

    Paravolidakis, V.; Moirogiorgou, K.; Ragia, L.; Zervakis, M.; Synolakis, C.

    2016-06-01

    Nowadays coastline extraction and tracking of its changes become of high importance because of the climate change, global warming and rapid growth of human population. Coastal areas play a significant role for the economy of the entire region. In this paper we propose a new methodology for automatic extraction of the coastline using aerial images. A combination of a four step algorithm is used to extract the coastline in a robust and generalizable way. First, noise distortion is reduced in order to ameliorate the input data for the next processing steps. Then, the image is segmented into two regions, land and sea, through the application of a local threshold to create the binary image. The result is further processed by morphological operators with the aim that small objects are being eliminated and only the objects of interest are preserved. Finally, we perform edge detection and active contours fitting in order to extract and model the coastline. These algorithmic steps are illustrated through examples, which demonstrate the efficacy of the proposed methodology.

  1. CMOS Imaging Sensor Technology for Aerial Mapping Cameras

    NASA Astrophysics Data System (ADS)

    Neumann, Klaus; Welzenbach, Martin; Timm, Martin

    2016-06-01

    In June 2015 Leica Geosystems launched the first large format aerial mapping camera using CMOS sensor technology, the Leica DMC III. This paper describes the motivation to change from CCD sensor technology to CMOS for the development of this new aerial mapping camera. In 2002 the DMC first generation was developed by Z/I Imaging. It was the first large format digital frame sensor designed for mapping applications. In 2009 Z/I Imaging designed the DMC II which was the first digital aerial mapping camera using a single ultra large CCD sensor to avoid stitching of smaller CCDs. The DMC III is now the third generation of large format frame sensor developed by Z/I Imaging and Leica Geosystems for the DMC camera family. It is an evolution of the DMC II using the same system design with one large monolithic PAN sensor and four multi spectral camera heads for R,G, B and NIR. For the first time a 391 Megapixel large CMOS sensor had been used as PAN chromatic sensor, which is an industry record. Along with CMOS technology goes a range of technical benefits. The dynamic range of the CMOS sensor is approx. twice the range of a comparable CCD sensor and the signal to noise ratio is significantly better than with CCDs. Finally results from the first DMC III customer installations and test flights will be presented and compared with other CCD based aerial sensors.

  2. Human Operator Modeling for Aerial Tracking.

    DTIC Science & Technology

    1980-12-01

    HUMAN OPERATOR MODELING FOR AERIAL TRACKING JONA THAN KORN ARTER. EPHRATH DA VLD L. KLEINMAN DBCXMBt 19MDTICSELECTE APR 3 1981.j B Approwd for pVA& u...8217the "Guid 8en th Cart end Use of laboratory Animals, "Inatitate of Laboratory Animl ReaNuWAes, National Rtesarch CouncL The voluntary Infomed consent...Continue. on reverse aide If necessary and identify hc block numbrh) ._Modern Optimal Control techniques are e:iployed to investigate and model human

  3. Application of high resolution images from unmanned aerial vehicles for hydrology and range science

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A common problem in many natural resource disciplines is the lack of high-enough spatial resolution images that can be used for monitoring and modeling purposes. Advances have been made in the utilization of Unmanned Aerial Vehicles (UAVs) in hydrology and rangeland science. By utilizing low fligh...

  4. Aerial image databases for pipeline rights-of-way management

    NASA Astrophysics Data System (ADS)

    Jadkowski, Mark A.

    1996-03-01

    Pipeline companies that own and manage extensive rights-of-way corridors are faced with ever-increasing regulatory pressures, operating issues, and the need to remain competitive in today's marketplace. Automation has long been an answer to the problem of having to do more work with less people, and Automated Mapping/Facilities Management/Geographic Information Systems (AM/FM/GIS) solutions have been implemented at several pipeline companies. Until recently, the ability to cost-effectively acquire and incorporate up-to-date aerial imagery into these computerized systems has been out of the reach of most users. NASA's Earth Observations Commercial Applications Program (EOCAP) is providing a means by which pipeline companies can bridge this gap. The EOCAP project described in this paper includes a unique partnership with NASA and James W. Sewall Company to develop an aircraft-mounted digital camera system and a ground-based computer system to geometrically correct and efficiently store and handle the digital aerial images in an AM/FM/GIS environment. This paper provides a synopsis of the project, including details on (1) the need for aerial imagery, (2) NASA's interest and role in the project, (3) the design of a Digital Aerial Rights-of-Way Monitoring System, (4) image georeferencing strategies for pipeline applications, and (5) commercialization of the EOCAP technology through a prototype project at Algonquin Gas Transmission Company which operates major gas pipelines in New England, New York, and New Jersey.

  5. Feature extraction with LIDAR data and aerial images

    NASA Astrophysics Data System (ADS)

    Mao, Jianhua; Liu, Yanjing; Cheng, Penggen; Li, Xianhua; Zeng, Qihong; Xia, Jing

    2006-10-01

    Raw LIDAR data is a irregular spacing 3D point cloud including reflections from bare ground, buildings, vegetation and vehicles etc., and the first task of the data analyses of point cloud is feature extraction. However, the interpretability of LIDAR point cloud is often limited due to the fact that no object information is provided, and the complex earth topography and object morphology make it impossible for a single operator to classify all the point cloud precisely 100%. In this paper, a hierarchy method for feature extraction with LIDAR data and aerial images is discussed. The aerial images provide us information of objects figuration and spatial distribution, and hierarchic classification of features makes it easy to apply automatic filters progressively. And the experiment results show that, using this method, it was possible to detect more object information and get a better result of feature extraction than using automatic filters alone.

  6. Vehicle Detection of Aerial Image Using TV-L1 Texture Decomposition

    NASA Astrophysics Data System (ADS)

    Wang, Y.; Wang, G.; Li, Y.; Huang, Y.

    2016-06-01

    Vehicle detection from high-resolution aerial image facilitates the study of the public traveling behavior on a large scale. In the context of road, a simple and effective algorithm is proposed to extract the texture-salient vehicle among the pavement surface. Texturally speaking, the majority of pavement surface changes a little except for the neighborhood of vehicles and edges. Within a certain distance away from the given vector of the road network, the aerial image is decomposed into a smoothly-varying cartoon part and an oscillatory details of textural part. The variational model of Total Variation regularization term and L1 fidelity term (TV-L1) is adopted to obtain the salient texture of vehicles and the cartoon surface of pavement. To eliminate the noise of texture decomposition, regions of pavement surface are refined by seed growing and morphological operation. Based on the shape saliency analysis of the central objects in those regions, vehicles are detected as the objects of rectangular shape saliency. The proposed algorithm is tested with a diverse set of aerial images that are acquired at various resolution and scenarios around China. Experimental results demonstrate that the proposed algorithm can detect vehicles at the rate of 71.5% and the false alarm rate of 21.5%, and that the speed is 39.13 seconds for a 4656 x 3496 aerial image. It is promising for large-scale transportation management and planning.

  7. a Fast Approach for Stitching of Aerial Images

    NASA Astrophysics Data System (ADS)

    Moussa, A.; El-Sheimy, N.

    2016-06-01

    The last few years have witnessed an increasing volume of aerial image data because of the extensive improvements of the Unmanned Aerial Vehicles (UAVs). These newly developed UAVs have led to a wide variety of applications. A fast assessment of the achieved coverage and overlap of the acquired images of a UAV flight mission is of great help to save the time and cost of the further steps. A fast automatic stitching of the acquired images can help to visually assess the achieved coverage and overlap during the flight mission. This paper proposes an automatic image stitching approach that creates a single overview stitched image using the acquired images during a UAV flight mission along with a coverage image that represents the count of overlaps between the acquired images. The main challenge of such task is the huge number of images that are typically involved in such scenarios. A short flight mission with image acquisition frequency of one second can capture hundreds to thousands of images. The main focus of the proposed approach is to reduce the processing time of the image stitching procedure by exploiting the initial knowledge about the images positions provided by the navigation sensors. The proposed approach also avoids solving for all the transformation parameters of all the photos together to save the expected long computation time if all the parameters were considered simultaneously. After extracting the points of interest of all the involved images using Scale-Invariant Feature Transform (SIFT) algorithm, the proposed approach uses the initial image's coordinates to build an incremental constrained Delaunay triangulation that represents the neighborhood of each image. This triangulation helps to match only the neighbor images and therefore reduces the time-consuming features matching step. The estimated relative orientation between the matched images is used to find a candidate seed image for the stitching process. The pre-estimated transformation

  8. Semi-automatic detection of linear archaeological traces from orthorectified aerial images

    NASA Astrophysics Data System (ADS)

    Figorito, Benedetto; Tarantino, Eufemia

    2014-02-01

    This paper presents a semi-automatic approach for archaeological traces detection from aerial images. The method developed was based on the multiphase active contour model (ACM). The image was segmented into three competing regions to improve the visibility of buried remains showing in the image as crop marks (i.e. centuriations, agricultural allocations, ancient roads, etc.). An initial determination of relevant traces can be quickly carried out by the operator by sketching straight lines close to the traces. Subsequently, tuning parameters (i.e. eccentricity, orientation, minimum area and distance from input line) are used to remove non-target objects and parameterize the detected traces. The algorithm and graphical user interface for this method were developed in a MATLAB environment and tested on high resolution orthorectified aerial images. A qualitative analysis of the method was lastly performed by comparing the traces extracted with ancient traces verified by archaeologists.

  9. Generating object proposals for improved object detection in aerial images

    NASA Astrophysics Data System (ADS)

    Sommer, Lars W.; Schuchert, Tobias; Beyerer, Jürgen

    2016-10-01

    Screening of aerial images covering large areas is important for many applications such as surveillance, tracing or rescue tasks. To reduce the workload of image analysts, an automatic detection of candidate objects is required. In general, object detection is performed by applying classifiers or a cascade of classifiers within a sliding window algorithm. However, the huge number of windows to classify, especially in case of multiple object scales, makes these approaches computationally expensive. To overcome this challenge, we reduce the number of candidate windows by generating so called object proposals. Object proposals are a set of candidate regions in an image that are likely to contain an object. We apply the Selective Search approach that has been broadly used as proposals method for detectors like R-CNN or Fast R-CNN. Therefore, a set of small regions is generated by initial segmentation followed by hierarchical grouping of the initial regions to generate proposals at different scales. To reduce the computational costs of the original approach, which consists of 80 combinations of segmentation settings and grouping strategies, we only apply the most appropriate combination. Therefore, we analyze the impact of varying segmentation settings, different merging strategies, and various colour spaces by calculating the recall with regard to the number of object proposals and the intersection over union between generated proposals and ground truth annotations. As aerial images differ considerably from datasets that are typically used for exploring object proposals methods, in particular in object size and the image fraction occupied by an object, we further adapt the Selective Search algorithm to aerial images by replacing the random order of generated proposals by a weighted order based on the object proposal size and integrate a termination criterion for the merging strategies. Finally, the adapted approach is compared to the original Selective Search algorithm

  10. An automatic high precision registration method between large area aerial images and aerial light detection and ranging data

    NASA Astrophysics Data System (ADS)

    Du, Q.; Xie, D.; Sun, Y.

    2015-06-01

    The integration of digital aerial photogrammetry and Light Detetion And Ranging (LiDAR) is an inevitable trend in Surveying and Mapping field. We calculate the external orientation elements of images which identical with LiDAR coordinate to realize automatic high precision registration between aerial images and LiDAR data. There are two ways to calculate orientation elements. One is single image spatial resection using image matching 3D points that registered to LiDAR. The other one is Position and Orientation System (POS) data supported aerotriangulation. The high precision registration points are selected as Ground Control Points (GCPs) instead of measuring GCPs manually during aerotriangulation. The registration experiments indicate that the method which registering aerial images and LiDAR points has a great advantage in higher automation and precision compare with manual registration.

  11. Application of machine learning for the evaluation of turfgrass plots using aerial images

    NASA Astrophysics Data System (ADS)

    Ding, Ke; Raheja, Amar; Bhandari, Subodh; Green, Robert L.

    2016-05-01

    Historically, investigation of turfgrass characteristics have been limited to visual ratings. Although relevant information may result from such evaluations, final inferences may be questionable because of the subjective nature in which the data is collected. Recent advances in computer vision techniques allow researchers to objectively measure turfgrass characteristics such as percent ground cover, turf color, and turf quality from the digital images. This paper focuses on developing a methodology for automated assessment of turfgrass quality from aerial images. Images of several turfgrass plots of varying quality were gathered using a camera mounted on an unmanned aerial vehicle. The quality of these plots were also evaluated based on visual ratings. The goal was to use the aerial images to generate quality evaluations on a regular basis for the optimization of water treatment. Aerial images are used to train a neural network so that appropriate features such as intensity, color, and texture of the turfgrass are extracted from these images. Neural network is a nonlinear classifier commonly used in machine learning. The output of the neural network trained model is the ratings of the grass, which is compared to the visual ratings. Currently, the quality and the color of turfgrass, measured as the greenness of the grass, are evaluated. The textures are calculated using the Gabor filter and co-occurrence matrix. Other classifiers such as support vector machines and simpler linear regression models such as Ridge regression and LARS regression are also used. The performance of each model is compared. The results show encouraging potential for using machine learning techniques for the evaluation of turfgrass quality and color.

  12. Algorithm for unmanned aerial vehicle aerial different-source image matching

    NASA Astrophysics Data System (ADS)

    Zuo, Yujia; Liu, Jinghong; Yang, Mingyu; Wang, Xuan; Sun, Mingchao

    2016-12-01

    The fusion between visible and infrared images captured by unmanned aerial vehicles (UAVs), both complementary to each other, can improve the reliability of target detection and recognition and other tasks. The images captured by UAV are featured by high dynamics and complex air-ground target background. Pixel-level matching should be conducted for the two different-source images, prior to their fusion. Therefore, an improved matching algorithm has been proposed that combines the improved Shi-Tomasi algorithm with the shape context (SC)-based algorithm. First, the Shi-Tomasi algorithm is employed to conduct feature-point detection in the scale space. The tangential direction of the edge contour where the feature-point lies is taken as its main direction, so as to guarantee the algorithm's rotational invariance. Then, this paper conducts the block description for the extracted feature-point within the n×n neighborhood of its edge contour to obtain its descriptors. Finally, a fast library for approximate nearest neighbors matching algorithm is adopted to match all the feature-points. And the experimental results show that, in the scene where the shape of the main target is clear, the algorithm can achieve better matching and registration results for infrared and visible images that have been transformed through rotation, translation, or zooming.

  13. Building 3D aerial image in photoresist with reconstructed mask image acquired with optical microscope

    NASA Astrophysics Data System (ADS)

    Chou, C. S.; Tang, Y. P.; Chu, F. S.; Huang, W. C.; Liu, R. G.; Gau, T. S.

    2012-03-01

    Calibration of mask images on wafer becomes more important as features shrink. Two major types of metrology have been commonly adopted. One is to measure the mask image with scanning electron microscope (SEM) to obtain the contours on mask and then simulate the wafer image with optical simulator. The other is to use an optical imaging tool Aerial Image Measurement System (AIMSTM) to emulate the image on wafer. However, the SEM method is indirect. It just gathers planar contours on a mask with no consideration of optical characteristics such as 3D topography structures. Hence, the image on wafer is not predicted precisely. Though the AIMSTM method can be used to directly measure the intensity at the near field of a mask but the image measured this way is not quite the same as that on the wafer due to reflections and refractions in the films on wafer. Here, a new approach is proposed to emulate the image on wafer more precisely. The behavior of plane waves with different oblique angles is well known inside and between planar film stacks. In an optical microscope imaging system, plane waves can be extracted from the pupil plane with a coherent point source of illumination. Once plane waves with a specific coherent illumination are analyzed, the partially coherent component of waves could be reconstructed with a proper transfer function, which includes lens aberration, polarization, reflection and refraction in films. It is a new method that we can transfer near light field of a mask into an image on wafer without the disadvantages of indirect SEM measurement such as neglecting effects of mask topography, reflections and refractions in the wafer film stacks. Furthermore, with this precise latent image, a separated resist model also becomes more achievable.

  14. a New Paradigm for Matching - and Aerial Images

    NASA Astrophysics Data System (ADS)

    Koch, T.; Zhuo, X.; Reinartz, P.; Fraundorfer, F.

    2016-06-01

    This paper investigates the performance of SIFT-based image matching regarding large differences in image scaling and rotation, as this is usually the case when trying to match images captured from UAVs and airplanes. This task represents an essential step for image registration and 3d-reconstruction applications. Various real world examples presented in this paper show that SIFT, as well as A-SIFT perform poorly or even fail in this matching scenario. Even if the scale difference in the images is known and eliminated beforehand, the matching performance suffers from too few feature point detections, ambiguous feature point orientations and rejection of many correct matches when applying the ratio-test afterwards. Therefore, a new feature matching method is provided that overcomes these problems and offers thousands of matches by a novel feature point detection strategy, applying a one-to-many matching scheme and substitute the ratio-test by adding geometric constraints to achieve geometric correct matches at repetitive image regions. This method is designed for matching almost nadir-directed images with low scene depth, as this is typical in UAV and aerial image matching scenarios. We tested the proposed method on different real world image pairs. While standard SIFT failed for most of the datasets, plenty of geometrical correct matches could be found using our approach. Comparing the estimated fundamental matrices and homographies with ground-truth solutions, mean errors of few pixels can be achieved.

  15. Error Estimation Techniques to Refine Overlapping Aerial Image Mosaic Processes via Detected Parameters

    ERIC Educational Resources Information Center

    Bond, William Glenn

    2012-01-01

    In this paper, I propose to demonstrate a means of error estimation preprocessing in the assembly of overlapping aerial image mosaics. The mosaic program automatically assembles several hundred aerial images from a data set by aligning them, via image registration using a pattern search method, onto a GIS grid. The method presented first locates…

  16. Realization of an aerial 3D image that occludes the background scenery.

    PubMed

    Kakeya, Hideki; Ishizuka, Shuta; Sato, Yuya

    2014-10-06

    In this paper we describe an aerial 3D image that occludes far background scenery based on coarse integral volumetric imaging (CIVI) technology. There have been many volumetric display devices that present floating 3D images, most of which have not reproduced the visual occlusion. CIVI is a kind of multilayered integral imaging and realizes an aerial volumetric image with visual occlusion by combining multiview and volumetric display technologies. The conventional CIVI, however, cannot show a deep space, for the number of layered panels is limited because of the low transmittance of each panel. To overcome this problem, we propose a novel optical design to attain an aerial 3D image that occludes far background scenery. In the proposed system, a translucent display panel with 120 Hz refresh rate is located between the CIVI system and the aerial 3D image. The system modulates between the aerial image mode and the background image mode. In the aerial image mode, the elemental images are shown on the CIVI display and the inserted translucent display is uniformly translucent. In the background image mode, the black shadows of the elemental images in a white background are shown on the CIVI display and the background scenery is displayed on the inserted translucent panel. By alternation of these two modes at 120 Hz, an aerial 3D image that visually occludes the far background scenery is perceived by the viewer.

  17. Line matching based on planar homography for stereo aerial images

    NASA Astrophysics Data System (ADS)

    Sun, Yanbiao; Zhao, Liang; Huang, Shoudong; Yan, Lei; Dissanayake, Gamini

    2015-06-01

    We propose an efficient line matching algorithm for a pair of calibrated aerial photogrammetric images, which makes use of sparse 3D points triangulated from 2D point feature correspondences to guide line matching based on planar homography. Two different strategies are applied in the proposed line matching algorithm for two different cases. When three or more points can be found coplanar with the line segment to be matched, the points are used to fit a plane and obtain an accurate planar homography. When one or two points can be found, the approximate terrain plane parallel to the line segment is utilized to compute an approximate planar homography. Six pairs of rural or urban aerial images are used to demonstrate the efficiency and validity of the proposed algorithm. Compared with line matching based on 2D point feature correspondences, the proposed method can increase the number of correctly matched line segments. In addition, compared with most line matching methods that do not use 2D point feature correspondences, the proposed method has better efficiency, although it obtains fewer matches. The C/C++ source code for the proposed algorithm is available at

  18. Direct Penguin Counting Using Unmanned Aerial Vehicle Image

    NASA Astrophysics Data System (ADS)

    Hyun, C. U.; Kim, H. C.; Kim, J. H.; Hong, S. G.

    2015-12-01

    This study presents an application of unmanned aerial vehicle (UAV) images to monitor penguin colony in Baton Peninsula, King George Island, Antarctica. The area around Narębski Point located on the southeast coast of Barton Peninsula was designated as Antarctic Specially Protected Area No. 171 (ASPA 171), and Chinstrap and Gentoo penguins inhabit in this area. The UAV images were acquired in a part of ASPA 171 from four flights in a single day, Jan 18, 2014. About 360 images were mosaicked as an image of about 3 cm spatial resolution and then a subset including representative penguin rookeries was selected. The subset image was segmented based on gradient map of pixel values, and spectral and spatial attributes were assigned to each segment. The object based image analysis (OBIA) was conducted with consideration of spectral attributes including mean and minimum values of each segment and various shape attributes such as area, length, compactness and roundness to detect individual penguin. The segments indicating individual penguin were effectively detected on rookeries with high contrasts in the spectral and shape attributes. The importance of periodic and precise monitoring of penguins has been recognized because variations of their populations reflect environmental changes and disturbance from human activities. Utilization of very high resolution imaging method shown in this study can be applied to other penguin habitats in Antarctica, and the results will be able to support establishing effective environmental management plans.

  19. Precision Relative Positioning for Automated Aerial Refueling from a Stereo Imaging System

    DTIC Science & Technology

    2015-03-01

    PRECISION RELATIVE POSITIONING FOR AUTOMATED AERIAL REFUELING FROM A STEREO IMAGING SYSTEM THESIS Kyle P. Werner, 2Lt, USAF AFIT-ENG-MS-15-M-048...Government and is not subject to copyright protection in the United States. AFIT-ENG-MS-15-M-048 PRECISION RELATIVE POSITIONING FOR AUTOMATED AERIAL...RELEASE; DISTRIBUTION UNLIMITED. AFIT-ENG-MS-15-M-048 PRECISION RELATIVE POSITIONING FOR AUTOMATED AERIAL REFUELING FROM A STEREO IMAGING SYSTEM THESIS

  20. Integration of aerial imaging and variable-rate technology for site-specific aerial herbicide application

    Technology Transfer Automated Retrieval System (TEKTRAN)

    As remote sensing and variable rate technology are becoming more available for aerial applicators, practical methodologies on effective integration of these technologies are needed for site-specific aerial applications of crop production and protection materials. The objectives of this study were to...

  1. Aerial imaging manages pipeline right-of-way programs

    SciTech Connect

    Jadkowski, M.A.; Convery, P.

    1996-02-01

    Pipeline companies that own and manage extensive rights-of-way corridors are facing ever-increasing regulatory pressures, operating issues and ongoing needs to remain competitive in today`s marketplace. The digital aerial rights-of-way monitoring system (DARMS) is a personal computer-based digital charge-coupled device (CCD) camera integrated with a high-capacity tape recorder. DARMS was developed through NASA by the Stennis Space Center for use in a Sewall aircraft. Sewall is responsible for its operational testing and developing the image products for pipeline monitoring. DARMS consists of a personal computer main control unit (MCU), a Kodak Megaplus 1.4-CCD camera head, a monochrome video monitor for in-flight operation, and an Exabyte 8500 8-millimeter tape recorder for image data storage. The system is designed to be operated in a small, unpressurized aircraft flown by a single pilot. The control program software provides a highly autonomous turnkey operation. After a mission has been flown, Exabyte tape is loaded onto a Sun workstation and the images are contrast-balanced and spatially enhanced using a mid-high filtering algorithm. Depending on client requirements, images also may be geo-referenced to a coordinate system or mosaicked together. The resulting image frames are indexed using their GPS location, delivered to the client and archived.

  2. Application of Digital Image Correlation Method to Improve the Accuracy of Aerial Photo Stitching

    NASA Astrophysics Data System (ADS)

    Tung, Shih-Heng; Jhou, You-Liang; Shih, Ming-Hsiang; Hsiao, Han-Wei; Sung, Wen-Pei

    2016-04-01

    Satellite images and traditional aerial photos have been used in remote sensing for a long time. However, there are some problems with these images. For example, the resolution of satellite image is insufficient, the cost to obtain traditional images is relatively high and there is also human safety risk in traditional flight. These result in the application limitation of these images. In recent years, the control technology of unmanned aerial vehicle (UAV) is rapidly developed. This makes unmanned aerial vehicle widely used in obtaining aerial photos. Compared to satellite images and traditional aerial photos, these aerial photos obtained using UAV have the advantages of higher resolution, low cost. Because there is no crew in UAV, it is still possible to take aerial photos using UAV under unstable weather conditions. Images have to be orthorectified and their distortion must be corrected at first. Then, with the help of image matching technique and control points, these images can be stitched or used to establish DEM of ground surface. These images or DEM data can be used to monitor the landslide or estimate the volume of landslide. For the image matching, we can use such as Harris corner method, SIFT or SURF to extract and match feature points. However, the accuracy of these methods for matching is about pixel or sub-pixel level. The accuracy of digital image correlation method (DIC) during image matching can reach about 0.01pixel. Therefore, this study applies digital image correlation method to match extracted feature points. Then the stitched images are observed to judge the improvement situation. This study takes the aerial photos of a reservoir area. These images are stitched under the situations with and without the help of DIC. The results show that the misplacement situation in the stitched image using DIC to match feature points has been significantly improved. This shows that the use of DIC to match feature points can actually improve the accuracy of

  3. Initial Efforts toward Mission-Representative Imaging Surveys from Aerial Explorers

    NASA Technical Reports Server (NTRS)

    Pisanich, Greg; Plice, Laura; Ippolito, Corey; Young, Larry A.; Lau, Benton; Lee, Pascal

    2004-01-01

    Numerous researchers have proposed the use of robotic aerial explorers to perform scientific investigation of planetary bodies in our solar system. One of the essential tasks for any aerial explorer is to be able to perform scientifically valuable imaging surveys. The focus of this paper is to discuss the challenges implicit in, and recent observations related to, acquiring mission-representative imaging data from a small fixed-wing UAV, acting as a surrogate planetary aerial explorer. This question of successfully performing aerial explorer surveys is also tied to other topics of technical investigation, including the development of unique bio-inspired technologies.

  4. Research of aerial imaging spectrometer data acquisition technology based on USB 3.0

    NASA Astrophysics Data System (ADS)

    Huang, Junze; Wang, Yueming; He, Daogang; Yu, Yanan

    2016-11-01

    With the emergence of UAV (unmanned aerial vehicle) platform for aerial imaging spectrometer, research of aerial imaging spectrometer DAS(data acquisition system) faces new challenges. Due to the limitation of platform and other factors, the aerial imaging spectrometer DAS requires small-light, low-cost and universal. Traditional aerial imaging spectrometer DAS system is expensive, bulky, non-universal and unsupported plug-and-play based on PCIe. So that has been unable to meet promotion and application of the aerial imaging spectrometer. In order to solve these problems, the new data acquisition scheme bases on USB3.0 interface.USB3.0 can provide guarantee of small-light, low-cost and universal relying on the forward-looking technology advantage. USB3.0 transmission theory is up to 5Gbps.And the GPIF programming interface achieves 3.2Gbps of the effective theoretical data bandwidth.USB3.0 can fully meet the needs of the aerial imaging spectrometer data transmission rate. The scheme uses the slave FIFO asynchronous data transmission mode between FPGA and USB3014 interface chip. Firstly system collects spectral data from TLK2711 of high-speed serial interface chip. Then FPGA receives data in DDR2 cache after ping-pong data processing. Finally USB3014 interface chip transmits data via automatic-dma approach and uploads to PC by USB3.0 cable. During the manufacture of aerial imaging spectrometer, the DAS can achieve image acquisition, transmission, storage and display. All functions can provide the necessary test detection for aerial imaging spectrometer. The test shows that system performs stable and no data lose. Average transmission speed and storage speed of writing SSD can stabilize at 1.28Gbps. Consequently ,this data acquisition system can meet application requirements for aerial imaging spectrometer.

  5. Semantic Segmentation of Aerial Images with AN Ensemble of Cnns

    NASA Astrophysics Data System (ADS)

    Marmanis, D.; Wegner, J. D.; Galliani, S.; Schindler, K.; Datcu, M.; Stilla, U.

    2016-06-01

    This paper describes a deep learning approach to semantic segmentation of very high resolution (aerial) images. Deep neural architectures hold the promise of end-to-end learning from raw images, making heuristic feature design obsolete. Over the last decade this idea has seen a revival, and in recent years deep convolutional neural networks (CNNs) have emerged as the method of choice for a range of image interpretation tasks like visual recognition and object detection. Still, standard CNNs do not lend themselves to per-pixel semantic segmentation, mainly because one of their fundamental principles is to gradually aggregate information over larger and larger image regions, making it hard to disentangle contributions from different pixels. Very recently two extensions of the CNN framework have made it possible to trace the semantic information back to a precise pixel position: deconvolutional network layers undo the spatial downsampling, and Fully Convolution Networks (FCNs) modify the fully connected classification layers of the network in such a way that the location of individual activations remains explicit. We design a FCN which takes as input intensity and range data and, with the help of aggressive deconvolution and recycling of early network layers, converts them into a pixelwise classification at full resolution. We discuss design choices and intricacies of such a network, and demonstrate that an ensemble of several networks achieves excellent results on challenging data such as the ISPRS semantic labeling benchmark, using only the raw data as input.

  6. Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis

    DTIC Science & Technology

    1989-08-01

    Automatic Line Network Extraction from Aerial Imangery of Urban Areas Sthrough KnowledghBased Image Analysis N 04 Final Technical ReportI December...Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis Accesion For NTIS CRA&I DTIC TAB 0...paittern re’ognlition. blac’kboardl oriented symbollic processing, knowledge based image analysis , image understanding, aer’ial imsagery, urban area, 17

  7. Grab a coffee: your aerial images are already analyzed

    NASA Astrophysics Data System (ADS)

    Garetto, Anthony; Rademacher, Thomas; Schulz, Kristian

    2015-07-01

    For over 2 decades the AIMTM platform has been utilized in mask shops as the standard for actinic review of photomask sites in order to perform defect disposition and repair review. Throughout this time the measurement throughput of the systems has been improved in order to keep pace with the requirements demanded by a manufacturing environment, however the analysis of the sites captured has seen little improvement and remained a manual process. This manual analysis of aerial images is time consuming, subject to error and unreliability and contributes to holding up turn-around time (TAT) and slowing process flow in a manufacturing environment. AutoAnalysis, the first application available for the FAVOR® platform, offers a solution to these problems by providing fully automated data transfer and analysis of AIMTM aerial images. The data is automatically output in a customizable format that can be tailored to your internal needs and the requests of your customers. Savings in terms of operator time arise from the automated analysis which no longer needs to be performed. Reliability is improved as human error is eliminated making sure the most defective region is always and consistently captured. Finally the TAT is shortened and process flow for the back end of the line improved as the analysis is fast and runs in parallel to the measurements. In this paper the concept and approach of AutoAnalysis will be presented as well as an update to the status of the project. A look at the benefits arising from the automation and the customizable approach of the solution will be shown.

  8. A registration strategy for long spatio-temporal aerial remote sensing image sequence

    NASA Astrophysics Data System (ADS)

    Cao, Yutian; Yan, Dongmei; Li, Jianming; Wang, Gang

    2015-12-01

    A novel registration strategy for aerial image sequence is put forward to adapt to the long spatio-temporal span of the aerial remote sensing imaging. By setting keyframe, this strategy aligns all images in sequence to a unified datum with high registration sustainability and precision. The contrast experiment on different registration strategies is carried out based on SIFT feature matching of mid-infrared aerial sequences. The experiment results show that the proposed strategy performs well on long spatio-temporal sequences with different imaging resolutions and scenes.

  9. Using aerial photography and image analysis to measure changes in giant reed populations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A study was conducted along the Rio Grande in southwest Texas to evaluate color-infrared aerial photography combined with supervised image analysis to quantify changes in giant reed (Arundo donax L.) populations over a 6-year period. Aerial photographs from 2002 and 2008 of the same seven study site...

  10. Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge-Based Image Analysis.

    DTIC Science & Technology

    1988-01-19

    approach for the analysis of aerial images. In this approach image analysis is performed ast three levels of abstraction, namely iconic or low-level... image analysis , symbolic or medium-level image analysis , and semantic or high-level image analysis . Domain dependent knowledge about prototypical urban

  11. Automatic orthorectification and mosaicking of oblique images from a zoom lens aerial camera

    NASA Astrophysics Data System (ADS)

    Zhou, Qianfei; Liu, Jinghong

    2015-01-01

    For the purpose of image distortion caused by the oblique photography of a zoom lens aerial camera, a fast and accurate image autorectification and mosaicking method in a ground control points (GCPs)-free environment was proposed. With the availability of integrated global positioning system (GPS) and inertial measurement units, the camera's exterior orientation parameters (EOPs) were solved through direct georeferencing. The one-parameter division model was adopted to estimate the distortion coefficient and the distortion center coordinates for the zoom lens to correct the lens distortion. Using the camera's EOPs and the lens distortion parameters, the oblique aerial images specified in the camera frame were geo-orthorectified into the mapping frame and then were mosaicked together based on the mapping coordinates to produce a larger field and high-resolution georeferenced image. Experimental results showed that the orthorectification error was less than 1.80 m at an 1100 m flight height above ground level, when compared with 14 presurveyed ground checkpoints which were measured by differential GPS. The mosaic error was about 1.57 m compared with 18 checkpoints. The accuracy was considered sufficient for urgent response such as military reconnaissance and disaster monitoring where GCPs were not available.

  12. New Approach for Segmentation and Extraction of Single Tree from Point Clouds Data and Aerial Images

    NASA Astrophysics Data System (ADS)

    Homainejad, A. S.

    2016-06-01

    This paper addresses a new approach for reconstructing a 3D model from single trees via Airborne Laser Scanners (ALS) data and aerial images. The approach detects and extracts single tree from ALS data and aerial images. The existing approaches are able to provide bulk segmentation from a group of trees; however, some methods focused on detection and extraction of a particular tree from ALS and images. Segmentation of a single tree within a group of trees is mostly a mission impossible since the detection of boundary lines between the trees is a tedious job and basically it is not feasible. In this approach an experimental formula based on the height of the trees was developed and applied in order to define the boundary lines between the trees. As a result, each single tree was segmented and extracted and later a 3D model was created. Extracted trees from this approach have a unique identification and attribute. The output has application in various fields of science and engineering such as forestry, urban planning, and agriculture. For example in forestry, the result can be used for study in ecologically diverse, biodiversity and ecosystem.

  13. Comparison of SLAR images and small-scale, low-sun aerial photographs.

    NASA Technical Reports Server (NTRS)

    Clark, M. M.

    1971-01-01

    A comparison of side-looking airborne radar (SLAR) images and black and white aerial photos of similar scale and illumination of an area in the Mojave Desert of California shows that aerial photos yield far more information about geology than do SLAR images because of greater resolution, tonal range, and geometric fidelity, and easier use in stereo. Nevertheless, radar can differentiate some materials or surfaces that aerial photos cannot; thus, they should be considered as complementary, rather than competing tools in geologic investigations. The most significant advantage of SLAR, however, is its freedom from the stringent conditions of weather, date, and time that are required by small-scale aerial photos taken with a specified direction and angle of illumination. Indeed, in low latitudes, SLAR is the only way to obtain small-scale images with low illumination from certain directions; moreover, in areas of nearly continuous cloudiness, radar may be the only practical source of small-scale images.

  14. Study of Automatic Image Rectification and Registration of Scanned Historical Aerial Photographs

    NASA Astrophysics Data System (ADS)

    Chen, H. R.; Tseng, Y. H.

    2016-06-01

    Historical aerial photographs directly provide good evidences of past times. The Research Center for Humanities and Social Sciences (RCHSS) of Taiwan Academia Sinica has collected and scanned numerous historical maps and aerial images of Taiwan and China. Some maps or images have been geo-referenced manually, but most of historical aerial images have not been registered since there are no GPS or IMU data for orientation assisting in the past. In our research, we developed an automatic process of matching historical aerial images by SIFT (Scale Invariant Feature Transform) for handling the great quantity of images by computer vision. SIFT is one of the most popular method of image feature extracting and matching. This algorithm extracts extreme values in scale space into invariant image features, which are robust to changing in rotation scale, noise, and illumination. We also use RANSAC (Random sample consensus) to remove outliers, and obtain good conjugated points between photographs. Finally, we manually add control points for registration through least square adjustment based on collinear equation. In the future, we can use image feature points of more photographs to build control image database. Every new image will be treated as query image. If feature points of query image match the features in database, it means that the query image probably is overlapped with control images.With the updating of database, more and more query image can be matched and aligned automatically. Other research about multi-time period environmental changes can be investigated with those geo-referenced temporal spatial data.

  15. Aberration measurement based on principal component analysis of aerial images of optimized marks

    NASA Astrophysics Data System (ADS)

    Yan, Guanyong; Wang, Xiangzhao; Li, Sikun; Yang, Jishuo; Xu, Dongbo

    2014-10-01

    We propose an aberration measurement technique based on principal component analysis of aerial images of optimized marks (AMAI-OM). Zernike aberrations are retrieved using a linear relationship between the aerial image and Zernike coefficients. The linear relationship is composed of the principal components (PCs) and regression matrix. A centering process is introduced to compensate position offsets of the measured aerial image. A new test mark is designed in order to improve the centering accuracy and theoretical accuracy of aberration measurement together. The new test marks are composed of three spaces with different widths, and their parameters are optimized by using an accuracy evaluation function. The offsets of the measured aerial image are compensated in the centering process and the adjusted PC coefficients are obtained. Then the Zernike coefficients are calculated according to these PC coefficients using a least square method. The simulations using the lithography simulators PROLITH and Dr.LiTHO validate the accuracy of our method. Compared with the previous aberration measurement technique based on principal component analysis of aerial image (AMAI-PCA), the measurement accuracy of Zernike aberrations under the real measurement condition of the aerial image is improved by about 50%.

  16. Exploration towards the modeling of gable-roofed buildings using a combination of aerial and street-level imagery

    NASA Astrophysics Data System (ADS)

    Creusen, Ivo; Hazelhoff, Lykele; de With, Peter H. N.

    2015-03-01

    Extraction of residential building properties is helpful for numerous applications, such as computer-guided feasibility analysis for solar panel placement, determination of real-estate taxes and assessment of real-estate insurance policies. Therefore, this work explores the automated modeling of buildings with a gable roof (the most common roof type within Western Europe), based on a combination of aerial imagery and street-level panoramic images. This is a challenging task, since buildings show large variations in shape, dimensions and building extensions, and may additionally be captured under non-ideal lighting conditions. The aerial images feature a coarse overview of the building due to the large capturing distance. The building footprint and an initial estimate of the building height is extracted based on the analysis of stereo aerial images. The estimated model is then refined using street-level images, which feature higher resolution and enable more accurate measurements, however, displaying a single building side only. Initial experiments indicate that the footprint dimensions of the main building can be accurately extracted from aerial images, while the building height is extracted with slightly less accuracy. By combining aerial and street-level images, we have found that the accuracies of these height measurements are significantly increased, thereby improving the overall quality of the extracted building model, and resulting in an average inaccuracy of the estimated volume below 10%.

  17. A line transect model for aerial surveys

    USGS Publications Warehouse

    Quang, Pham Xuan; Lanctot, Richard B.

    1991-01-01

    We employ a line transect method to estimate the density of the common and Pacific loon in the Yukon Flats National Wildlife Refuge from aerial survey data. Line transect methods have the advantage of automatically taking into account “visibility bias” due to detectability difference of animals at different distances from the transect line. However, line transect methods must overcome two difficulties when applied to inaccurate recording of sighting distances due to high travel speeds, so that in fact only a few reliable distance class counts are available. We propose a unimodal detection function that provides an estimate of the effective area lost due to the blind strip, under the assumption that a line of perfect detection exists parallel to the transect line. The unimodal detection function can also be applied when a blind strip is absent, and in certain instances when the maximum probability of detection is less than 100%. A simple bootstrap procedure to estimate standard error is illustrated. Finally, we present results from a small set of Monte Carlo experiments.

  18. 3D Building Modeling and Reconstruction using Photometric Satellite and Aerial Imageries

    NASA Astrophysics Data System (ADS)

    Izadi, Mohammad

    In this thesis, the problem of three dimensional (3D) reconstruction of building models using photometric satellite and aerial images is investigated. Here, two systems are pre-sented: 1) 3D building reconstruction using a nadir single-view image, and 2) 3D building reconstruction using slant multiple-view aerial images. The first system detects building rooftops in orthogonal aerial/satellite images using a hierarchical segmentation algorithm and a shadow verification approach. The heights of detected buildings are then estimated using a fuzzy rule-based method, which measures the height of a building by comparing its predicted shadow region with the actual shadow evidence in the image. This system finally generated a KML (Keyhole Markup Language) file as the output, that contains 3D models of detected buildings. The second system uses the geolocation information of a scene containing a building of interest and uploads all slant-view images that contain this scene from an input image dataset. These images are then searched automatically to choose image pairs with different views of the scene (north, east, south and west) based on the geolocation and auxiliary data accompanying the input data (metadata that describes the acquisition parameters at the capture time). The camera parameters corresponding to these images are refined using a novel point matching algorithm. Next, the system independently reconstructs 3D flat surfaces that are visible in each view using an iterative algorithm. 3D surfaces generated for all views are combined, and redundant surfaces are removed to create a complete set of 3D surfaces. Finally, the combined 3D surfaces are connected together to generate a more complete 3D model. For the experimental results, both presented systems are evaluated quantitatively and qualitatively and different aspects of the two systems including accuracy, stability, and execution time are discussed.

  19. Three dimensional monitoring of urban development by means of ortho-rectified aerial photographs and high-resolution satellite images.

    PubMed

    Ayhan, E; Erden, O; Gormus, E T

    2008-12-01

    Nowadays, cities are developing and changing rapidly due to the increases in the population and immigration. Rapid changing brings obligation to control the cities by planning. The satellite images and the aerial photographs enable us to track the urban development and provide the opportunity to get the current data about urban. With the help of these images, cities may have interrogated dynamic structures. This study is composed of three steps. In the first step, orthophoto images have been generated in order to track urban developments by using the aerial photographs and the satellite images. In this step, the panchromatic (PAN), the multi spectral (MS) and the pan-sharpened image of IKONOS satellite have been used as input satellite data and the accuracy of orthophoto images has been investigated in detail, in terms of digital elevation model (DEM), control points, input images and their properties. In the second step, a 3D city model with database has been generated with the help of orthophoto images and the vector layouts. And in the last step, up to date urban information obtained from 3D city model. This study shows that it is possible to detect the unlicensed buildings and the areas which are going to be nationalized and it also shows that it is easy to document the existing alterations in the cities with the help of current development plans and orthophoto images. And since accessing updated data is very essential to control development and monitor the temporal alterations in urban areas, in this study it is proven that the orthophoto images generated by using aerial photos and satellite images are very reliable to use in obtaining topographical information, in change detection and in city planning. When digital orthophoto images used with GIS, they provide quick decision control mechanisms and quick data collection. Besides, they help to find efficient solutions in a short time in the planning applications.

  20. Line Matching Algorithm for Aerial Image Combining image and object space similarity constraints

    NASA Astrophysics Data System (ADS)

    Wang, Jingxue; Wang, Weixi; Li, Xiaoming; Cao, Zhenyu; Zhu, Hong; Li, Miao; He, Biao; Zhao, Zhigang

    2016-06-01

    A new straight line matching method for aerial images is proposed in this paper. Compared to previous works, similarity constraints combining radiometric information in image and geometry attributes in object plane are employed in these methods. Firstly, initial candidate lines and the elevation values of lines projection plane are determined by corresponding points in neighborhoods of reference lines. Secondly, project reference line and candidate lines back forward onto the plane, and then similarity measure constraints are enforced to reduce the number of candidates and to determine the finial corresponding lines in a hierarchical way. Thirdly, "one-to-many" and "many-to-one" matching results are transformed into "one-to-one" by merging many lines into the new one, and the errors are eliminated simultaneously. Finally, endpoints of corresponding lines are detected by line expansion process combing with "image-object-image" mapping mode. Experimental results show that the proposed algorithm can be able to obtain reliable line matching results for aerial images.

  1. Critical Assessment of Object Segmentation in Aerial Image Using Geo-Hausdorff Distance

    NASA Astrophysics Data System (ADS)

    Sun, H.; Ding, Y.; Huang, Y.; Wang, G.

    2016-06-01

    Aerial Image records the large-range earth objects with the ever-improving spatial and radiometric resolution. It becomes a powerful tool for earth observation, land-coverage survey, geographical census, etc., and helps delineating the boundary of different kinds of objects on the earth both manually and automatically. In light of the geo-spatial correspondence between the pixel locations of aerial image and the spatial coordinates of ground objects, there is an increasing need of super-pixel segmentation and high-accuracy positioning of objects in aerial image. Besides the commercial software package of eCognition and ENVI, many algorithms have also been developed in the literature to segment objects of aerial images. But how to evaluate the segmentation results remains a challenge, especially in the context of the geo-spatial correspondence. The Geo-Hausdorff Distance (GHD) is proposed to measure the geo-spatial distance between the results of various object segmentation that can be done with the manual ground truth or with the automatic algorithms.Based on the early-breaking and random-sampling design, the GHD calculates the geographical Hausdorff distance with nearly-linear complexity. Segmentation results of several state-of-the-art algorithms, including those of the commercial packages, are evaluated with a diverse set of aerial images. They have different signal-to-noise ratio around the object boundaries and are hard to trace correctly even for human operators. The GHD value is analyzed to comprehensively measure the suitability of different object segmentation methods for aerial images of different spatial resolution. By critically assessing the strengths and limitations of the existing algorithms, the paper provides valuable insight and guideline for extensive research in automating object detection and classification of aerial image in the nation-wide geographic census. It is also promising for the optimal design of operational specification of remote

  2. A hybrid double-observer sightability model for aerial surveys

    USGS Publications Warehouse

    Griffin, Paul C.; Lubow, Bruce C.; Jenkins, Kurt J.; Vales, David J.; Moeller, Barbara J.; Reid, Mason; Happe, Patricia J.; Mccorquodale, Scott M.; Tirhi, Michelle J.; Schaberi, Jim P.; Beirne, Katherine

    2013-01-01

    Raw counts from aerial surveys make no correction for undetected animals and provide no estimate of precision with which to judge the utility of the counts. Sightability modeling and double-observer (DO) modeling are 2 commonly used approaches to account for detection bias and to estimate precision in aerial surveys. We developed a hybrid DO sightability model (model MH) that uses the strength of each approach to overcome the weakness in the other, for aerial surveys of elk (Cervus elaphus). The hybrid approach uses detection patterns of 2 independent observer pairs in a helicopter and telemetry-based detections of collared elk groups. Candidate MH models reflected hypotheses about effects of recorded covariates and unmodeled heterogeneity on the separate front-seat observer pair and back-seat observer pair detection probabilities. Group size and concealing vegetation cover strongly influenced detection probabilities. The pilot's previous experience participating in aerial surveys influenced detection by the front pair of observers if the elk group was on the pilot's side of the helicopter flight path. In 9 surveys in Mount Rainier National Park, the raw number of elk counted was approximately 80–93% of the abundance estimated by model MH. Uncorrected ratios of bulls per 100 cows generally were low compared to estimates adjusted for detection bias, but ratios of calves per 100 cows were comparable whether based on raw survey counts or adjusted estimates. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to DO modeling.

  3. An aerial sightability model for estimating ferruginous hawk population size

    USGS Publications Warehouse

    Ayers, L.W.; Anderson, S.H.

    1999-01-01

    Most raptor aerial survey projects have focused on numeric description of visibility bias without identifying the contributing factors or developing predictive models to account for imperfect detection rates. Our goal was to develop a sightability model for nesting ferruginous hawks (Buteo regalis) that could account for nests missed during aerial surveys and provide more accurate population estimates. Eighteen observers, all unfamiliar with nest locations in a known population, searched for nests within 300 m of flight transects via a Maule fixed-wing aircraft. Flight variables tested for their influence on nest-detection rates included aircraft speed, height, direction of travel, time of day, light condition, distance to nest, and observer experience level. Nest variables included status (active vs. inactive), condition (i.e., excellent, good, fair, poor, bad), substrate type, topography, and tree density. A multiple logistic regression model identified nest substrate type, distance to nest, and observer experience level as significant predictors of detection rates (P < 0.05). The overall model was significant (??26 = 124.4, P < 0.001, n = 255 nest observations), and the correct classification rate was 78.4%. During 2 validation surveys, observers saw 23.7% (14/59) and 36.5% (23/63) of the actual population. Sightability model predictions, with 90% confidence intervals, captured the true population in both tests. Our results indicate standardized aerial surveys, when used in conjunction with the predictive sightability model, can provide unbiased population estimates for nesting ferruginous hawks.

  4. Object-based Image Classification of Arctic Sea Ice and Melt Ponds through Aerial Photos

    NASA Astrophysics Data System (ADS)

    Miao, X.; Xie, H.; Li, Z.; Lei, R.

    2013-12-01

    The last six years have marked the lowest Arctic summer sea ice extents in the modern era, with a new record summer minimum (3.4 million km2) set on 13 September 2012. It has been predicted that the Arctic could be free of summer ice within the next 25-30. The loss of Arctic summer ice could have serious consequences, such as higher water temperature due to the positive feedback of albedo, more powerful and frequent storms, rising sea levels, diminished habitats for polar animals, and more pollution due to fossil fuel exploitation and/ or increased traffic through the Northwest/ Northeast Passage. In these processes, melt ponds play an important role in Earth's radiation balance since they strongly absorb solar radiation rather than reflecting it as snow and ice do. Therefore, it is necessary to develop the ability of predicting the sea ice/ melt pond extents and space-time evolution, which is pivotal to prepare for the variation and uncertainty of the future environment, political, economic, and military needs. A lot of efforts have been put into Arctic sea ice modeling to simulate sea ice processes. However, these sea ice models were initiated and developed based on limited field surveys, aircraft or satellite image data. Therefore, it is necessary to collect high resolution sea ice aerial photo in a systematic way to tune up, validate, and improve models. Currently there are many sea ice aerial photos available, such as Chinese Arctic Exploration (CHINARE 2008, 2010, 2012), SHEBA 1998 and HOTRAX 2005. However, manually delineating of sea ice and melt pond from these images is time-consuming and labor-intensive. In this study, we use the object-based remote sensing classification scheme to extract sea ice and melt ponds efficiently from 1,727 aerial photos taken during the CHINARE 2010. The algorithm includes three major steps as follows. (1) Image segmentation groups the neighboring pixels into objects according to the similarity of spectral and texture

  5. Aerial image simulation for partial coherent system with programming development in MATLAB

    NASA Astrophysics Data System (ADS)

    Hasan, Md. Nazmul; Rahman, Md. Momtazur; Udoy, Ariful Banna

    2014-10-01

    Aerial image can be calculated by either Abbe's method or sum of coherent system decomposition (SOCS) method for partial coherent system. This paper introduces a programming with Matlab code that changes the analytical representation of Abbe's method to the matrix form, which has advantages for both Abbe's method and SOCS since matrix calculation is easier than double integration over object plane or pupil plane. First a singular matrix P is derived from a pupil function and effective light source in the spatial frequency domain. By applying Singular Value Decomposition (SVD) to the matrix P, eigenvalues and eigenfunctions are obtained. The aerial image can then be computed by the eigenvalues and eigenfunctions without calculation of Transmission Cross Coefficient (TCC). The aerial final image is almost identical as an original cross mask and the intensity distribution on image plane shows that it is almost uniform across the linewidth of the mask.

  6. A Comparison of Visual Statistics for the Image Enhancement of FORESITE Aerial Images with Those of Major Image Classes

    NASA Technical Reports Server (NTRS)

    Johnson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.; Hines, Glenn D.

    2006-01-01

    Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally with the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging--terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

  7. [Automatic houses detection with color aerial images based on image segmentation].

    PubMed

    He, Pei-Pei; Wan, You-Chuan; Jiang, Peng-Rui; Gao, Xian-Jun; Qin, Jia-Xin

    2014-07-01

    In order to achieve housing automatic detection from high-resolution aerial imagery, the present paper utilized the color information and spectral characteristics of the roofing material, with the image segmentation theory, to study the housing automatic detection method. Firstly, This method proposed in this paper converts the RGB color space to HIS color space, uses the characteristics of each component of the HIS color space and the spectral characteristics of the roofing material for image segmentation to isolate red tiled roofs and gray cement roof areas, and gets the initial segmentation housing areas by using the marked watershed algorithm. Then, region growing is conducted in the hue component with the seed segment sample by calculating the average hue in the marked region. Finally through the elimination of small spots and rectangular fitting process to obtain a clear outline of the housing area. Compared with the traditional pixel-based region segmentation algorithm, the improved method proposed in this paper based on segment growing is in a one-dimensional color space to reduce the computation without human intervention, and can cater to the geometry information of the neighborhood pixels so that the speed and accuracy of the algorithm has been significantly improved. A case study was conducted to apply the method proposed in this paper to high resolution aerial images, and the experimental results demonstrate that this method has a high precision and rational robustness.

  8. High Density Aerial Image Matching: State-Of and Future Prospects

    NASA Astrophysics Data System (ADS)

    Haala, N.; Cavegn, S.

    2016-06-01

    Ongoing innovations in matching algorithms are continuously improving the quality of geometric surface representations generated automatically from aerial images. This development motivated the launch of the joint ISPRS/EuroSDR project "Benchmark on High Density Aerial Image Matching", which aims on the evaluation of photogrammetric 3D data capture in view of the current developments in dense multi-view stereo-image matching. Originally, the test aimed on image based DSM computation from conventional aerial image flights for different landuse and image block configurations. The second phase then put an additional focus on high quality, high resolution 3D geometric data capture in complex urban areas. This includes both the extension of the test scenario to oblique aerial image flights as well as the generation of filtered point clouds as additional output of the respective multi-view reconstruction. The paper uses the preliminary outcomes of the benchmark to demonstrate the state-of-the-art in airborne image matching with a special focus of high quality geometric data capture in urban scenarios.

  9. A two-camera imaging system for pest detection and aerial application

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This presentation reports on the design and testing of an airborne two-camera imaging system for pest detection and aerial application assessment. The system consists of two digital cameras with 5616 x 3744 effective pixels. One camera captures normal color images with blue, green and red bands, whi...

  10. A low-cost dual-camera imaging system for aerial applicators

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agricultural aircraft provide a readily available remote sensing platform as low-cost and easy-to-use consumer-grade cameras are being increasingly used for aerial imaging. In this article, we report on a dual-camera imaging system we recently assembled that can capture RGB and near-infrared (NIR) i...

  11. Aerial image mosaics built using images with vegetation index pre-calculated

    NASA Astrophysics Data System (ADS)

    Rosendo Candido, Leandro; de Castro Jorge, Lúcio André; Luppe, Maximiliam

    2016-10-01

    Precision agriculture (PA) has offered a multitude of benefits to farmers, such as cost reduction, accuracy and speed in decision making. Among the tools that work with PA, the aerial image mosaics have key role in accurate mapping of diseases and pests in crops. A mosaic is the combination of multiple images, creating a new image that covers the property or plots accurately. One of the important analysis for farmers is based on the properties of the reflectance in each range of the electromagnetic spectrum of vegetation. Performing mathematical combinations of the different spectral bands has a better understanding of the spectral response of the vegetation. These combinations are called vegetation index (VI) and are useful for the control of the biomass, water content in leaf, chlorophyll content and others. It is usually calculated VI after the construction of the mosaic, as well the farmer has an accurate analysis of its vegetation. However, building a mosaic of images, it has a high computational cost, taking hours to complete and then apply the VI and to have the first test results. In order to reduce the computational cost of this process, this work aims to present a mosaic of images constructed from images with the VI already pre-calculated providing faster analysis to the farmer, given the fact that applying VI on the image came a this reduction in density image and thus have the gain in computational cost to build the mosaic.

  12. The cleaning effects of mask aerial image after FIB repair in sub-80nm node

    NASA Astrophysics Data System (ADS)

    Lee, Hyemi; Jeong, Goomin; Jeong, Sookyeong; Kim, Sangchul; Han, Oscar

    2007-10-01

    The Aerial Image Measurement Tool (AIMS) can estimate the wafer printability without exposure to wafer by using scanner. Since measured aerial images are similar with wafer prints, using AIMS becomes normal for verifying issue points of a mask. Also because mask design rule continues to shrink, defects and CD uniformity are at issues as factors decreasing mask yield. Occurred defects on a mask are removed by existing mask repair techniques such as nanomachining, electron beam and focused ion beam. But damages and contaminants by chemical and physical action are found on the mask surface and contaminants above special size lead to defects on a wafer. So cleaning has been necessary after repair process and detergency has been important. Before AIMS measurement, cleaning is done to make same condition with shipped mask, which method brings repeated process - repair and cleaning - if aerial image was not usual. So cleaning effect after the FIB repair is tested by using the AIMS to find the optimized process minimizing the repeated process and to get similar scanner results. First, programmed defect mask that includes various defect size and type is manufactured on some kinds of patterns in DRAM device and sub-80nm tech. Next the defects on the programmed mask are repaired by FIB repair machine. And aerial images are compared after the chemical cleaning, non-chemical cleaning and without cleaning. Finally, approximate aerial images to scanner results are taken regardless of cleaning process. It means that residue originated from repair process doesn't affect aerial images and flexible process is possible between AIMS, repair and cleaning process. But as the effect of minute particles and contaminations will be increased if pattern size is much smaller, it needs to reconfirm the effect below the sub-60nm in DRAM device.

  13. Comparison of analysis techniques for aerial image metrology on advanced photomask

    NASA Astrophysics Data System (ADS)

    Hwang, Seolchong; Woo, Sungha; Jang, Heeyeon; Lee, Youngmo; Kim, Sangpyo; Yang, Hyunjo; Schulz, Kristian; Garetto, Anthony

    2016-05-01

    The standard method for defect disposition and verification of repair success in the mask shop is through the utilization of the aerial imaging platform, AIMSTM. The CD (Critical Dimension) deviation of the defective or repaired region as well as the pattern shift can be calculated by comparing the measured aerial images of this region to that of a reference. Through this analysis it can be determined if the defect or repaired region will be printed on the wafer under the illumination conditions of the scanner. The analysis of the measured aerial images from the AIMSTM are commonly performed manually using the analysis software available on the system or with the help of an analysis software called RV (Repair Verification). Because the process is manual, it is not standardized and is subject to operator variations. This method of manual aerial image analysis is time consuming, dependent on the skill level of the operator and significantly contributes to the overall mask manufacturing process flow. AutoAnalysis (AA), the first application available for the FAVOR® platform, provides fully automated analysis of AIMSTM aerial images [1] and runs in parallel to the measurement of the aerial images. In this paper, we investigate the initial AutoAnalysis performance compared to the conventional method using RV and its application to a production environment. The evaluation is based on the defect CD of three pattern types: contact holes, dense line and spaces and peripheral structure. The defect analysis results for different patterns and illumination conditions will be correlated and challenges in transitioning to the new approach will be discussed.

  14. Model-based conifer crown surface reconstruction from multi-ocular high-resolution aerial imagery

    NASA Astrophysics Data System (ADS)

    Sheng, Yongwei

    2000-12-01

    Tree crown parameters such as width, height, shape and crown closure are desirable in forestry and ecological studies, but they are time-consuming and labor intensive to measure in the field. The stereoscopic capability of high-resolution aerial imagery provides a way to crown surface reconstruction. Existing photogrammetric algorithms designed to map terrain surfaces, however, cannot adequately extract crown surfaces, especially for steep conifer crowns. Considering crown surface reconstruction in a broader context of tree characterization from aerial images, we develop a rigorous perspective tree image formation model to bridge image-based tree extraction and crown surface reconstruction, and an integrated model-based approach to conifer crown surface reconstruction. Based on the fact that most conifer crowns are in a solid geometric form, conifer crowns are modeled as a generalized hemi-ellipsoid. Both the automatic and semi-automatic approaches are investigated to optimal tree model development from multi-ocular images. The semi-automatic 3D tree interpreter developed in this thesis is able to efficiently extract reliable tree parameters and tree models in complicated tree stands. This thesis starts with a sophisticated stereo matching algorithm, and incorporates tree models to guide stereo matching. The following critical problems are addressed in the model-based surface reconstruction process: (1) the problem of surface model composition from tree models, (2) the occlusion problem in disparity prediction from tree models, (3) the problem of integrating the predicted disparities into image matching, (4) the tree model edge effect reduction on the disparity map, (5) the occlusion problem in orthophoto production, and (6) the foreshortening problem in image matching, which is very serious for conifer crown surfaces. Solutions to the above problems are necessary for successful crown surface reconstruction. The model-based approach was applied to recover the

  15. Aerial thermography from low-cost UAV for the generation of thermographic digital terrain models

    NASA Astrophysics Data System (ADS)

    Lagüela, S.; Díaz-Vilariño, L.; Roca, D.; Lorenzo, H.

    2015-03-01

    Aerial thermography is performed from a low-cost aerial vehicle, copter type, for the acquisition of data of medium-size areas, such as neighbourhoods, districts or small villages. Thermographic images are registered in a mosaic subsequently used for the generation of a thermographic digital terrain model (DTM). The thermographic DTM can be used with several purposes, from classification of land uses according to their thermal response to the evaluation of the building prints as a function of their energy performance, land and water management. In the particular case of buildings, apart from their individual evaluation and roof inspection, the availability of thermographic information on a DTM allows for the spatial contextualization of the buildings themselves and the general study of the surrounding area for the detection of global effects such as heat islands.

  16. Aerial-image enables diagrams and animation to be inserted in motion pictures

    NASA Technical Reports Server (NTRS)

    Andrews, S. J., Jr.; Tressel, G. W.

    1967-01-01

    Aerial-image unit makes it possible to insert diagrams and animation into live motion pictures, and also lift an element from a confusing background by suppressing general details. The unit includes a combination of two separate lens systems, the camera-projector system and the field lens system.

  17. A low-cost single-camera imaging system for aerial applicators

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agricultural aircraft provide a readily available and versatile platform for airborne remote sensing. Although various airborne imaging systems are available, most of these systems are either too expensive or too complex to be of practical use for aerial applicators. The objective of this study was ...

  18. Registering aerial video images using the projective constraint.

    PubMed

    Jackson, Brian P; Goshtasby, A Ardeshir

    2010-03-01

    To separate object motion from camera motion in an aerial video, consecutive frames are registered at their planar background. Feature points are selected in consecutive frames and those that belong to the background are identified using the projective constraint. Corresponding background feature points are then used to register and align the frames. By aligning video frames at the background and knowing that objects move against the background, a means to detect and track moving objects is provided. Only scenes with planar background are considered in this study. Experimental results show improvement in registration accuracy when using the projective constraint to determine the registration parameters as opposed to finding the registration parameters without the projective constraint.

  19. An Aerial-Image Dense Matching Approach Based on Optical Flow Field

    NASA Astrophysics Data System (ADS)

    Yuan, Wei; Chen, Shiyu; Zhang, Yong; Gong, Jianya; Shibasaki, Ryosuke

    2016-06-01

    Dense matching plays an important role in many fields, such as DEM (digital evaluation model) producing, robot navigation and 3D environment reconstruction. Traditional approaches may meet the demand of accuracy. But the calculation time and out puts density is hardly be accepted. Focus on the matching efficiency and complex terrain surface matching feasibility an aerial image dense matching method based on optical flow field is proposed in this paper. First, some high accurate and uniformed control points are extracted by using the feature based matching method. Then the optical flow is calculated by using these control points, so as to determine the similar region between two images. Second, the optical flow field is interpolated by using the multi-level B-spline interpolation in the similar region and accomplished the pixel by pixel coarse matching. Final, the results related to the coarse matching refinement based on the combined constraint, which recognizes the same points between images. The experimental results have shown that our method can achieve per-pixel dense matching points, the matching accuracy achieves sub-pixel level, and fully meet the three-dimensional reconstruction and automatic generation of DSM-intensive matching's requirements. The comparison experiments demonstrated that our approach's matching efficiency is higher than semi-global matching (SGM) and Patch-based multi-view stereo matching (PMVS) which verifies the feasibility and effectiveness of the algorithm.

  20. Intra-field CDU map correlation between SEMs and aerial image characterization

    NASA Astrophysics Data System (ADS)

    Ning, Guoxiang; Philipp, Peter; Litt, Lloyd C.; Meusemann, Stefan; Thaler, Thomas; Schulz, Kristian; Tschinkl, Martin; Ackmann, Paul

    2014-09-01

    Reticle critical dimension uniformity (CDU) is one of the major sources of wafer CD variations which include both inter-field variations and intra-field variations. Generally, wafer critical dimension (CD) measurement sample size interfield is much less than intra-field. Intra-field CDU correction requires time-consumption of metrology. In order to improve wafer intra-field CDU, several methods can be applied such as intra-field dose correction to improve wafer intra-field CDU. Corrections can be based on CD(SEM) or aerial image metrology data from the reticle. Reticle CDU and wafer CDU maps are based on scanning electron microscope (SEM) metrology, while reticle inspection intensity mapping (NuFLare 6000) and wafer level critical dimension (WLCD) utilize aerial images or optical techniques. Reticle inspecton tools such as those from KLA and NuFlare, offer the ability to collect optical measurement data to produce an optical CDU map. WLCD of Zeiss has the advantage of using the same illumination condition as the scanner to measure the aerial images or optical CD. In this study, the intra-field wafer CDU map correlation between SEMs and aerial images are characterized. The layout of metrology structures is very important for the correlation between wafer intra-field CDU, measured by SEM, and the CDU determined by aerial images. The selection of metrology structures effects on the correlation to SEM CD to wafer is also demonstrated. Both reticle CDU, intensity CDU and WLCD are candidates for intra-field wafer CDU characterization and the advantages and limitations of each approach are discussed.

  1. Aerial Vehicle Surveys of other Planetary Atmospheres and Surfaces: Imaging, Remote-sensing, and Autonomy Technology Requirements

    NASA Technical Reports Server (NTRS)

    Young, Larry A.; Pisanich, Gregory; Ippolito, Corey; Alena, Rick

    2005-01-01

    The objective of this paper is to review the anticipated imaging and remote-sensing technology requirements for aerial vehicle survey missions to other planetary bodies in our Solar system that can support in-atmosphere flight. In the not too distant future such planetary aerial vehicle (a.k.a. aerial explorers) exploration missions will become feasible. Imaging and remote-sensing observations will be a key objective for these missions. Accordingly, it is imperative that optimal solutions in terms of imaging acquisition and real-time autonomous analysis of image data sets be developed for such vehicles.

  2. Registration of multitemporal aerial optical images using line features

    NASA Astrophysics Data System (ADS)

    Zhao, Chenyang; Goshtasby, A. Ardeshir

    2016-07-01

    Registration of multitemporal images is generally considered difficult because scene changes can occur between the times the images are obtained. Since the changes are mostly radiometric in nature, features are needed that are insensitive to radiometric differences between the images. Lines are geometric features that represent straight edges of rigid man-made structures. Because such structures rarely change over time, lines represent stable geometric features that can be used to register multitemporal remote sensing images. An algorithm to establish correspondence between lines in two images of a planar scene is introduced and formulas to relate the parameters of a homography transformation to the parameters of corresponding lines in images are derived. Results of the proposed image registration on various multitemporal images are presented and discussed.

  3. Enabling high-quality observations of surface imperviousness for water runoff modelling from unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Tokarczyk, Piotr; Leitao, Joao Paulo; Rieckermann, Jörg; Schindler, Konrad; Blumensaat, Frank

    2015-04-01

    Modelling rainfall-runoff in urban areas is increasingly applied to support flood risk assessment particularly against the background of a changing climate and an increasing urbanization. These models typically rely on high-quality data for rainfall and surface characteristics of the area. While recent research in urban drainage has been focusing on providing spatially detailed rainfall data, the technological advances in remote sensing that ease the acquisition of detailed land-use information are less prominently discussed within the community. The relevance of such methods increase as in many parts of the globe, accurate land-use information is generally lacking, because detailed image data is unavailable. Modern unmanned air vehicles (UAVs) allow acquiring high-resolution images on a local level at comparably lower cost, performing on-demand repetitive measurements, and obtaining a degree of detail tailored for the purpose of the study. In this study, we investigate for the first time the possibility to derive high-resolution imperviousness maps for urban areas from UAV imagery and to use this information as input for urban drainage models. To do so, an automatic processing pipeline with a modern classification method is tested and applied in a state-of-the-art urban drainage modelling exercise. In a real-life case study in the area of Lucerne, Switzerland, we compare imperviousness maps generated from a consumer micro-UAV and standard large-format aerial images acquired by the Swiss national mapping agency (swisstopo). After assessing their correctness, we perform an end-to-end comparison, in which they are used as an input for an urban drainage model. Then, we evaluate the influence which different image data sources and their processing methods have on hydrological and hydraulic model performance. We analyze the surface runoff of the 307 individual sub-catchments regarding relevant attributes, such as peak runoff and volume. Finally, we evaluate the model

  4. Evaluation of Color Settings in Aerial Images with the Use of Eye-Tracking User Study

    NASA Astrophysics Data System (ADS)

    Mirijovsky, J.; Popelka, S.

    2016-06-01

    The main aim of presented paper is to find the most realistic and preferred color settings for four different types of surfaces on the aerial images. This will be achieved through user study with the use of eye-movement recording. Aerial images taken by the unmanned aerial system were used as stimuli. From each image, squared crop area containing one of the studied types of surfaces (asphalt, concrete, water, soil, and grass) was selected. For each type of surface, the real value of reflectance was found with the use of precise spectroradiometer ASD HandHeld 2 which measures the reflectance. The device was used at the same time as aerial images were captured, so lighting conditions and state of vegetation were equal. The spectral resolution of the ASD device is better than 3.0 nm. For defining the RGB values of selected type of surface, the spectral reflectance values recorded by the device were merged into wider groups. Finally, we get three groups corresponding to RGB color system. Captured images were edited with the graphic editor Photoshop CS6. Contrast, clarity, and brightness were edited for all surface types on images. Finally, we get a set of 12 images of the same area with different color settings. These images were put into the grid and used as stimuli for the eye-tracking experiment. Eye-tracking is one of the methods of usability studies and it is considered as relatively objective. Eye-tracker SMI RED 250 with the sampling frequency 250 Hz was used in the study. As respondents, a group of 24 students of Geoinformatics and Geography was used. Their task was to select which image in the grid has the best color settings. The next task was to select which color settings they prefer. Respondents' answers were evaluated and the most realistic and most preferable color settings were found. The advantage of the eye-tracking evaluation was that also the process of the selection of the answers was analyzed. Areas of Interest were marked around each image in the

  5. First results for an image processing workflow for hyperspatial imagery acquired with a low-cost unmanned aerial vehicle (UAV).

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Very high-resolution images from unmanned aerial vehicles (UAVs) have great potential for use in rangeland monitoring and assessment, because the imagery fills the gap between ground-based observations and remotely sensed imagery from aerial or satellite sensors. However, because UAV imagery is ofte...

  6. Observation of coral reefs on Ishigaki Island, Japan, using Landsat TM images and aerial photographs

    SciTech Connect

    Matsunaga, Tsuneo; Kayanne, Hajime

    1997-06-01

    Ishigaki Island is located at the southwestern end of Japanese Islands and famous for its fringing coral reefs. More than twenty LANDSAT TM images in twelve years and aerial photographs taken on 1977 and 1994 were used to survey two shallow reefs on this island, Shiraho and Kabira. Intensive field surveys were also conducted in 1995. All satellite images of Shiraho were geometrically corrected and overlaid to construct a multi-date satellite data set. The effects of solar elevation and tide on satellite imagery were studied with this data set. The comparison of aerial and satellite images indicated that significant changes occurred between 1977 and 1984 in Kabira: rapid formation in the western part and decrease in the eastern part of dark patches. The field surveys revealed that newly formed dark patches in the west contain young corals. These results suggest that remote sensing is useful for not only mapping but also monitoring of shallow coral reefs.

  7. Image Dependent Relative Formation Navigation for Autonomous Aerial Refueling

    DTIC Science & Technology

    2011-03-01

    sensors that do not emit any electro- magnetic energy) to reduce the likelihood of detection when operating in unfriendly areas of interest. This would...modification and analysis of the images in other ways. By modifying the values of the pixels, images can be sharpened, smoothed, darken, lightened , and

  8. Decentralized robust nonlinear model predictive controller for unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Garcia Garreton, Gonzalo A.

    The nonlinear and unsteady nature of aircraft aerodynamics together with limited practical range of controls and state variables make the use of the linear control theory inadequate especially in the presence of external disturbances, such as wind. In the classical approach, aircraft are controlled by multiple inner and outer loops, designed separately and sequentially. For unmanned aerial systems in particular, control technology must evolve to a point where autonomy is extended to the entire mission flight envelope. This requires advanced controllers that have sufficient robustness, track complex trajectories, and use all the vehicles control capabilities at higher levels of accuracy. In this work, a robust nonlinear model predictive controller is designed to command and control an unmanned aerial system to track complex tight trajectories in the presence of internal and external perturbance. The Flight System developed in this work achieves the above performance by using: 1. A nonlinear guidance algorithm that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2. A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3. An artificial neural network, designed to adaptively estimate and provide aerodynamic and propulsive forces in real-time; and 4. A mixed sensitivity approach that enhances the robustness for a nonlinear model predictive controller overcoming the effect of un-modeled dynamics, external disturbances such as wind, and measurement additive perturbations, such as noise and biases. These elements have been integrated and tested in simulation and with previously stored flight test data and shown to be feasible.

  9. Detection and clustering of features in aerial images by neuron network-based algorithm

    NASA Astrophysics Data System (ADS)

    Vozenilek, Vit

    2015-12-01

    The paper presents the algorithm for detection and clustering of feature in aerial photographs based on artificial neural networks. The presented approach is not focused on the detection of specific topographic features, but on the combination of general features analysis and their use for clustering and backward projection of clusters to aerial image. The basis of the algorithm is a calculation of the total error of the network and a change of weights of the network to minimize the error. A classic bipolar sigmoid was used for the activation function of the neurons and the basic method of backpropagation was used for learning. To verify that a set of features is able to represent the image content from the user's perspective, the web application was compiled (ASP.NET on the Microsoft .NET platform). The main achievements include the knowledge that man-made objects in aerial images can be successfully identified by detection of shapes and anomalies. It was also found that the appropriate combination of comprehensive features that describe the colors and selected shapes of individual areas can be useful for image analysis.

  10. EROS main image file - A picture perfect database for Landsat imagery and aerial photography

    NASA Technical Reports Server (NTRS)

    Jack, R. F.

    1984-01-01

    The Earth Resources Observation System (EROS) Program was established by the U.S. Department of the Interior in 1966 under the administration of the Geological Survey. It is primarily concerned with the application of remote sensing techniques for the management of natural resources. The retrieval system employed to search the EROS database is called INORAC (Inquiry, Ordering, and Accounting). A description is given of the types of images identified in EROS, taking into account Landsat imagery, Skylab images, Gemini/Apollo photography, and NASA aerial photography. Attention is given to retrieval commands, geographic coordinate searching, refinement techniques, various online functions, and questions regarding the access to the EROS Main Image File.

  11. Counter Unmanned Aerial Systems Testing: Evaluation of VIS SWIR MWIR and LWIR passive imagers.

    SciTech Connect

    Birch, Gabriel Carlisle; Woo, Bryana Lynn

    2017-01-01

    This report contains analysis of unmanned aerial systems as imaged by visible, short-wave infrared, mid-wave infrared, and long-wave infrared passive devices. Testing was conducted at the Nevada National Security Site (NNSS) during the week of August 15, 2016. Target images in all spectral bands are shown and contrast versus background is reported. Calculations are performed to determine estimated pixels-on-target for detection and assessment levels, and the number of pixels needed to cover a hemisphere for detection or assessment at defined distances. Background clutter challenges are qualitatively discussed for different spectral bands, and low contrast scenarios are highlighted for long-wave infrared imagers.

  12. Mobile Aerial Tracking and Imaging System (MATRIS) for Aeronautical Research

    NASA Technical Reports Server (NTRS)

    Banks, Daniel W.; Blanchard, R. C.; Miller, G. M.

    2004-01-01

    A mobile, rapidly deployable ground-based system to track and image targets of aeronautical interest has been developed. Targets include reentering reusable launch vehicles (RLVs) as well as atmospheric and transatmospheric vehicles. The optics were designed to image targets in the visible and infrared wavelengths. To minimize acquisition cost and development time, the system uses commercially available hardware and software where possible. The conception and initial funding of this system originated with a study of ground-based imaging of global aerothermal characteristics of RLV configurations. During that study NASA teamed with the Missile Defense Agency/Innovative Science and Technology Experimentation Facility (MDA/ISTEF) to test techniques and analysis on two Space Shuttle flights.

  13. Semi-auto assessment system on building damage caused by landslide disaster with high-resolution satellite and aerial images

    NASA Astrophysics Data System (ADS)

    Sun, Bo; Xu, Qihua; He, Jun; Ge, Fengxiang; Wang, Ying

    2015-10-01

    In recent years, earthquake and heavy rain have triggered more and more landslides, which have caused serious economic losses. The timely detection of the disaster area and the assessment of the hazard are necessary and primary for disaster mitigation and relief. As high-resolution satellite and aerial images have been widely used in the field of environmental monitoring and disaster management, the damage assessment by processing satellite and aerial images has become a hot spot of research work. The rapid assessment of building damage caused by landslides with high-resolution satellite or aerial images is the focus of this article. In this paper, after analyzing the morphological characteristics of the landslide disaster, we proposed a set of criteria for rating building damage, and designed a semi-automatic evaluation system. The system is applied to the satellite and aerial images processing. The performance of the experiments demonstrated the effectiveness of our system.

  14. Aerial imaging with manned aircraft for precision agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the last two decades, numerous commercial and custom-built airborne imaging systems have been developed and deployed for diverse remote sensing applications, including precision agriculture. More recently, unmanned aircraft systems (UAS) have emerged as a versatile and cost-effective platform f...

  15. Evaluation of orthomosics and digital surface models derived from aerial imagery for crop mapping

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Orthomosics derived from aerial imagery acquired by consumer-grade cameras have been used for crop mapping. However, digital surface models (DSM) derived from aerial imagery have not been evaluated for this application. In this study, a novel method was proposed to extract crop height from DSM and t...

  16. Parameter-Based Performance Analysis of Object-Based Image Analysis Using Aerial and Quikbird-2 Images

    NASA Astrophysics Data System (ADS)

    Kavzoglu, T.; Yildiz, M.

    2014-09-01

    Opening new possibilities for research, very high resolution (VHR) imagery acquired by recent commercial satellites and aerial systems requires advanced approaches and techniques that can handle large volume of data with high local variance. Delineation of land use/cover information from VHR images is a hot research topic in remote sensing. In recent years, object-based image analysis (OBIA) has become a popular solution for image analysis tasks as it considers shape, texture and content information associated with the image objects. The most important stage of OBIA is the image segmentation process applied prior to classification. Determination of optimal segmentation parameters is of crucial importance for the performance of the selected classifier. In this study, effectiveness and applicability of the segmentation method in relation to its parameters was analysed using two VHR images, an aerial photo and a Quickbird-2 image. Multi-resolution segmentation technique was employed with its optimal parameters of scale, shape and compactness that were defined after an extensive trail process on the data sets. Nearest neighbour classifier was applied on the segmented images, and then the accuracy assessment was applied. Results show that segmentation parameters have a direct effect on the classification accuracy, and low values of scale-shape combinations produce the highest classification accuracies. Also, compactness parameter was found to be having minimal effect on the construction of image objects, hence it can be set to a constant value in image classification.

  17. A semi-automated single day image differencing technique to identify animals in aerial imagery.

    PubMed

    Terletzky, Pat; Ramsey, Robert Douglas

    2014-01-01

    Our research presents a proof-of-concept that explores a new and innovative method to identify large animals in aerial imagery with single day image differencing. We acquired two aerial images of eight fenced pastures and conducted a principal component analysis of each image. We then subtracted the first principal component of the two pasture images followed by heuristic thresholding to generate polygons. The number of polygons represented the number of potential cattle (Bos taurus) and horses (Equus caballus) in the pasture. The process was considered semi-automated because we were not able to automate the identification of spatial or spectral thresholding values. Imagery was acquired concurrently with ground counts of animal numbers. Across the eight pastures, 82% of the animals were correctly identified, mean percent commission was 53%, and mean percent omission was 18%. The high commission error was due to small mis-alignments generated from image-to-image registration, misidentified shadows, and grouping behavior of animals. The high probability of correctly identifying animals suggests short time interval image differencing could provide a new technique to enumerate wild ungulates occupying grassland ecosystems, especially in isolated or difficult to access areas. To our knowledge, this was the first attempt to use standard change detection techniques to identify and enumerate large ungulates.

  18. Land Use Classification from Vhr Aerial Images Using Invariant Colour Components and Texture

    NASA Astrophysics Data System (ADS)

    Movia, A.; Beinat, A.; Sandri, T.

    2016-06-01

    Very high resolution (VHR) aerial images can provide detailed analysis about landscape and environment; nowadays, thanks to the rapid growing airborne data acquisition technology an increasing number of high resolution datasets are freely available. In a VHR image the essential information is contained in the red-green-blue colour components (RGB) and in the texture, therefore a preliminary step in image analysis concerns the classification in order to detect pixels having similar characteristics and to group them in distinct classes. Common land use classification approaches use colour at a first stage, followed by texture analysis, particularly for the evaluation of landscape patterns. Unfortunately RGB-based classifications are significantly influenced by image setting, as contrast, saturation, and brightness, and by the presence of shadows in the scene. The classification methods analysed in this work aim to mitigate these effects. The procedures developed considered the use of invariant colour components, image resampling, and the evaluation of a RGB texture parameter for various increasing sizes of a structuring element. To identify the most efficient solution, the classification vectors obtained were then processed by a K-means unsupervised classifier using different metrics, and the results were compared with respect to corresponding user supervised classifications. The experiments performed and discussed in the paper let us evaluate the effective contribution of texture information, and compare the most suitable vector components and metrics for automatic classification of very high resolution RGB aerial images.

  19. Real-time aerial multispectral imaging solutions using dichroic filter arrays

    NASA Astrophysics Data System (ADS)

    Chandler, Eric V.; Fish, David E.

    2014-06-01

    The next generation of multispectral sensors and cameras needs to deliver significant improvements in size, weight, portability, and spectral band customization to support widespread commercial deployment for a variety of purposebuilt aerial, unmanned, and scientific applications. The benefits of multispectral imaging are well established for applications including machine vision, biomedical, authentication, and remote sensing environments - but many aerial and OEM solutions require more compact, robust, and cost-effective production cameras to realize these benefits. A novel implementation uses micropatterning of dichroic filters into Bayer and custom mosaics, enabling true real-time multispectral imaging with simultaneous multi-band image acquisition. Consistent with color camera image processing, individual spectral channels are de-mosaiced with each channel providing an image of the field of view. We demonstrate recent results of 4-9 band dichroic filter arrays in multispectral cameras using a variety of sensors including linear, area, silicon, and InGaAs. Specific implementations range from hybrid RGB + NIR sensors to custom sensors with applicationspecific VIS, NIR, and SWIR spectral bands. Benefits and tradeoffs of multispectral sensors using dichroic filter arrays are compared with alternative approaches - including their passivity, spectral range, customization options, and development path. Finally, we report on the wafer-level fabrication of dichroic filter arrays on imaging sensors for scalable production of multispectral sensors and cameras.

  20. Real-time observations of extreme-ultraviolet aerial images by fluorescence microimaging

    SciTech Connect

    La Fontaine, B. ); White, D.L. ); Wood, O.R. II ); MacDowell, A.A.; Tan, Z. ); Taylor, G.N. ); Tennant, D.M. ); Hulbert, S.L. )

    1994-11-01

    A new technique, fluorescence microimaging (FMI), using single-crystal phosphors was used to look directly at aerial images produced by an extreme-ultraviolet (EUV) camera operating at a wavelength of 139 A. The achieved spatial resolution was estimated to be [similar to]0.2 [mu]m. A comparison of this technique with the usual resist-exposure scanning electron microscopy inspection technique as a means of focusing a 20[times]EUV Schwarzschild camera was performed. FMI could in principle be improved to view fluorescent images with features as small as 0.07 [mu]m, in real time.

  1. Using aberration test patterns to optimize the performance of EUV aerial imaging microscopes

    SciTech Connect

    Mochi, Iacopo; Goldberg, Kenneth A.; Miyakawa, Ryan; Naulleau, Patrick; Han, Hak-Seung; Huh, Sungmin

    2009-06-16

    The SEMATECH Berkeley Actinic Inspection Tool (AIT) is a prototype EUV-wavelength zoneplate microscope that provides high quality aerial image measurements of EUV reticles. To simplify and improve the alignment procedure we have created and tested arrays of aberration-sensitive patterns on EUV reticles and we have compared their images collected with the AIT to the expected shapes obtained by simulating the theoretical wavefront of the system. We obtained a consistent measure of coma and astigmatism in the center of the field of view using two different patterns, revealing a misalignment condition in the optics.

  2. Three - Dimensional Image Generation from an Aerial Photograph.

    DTIC Science & Technology

    1987-09-01

    expected of a higher resolution terrain model . .7 L,,I- 4.. 4.% 6 ,T. !AcceSston For NTIS G A.& I t-b N 𔃼 T (I TAR Ap . . ..... -. ... . . .% t !02 f...elevation data, and yielded less desirable results than could be expected of a higher resolition terrain model . Lj I TABLE OF CONTENTS !. INTRODUCTION...generate a different perspective of a terrain model . This may be used to generate different views that a pilot of an aircraft could expect following

  3. Film cameras or digital sensors? The challenge ahead for aerial imaging

    USGS Publications Warehouse

    Light, D.L.

    1996-01-01

    Cartographic aerial cameras continue to play the key role in producing quality products for the aerial photography business, and specifically for the National Aerial Photography Program (NAPP). One NAPP photograph taken with cameras capable of 39 lp/mm system resolution can contain the equivalent of 432 million pixels at 11 ??m spot size, and the cost is less than $75 per photograph to scan and output the pixels on a magnetic storage medium. On the digital side, solid state charge coupled device linear and area arrays can yield quality resolution (7 to 12 ??m detector size) and a broader dynamic range. If linear arrays are to compete with film cameras, they will require precise attitude and positioning of the aircraft so that the lines of pixels can be unscrambled and put into a suitable homogeneous scene that is acceptable to an interpreter. Area arrays need to be much larger than currently available to image scenes competitive in size with film cameras. Analysis of the relative advantages and disadvantages of the two systems show that the analog approach is more economical at present. However, as arrays become larger, attitude sensors become more refined, global positioning system coordinate readouts become commonplace, and storage capacity becomes more affordable, the digital camera may emerge as the imaging system for the future. Several technical challenges must be overcome if digital sensors are to advance to where they can support mapping, charting, and geographic information system applications.

  4. Computer vision-based orthorectification and georeferencing of aerial image sets

    NASA Astrophysics Data System (ADS)

    Faraji, Mohammad Reza; Qi, Xiaojun; Jensen, Austin

    2016-07-01

    Generating a georeferenced mosaic map from unmanned aerial vehicle (UAV) imagery is a challenging task. Direct and indirect georeferencing methods may fail to generate an accurate mosaic map due to the erroneous exterior orientation parameters stored in the inertial measurement unit (IMU), erroneous global positioning system (GPS) data, and difficulty in locating ground control points (GCPs) or having a sufficient number of GCPs. This paper presents a practical framework to orthorectify and georeference aerial images using the robust features-based matching method. The proposed georeferencing process is fully automatic and does not require any GCPs. It is also a near real-time process which can be used to determine whether aerial images taken by UAV cover the entire target area. We also extend this framework to use the inverse georeferencing process to update the IMU/GPS data which can be further used to calibrate the camera of the UAV, reduce IMU/GPS errors, and thus produce more accurate mosaic maps by employing any georeferencing method. Our experiments demonstrate the effectiveness of the proposed framework in producing comparable mosaic maps as commercial software Agisoft and the effectiveness of the extended framework in significantly reducing the errors in the IMU/GPS data.

  5. Moment feature based fast feature extraction algorithm for moving object detection using aerial images.

    PubMed

    Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

    2015-01-01

    Fast and computationally less complex feature extraction for moving object detection using aerial images from unmanned aerial vehicles (UAVs) remains as an elusive goal in the field of computer vision research. The types of features used in current studies concerning moving object detection are typically chosen based on improving detection rate rather than on providing fast and computationally less complex feature extraction methods. Because moving object detection using aerial images from UAVs involves motion as seen from a certain altitude, effective and fast feature extraction is a vital issue for optimum detection performance. This research proposes a two-layer bucket approach based on a new feature extraction algorithm referred to as the moment-based feature extraction algorithm (MFEA). Because a moment represents the coherent intensity of pixels and motion estimation is a motion pixel intensity measurement, this research used this relation to develop the proposed algorithm. The experimental results reveal the successful performance of the proposed MFEA algorithm and the proposed methodology.

  6. Looking into the water with oblique head tilting: revision of the aerial binocular imaging of underwater objects

    NASA Astrophysics Data System (ADS)

    Horváth, Gábor; Buchta, Krisztián; Varjú, Dezsö

    2003-06-01

    It is a well-known phenomenon that when we look into the water with two aerial eyes, both the apparent position and the apparent shape of underwater objects are different from the real ones because of refraction at the water surface. Earlier studies of the refraction-distorted structure of the underwater binocular visual field of aerial observers were restricted to either vertically or horizontally oriented eyes. We investigate a generalized version of this problem: We calculate the position of the binocular image point of an underwater object point viewed by two arbitrarily positioned aerial eyes, including oblique orientations of the eyes relative to the flat water surface. Assuming that binocular image fusion is performed by appropriate vergent eye movements to bring the object's image onto the foveas, the structure of the underwater binocular visual field is computed and visualized in different ways as a function of the relative positions of the eyes. We show that a revision of certain earlier treatments of the aerial imaging of underwater objects is necessary. We analyze and correct some widespread erroneous or incomplete representations of this classical geometric optical problem that occur in different textbooks. Improving the theory of aerial binocular imaging of underwater objects, we demonstrate that the structure of the underwater binocular visual field of aerial observers distorted by refraction is more complex than has been thought previously. (vision).

  7. Application of high resolution images from unmanned aerial vehicles for hydrology and rangeland science

    NASA Astrophysics Data System (ADS)

    Rango, A.; Vivoni, E. R.; Anderson, C. A.; Perini, N. A.; Saripalli, S.; Laliberte, A.

    2012-12-01

    A common problem in many natural resource disciplines is the lack of high-enough spatial resolution images that can be used for monitoring and modeling purposes. Advances have been made in the utilization of Unmanned Aerial Vehicles (UAVs) in hydrology and rangeland science. By utilizing low flight altitudes and velocities, UAVs are able to produce high resolution (5 cm) images as well as stereo coverage (with 75% forward overlap and 40% sidelap) to extract digital elevation models (DEM). Another advantage of flying at low altitude is that the potential problems of atmospheric haze obscuration are eliminated. Both small fixed-wing and rotary-wing aircraft have been used in our experiments over two rangeland areas in the Jornada Experimental Range in southern New Mexico and the Santa Rita Experimental Range in southern Arizona. The fixed-wing UAV has a digital camera in the wing and six-band multispectral camera in the nose, while the rotary-wing UAV carries a digital camera as payload. Because we have been acquiring imagery for several years, there are now > 31,000 photos at one of the study sites, and 177 mosaics over rangeland areas have been constructed. Using the DEM obtained from the imagery we have determined the actual catchment areas of three watersheds and compared these to previous estimates. At one site, the UAV-derived watershed area is 4.67 ha which is 22% smaller compared to a manual survey using a GPS unit obtained several years ago. This difference can be significant in constructing a watershed model of the site. From a vegetation species classification, we also determined that two of the shrub types in this small watershed(mesquite and creosote with 6.47 % and 5.82% cover, respectively) grow in similar locations(flat upland areas with deep soils), whereas the most predominant shrub(mariola with 11.9% cover) inhabits hillslopes near stream channels(with steep shallow soils). The positioning of these individual shrubs throughout the catchment using

  8. Image degradation in aerial imagery duplicates. [photographic processing of photographic film and reproduction (copying)

    NASA Technical Reports Server (NTRS)

    Lockwood, H. E.

    1975-01-01

    A series of Earth Resources Aircraft Program data flights were made over an aerial test range in Arizona for the evaluation of large cameras. Specifically, both medium altitude and high altitude flights were made to test and evaluate a series of color as well as black-and-white films. Image degradation, inherent in duplication processing, was studied. Resolution losses resulting from resolution characteristics of the film types are given. Color duplicates, in general, are shown to be degraded more than black-and-white films because of the limitations imposed by available aerial color duplicating stock. Results indicate that a greater resolution loss may be expected when the original has higher resolution. Photographs of the duplications are shown.

  9. Estimating Mixed Broadleaves Forest Stand Volume Using Dsm Extracted from Digital Aerial Images

    NASA Astrophysics Data System (ADS)

    Sohrabi, H.

    2012-07-01

    In mixed old growth broadleaves of Hyrcanian forests, it is difficult to estimate stand volume at plot level by remotely sensed data while LiDar data is absent. In this paper, a new approach has been proposed and tested for estimating stand forest volume. The approach is based on this idea that forest volume can be estimated by variation of trees height at plots. In the other word, the more the height variation in plot, the more the stand volume would be expected. For testing this idea, 120 circular 0.1 ha sample plots with systematic random design has been collected in Tonekaon forest located in Hyrcanian zone. Digital surface model (DSM) measure the height values of the first surface on the ground including terrain features, trees, building etc, which provides a topographic model of the earth's surface. The DSMs have been extracted automatically from aerial UltraCamD images so that ground pixel size for extracted DSM varied from 1 to 10 m size by 1m span. DSMs were checked manually for probable errors. Corresponded to ground samples, standard deviation and range of DSM pixels have been calculated. For modeling, non-linear regression method was used. The results showed that standard deviation of plot pixels with 5 m resolution was the most appropriate data for modeling. Relative bias and RMSE of estimation was 5.8 and 49.8 percent, respectively. Comparing to other approaches for estimating stand volume based on passive remote sensing data in mixed broadleaves forests, these results are more encouraging. One big problem in this method occurs when trees canopy cover is totally closed. In this situation, the standard deviation of height is low while stand volume is high. In future studies, applying forest stratification could be studied.

  10. An airport runway centerline location method for one-off aerial imaging system

    NASA Astrophysics Data System (ADS)

    Ge, Shule; Xu, Tingfa; Ni, Guoqiang; Shao, Xiaoguang

    2010-11-01

    An airport runway centerline location method is proposed for extracting airport runway in images from one-off aerial imaging system. One-off aerial imaging system captures image at an altitude about one kilometer or below, thus detailed feature of the scenery reveals itself clearly. The proposed method relies on this precondition to detect and locate centerline of airport runway. This method has four steps: edge detection, dominating line orientation extraction, distance histogram building and centerline location. A salient edge detection method is developed with Sobel detector, which could detect edges of runway strips at the disturbance of edges features from surrounding objects. Then, a traditional Hough transform is performed to build a Hough map, within which the dominating line orientation is extracted. After getting the dominating line orientation, a reference straight line is chosen for building distance histogram. This distance histogram is a one-dimensional one, built up with the distance of all edge pixels in the edge map to the reference line. Airport centerline has a three-peak pattern in the one-dimensional distance histogram, and the center peak is corresponding to the centerline of airport runway. Experiments with simulated images show this method could location airport runway centerline effectively.

  11. Efficient registration of multitemporal and multisensor aerial images based on alignment of nonparametric edge features

    NASA Astrophysics Data System (ADS)

    Makrogiannis, Sokratis; Bourbakis, Nikolaos G.

    2010-01-01

    The topic of aerial image registration attracts considerable interest within the imaging research community due to its significance for several applications, including change detection, sensor fusion, and topographic mapping. Our interest is focused on finding the optimal transformation between two aerial images that depict the same visual scene in the presence of pronounced spatial, temporal, and sensor variations. We first introduce a stochastic edge estimation process suitable for geometric shape-based registration, which we also compare to intensity-based registration. Furthermore, we propose an objective function that weights the L2 distances of the edge estimates by the feature points' energy, which we denote by sum of normalized squared differences and compare to standard objective functions, such as mutual information and the sum of absolute centered differences. In the optimization stage, we employ a genetic algorithm scheme in a multiscale image representation scheme to enhance the registration accuracy and reduce the computational load. Our experimental tests, measuring registration accuracy, rate of convergence, and statistical properties of registration errors, suggest that the proposed edge-based representation and objective function in conjunction with genetic algorithm optimization are capable of addressing several forms of imaging variations and producing encouraging registration results.

  12. Collecting Inexpensive High Resolution Aerial and Stereo Images of Small- to Mid-Scale Geomorphic and Tectonic Features

    NASA Astrophysics Data System (ADS)

    Wheelwright, R. J.; White, W. S.; Willis, J. B.

    2010-12-01

    Methods for collecting accurate, mm- to cm-scale stereoscopic aerial imagery of both small- and mid-scale geomorphic features are developed for a one-time cost of under $1500. High resolution aerial images are valuable for documenting and analyzing small- to mid-scale geomorphic and tectonic features. However, collecting images of mid-scale features such as landslides, rock glaciers, fault scarps, and cinder cones is expensive and makes studies that rely on high resolution repeat imagery prohibitive for undergraduate geology departments with limited budgets. In addition to cost, collecting images of smaller scale geomorphic features such as gravel bars is often impeded by overhanging vegetation or other features in the immediate environment that make impractical the collection of aerial images using standard airborne techniques. The methods provide high resolution stereo photos suitable for image processing and stereographic analysis; the images are potentially suitable for change analyses, velocity tracking, and construction of lidar-resolution digital elevation models. We developed two techniques. The technique suitable for small-scale features (such as gravel bars) utilizes two Nikon D3000 digital single-lens reflex (DSLR) cameras attached to a system of poles that suspends the cameras at a height of 4 meters with a variable camera separation of 0.6 to 0.9 m. The poles are oriented such that they do not appear in the photographs. The cameras are simultaneously remotely activated to collect stereo pairs at a resolution of 64 pixels/cm2 (pixel length is 1.2 mm). Ground control on the images is provided by pegs placed 5 meters apart, GPS positioning, and a meter-stick included in each photograph. Initial photo data gathered of a gravel bar on the Henry’s Fork of the Snake River, north of Rexburg, Idaho is sharp and readily segmented using the MatLab-based CLASTS image processing algorithm. The technique developed for imaging mid-scale features (such as cinder

  13. Algorithm for automatic image dodging of unmanned aerial vehicle images using two-dimensional radiometric spatial attributes

    NASA Astrophysics Data System (ADS)

    Li, Wenzhuo; Sun, Kaimin; Li, Deren; Bai, Ting

    2016-07-01

    Unmanned aerial vehicle (UAV) remote sensing technology has come into wide use in recent years. The poor stability of the UAV platform, however, produces more inconsistencies in hue and illumination among UAV images than other more stable platforms. Image dodging is a process used to reduce these inconsistencies caused by different imaging conditions. We propose an algorithm for automatic image dodging of UAV images using two-dimensional radiometric spatial attributes. We use object-level image smoothing to smooth foreground objects in images and acquire an overall reference background image by relative radiometric correction. We apply the Contourlet transform to separate high- and low-frequency sections for every single image, and replace the low-frequency section with the low-frequency section extracted from the corresponding region in the overall reference background image. We apply the inverse Contourlet transform to reconstruct the final dodged images. In this process, a single image must be split into reasonable block sizes with overlaps due to large pixel size. Experimental mosaic results show that our proposed method reduces the uneven distribution of hue and illumination. Moreover, it effectively eliminates dark-bright interstrip effects caused by shadows and vignetting in UAV images while maximally protecting image texture information.

  14. Damaged road extracting with high-resolution aerial image of post-earthquake

    NASA Astrophysics Data System (ADS)

    Zheng, Zezhong; Pu, Chengjun; Zhu, Mingcang; Xia, Jun; Zhang, Xiang; Liu, Yalan; Li, Jiang

    2015-12-01

    With the rapid development of earth observation technology, remote sensing images have played more important roles, because the high resolution images can provide the original data for object recognition, disaster investigation, and so on. When a disastrous earthquake breaks out, a large number of roads could be damaged instantly. There are a lot of approaches about road extraction, such as region growing, gray threshold, and k-means clustering algorithm. We could not obtain the undamaged roads with these approaches, if the trees or their shadows along the roads are difficult to be distinguished from the damaged road. In the paper, a method is presented to extract the damaged road with high resolution aerial image of post-earthquake. Our job is to extract the damaged road and the undamaged with the aerial image. We utilized the mathematical morphology approach and the k-means clustering algorithm to extract the road. Our method was composed of four ingredients. Firstly, the mathematical morphology filter operators were employed to remove the interferences from the trees or their shadows. Secondly, the k-means algorithm was employed to derive the damaged segments. Thirdly, the mathematical morphology approach was used to extract the undamaged road; Finally, we could derive the damaged segments by overlaying the road networks of pre-earthquake. Our results showed that the earthquake, broken in Yaan, was disastrous for the road, Therefore, we could take more measures to keep it clear.

  15. Shadow detection in color aerial images based on HSI space and color attenuation relationship

    NASA Astrophysics Data System (ADS)

    Shi, Wenxuan; Li, Jie

    2012-12-01

    Many problems in image processing and computer vision arise from shadows in a single color aerial image. This article presents a new algorithm by which shadows are extracted from a single color aerial image. Apart from using the ratio value of the hue over the intensity in some state-of-the-art algorithms, this article introduces another ratio map, which is obtained by applying the saturation over the intensity. Candidate shadow and nonshadow regions are separated by applying Otus's thresholding method. The color attenuation relationship that describes the relationship between the attenuation of each color channel is derived from the Planck's blackbody irradiance law. For each region, the color attenuation relationship and other determination conditions are performed iteratively to segment it into smaller sub-regions and to identify whether each sub-region is a true shadow region. Compared with previous methods, the proposed algorithm presents better shadow detection accuracy in the images that contain some dark green lawn, river, or low brightness shadow regions. The experimental results demonstrate the advantage of the proposed algorithm.

  16. Reconstruction of former glacier surface topography from archive oblique aerial images

    NASA Astrophysics Data System (ADS)

    Midgley, N. G.; Tonkin, T. N.

    2017-04-01

    Archive oblique aerial imagery offers the potential to reconstruct the former geometry of valley glaciers and other landscape surfaces. Whilst the use of Structure-from-Motion (SfM) photogrammetry with multiview stereopsis (MVS) to process small-format imagery is now well established in the geosciences, the potential of the technique for extracting topographic data from archive oblique aerial imagery is unclear. Here, SfM-MVS is used to reconstruct the former topography of two high-Arctic glaciers (Midtre and Austre Lovénbreen, Svalbard, Norway) using three archive oblique aerial images obtained by the Norwegian Polar Institute in 1936. The 1936 point cloud was produced using seven LiDAR-derived ground control points located on stable surfaces in proximity to the former piedmont glacier termini. To assess accuracy, the 1936 data set was compared to a LiDAR data set using the M3C2 algorithm to calculate cloud-to-cloud differences. For stable areas (such as nonglacial surfaces), vertical differences were detected between the two point clouds (RMS M3C2 vertical difference of 8.5 m), with the outwash zones adjacent to the assessed glacier termini showing less extensive vertical discrepancies (94% of M3C2 vertical differences between ± 5 m). This

  17. New aerial survey and hierarchical model to estimate manatee abundance

    USGS Publications Warehouse

    Langimm, Cahterine A.; Dorazio, Robert M.; Stith, Bradley M.; Doyle, Terry J.

    2011-01-01

    Monitoring the response of endangered and protected species to hydrological restoration is a major component of the adaptive management framework of the Comprehensive Everglades Restoration Plan. The endangered Florida manatee (Trichechus manatus latirostris) lives at the marine-freshwater interface in southwest Florida and is likely to be affected by hydrologic restoration. To provide managers with prerestoration information on distribution and abundance for postrestoration comparison, we developed and implemented a new aerial survey design and hierarchical statistical model to estimate and map abundance of manatees as a function of patch-specific habitat characteristics, indicative of manatee requirements for offshore forage (seagrass), inland fresh drinking water, and warm-water winter refuge. We estimated the number of groups of manatees from dual-observer counts and estimated the number of individuals within groups by removal sampling. Our model is unique in that we jointly analyzed group and individual counts using assumptions that allow probabilities of group detection to depend on group size. Ours is the first analysis of manatee aerial surveys to model spatial and temporal abundance of manatees in association with habitat type while accounting for imperfect detection. We conducted the study in the Ten Thousand Islands area of southwestern Florida, USA, which was expected to be affected by the Picayune Strand Restoration Project to restore hydrology altered for a failed real-estate development. We conducted 11 surveys in 2006, spanning the cold, dry season and warm, wet season. To examine short-term and seasonal changes in distribution we flew paired surveys 1–2 days apart within a given month during the year. Manatees were sparsely distributed across the landscape in small groups. Probability of detection of a group increased with group size; the magnitude of the relationship between group size and detection probability varied among surveys. Probability

  18. Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.

    PubMed

    Rosnell, Tomi; Honkavaara, Eija

    2012-01-01

    The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.

  19. Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera

    PubMed Central

    Rosnell, Tomi; Honkavaara, Eija

    2012-01-01

    The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

  20. Density estimation in aerial images of large crowds for automatic people counting

    NASA Astrophysics Data System (ADS)

    Herrmann, Christian; Metzler, Juergen

    2013-05-01

    Counting people is a common topic in the area of visual surveillance and crowd analysis. While many image-based solutions are designed to count only a few persons at the same time, like pedestrians entering a shop or watching an advertisement, there is hardly any solution for counting large crowds of several hundred persons or more. We addressed this problem previously by designing a semi-automatic system being able to count crowds consisting of hundreds or thousands of people based on aerial images of demonstrations or similar events. This system requires major user interaction to segment the image. Our principle aim is to reduce this manual interaction. To achieve this, we propose a new and automatic system. Besides counting the people in large crowds, the system yields the positions of people allowing a plausibility check by a human operator. In order to automatize the people counting system, we use crowd density estimation. The determination of crowd density is based on several features like edge intensity or spatial frequency. They indicate the density and discriminate between a crowd and other image regions like buildings, bushes or trees. We compare the performance of our automatic system to the previous semi-automatic system and to manual counting in images. By counting a test set of aerial images showing large crowds containing up to 12,000 people, the performance gain of our new system will be measured. By improving our previous system, we will increase the benefit of an image-based solution for counting people in large crowds.

  1. A multi-scale registration of urban aerial image with airborne lidar data

    NASA Astrophysics Data System (ADS)

    Huang, Shuo; Chen, Siying; Zhang, Yinchao; Guo, Pan; Chen, He

    2015-11-01

    This paper presented a multi-scale progressive registration method of airborne LiDAR data with aerial image. The cores of the proposed method lie in the coarse registration with road networks and the fine registration method using regularized building corners. During the two-stage registration, the exterior orientation parameters (EOP) are continually refined. By validation of the actual flight data of Dunhuang, the experimental result shows that the proposed method can obtain accurate results with low-precision initial EOP, also improve the automatic degree of registration.

  2. Urban road extraction based on shadow removal and road clues detection from high resolution RGB aerial image

    NASA Astrophysics Data System (ADS)

    Herumurti, Darlis; Uchimura, Keiichi; Koutaki, Gou; Uemura, Takumi

    2014-10-01

    In urban areas, the shadow cast by buildings, trees along the road, abundant objects and complex image texture make the extraction of the road on very high Resolution RGB aerial image very difficult and challenging. We propose a method of road extraction from RGB aerial image in the followings steps: Shadow removal, enhanced sobel transform, keypoints extraction based on Maximally Stable Extremal Regions (MSER), feature extraction based on Speeded Up Robust Features (SURF) and road construction based on multi-resolution segmentation. The experimental results show that the proposed method achieves a good result.

  3. Unmanned Aerial Vehicle Systems for Remote Estimation of Flooded Areas Based on Complex Image Processing

    PubMed Central

    Popescu, Dan; Ichim, Loretta; Stoican, Florin

    2017-01-01

    Floods are natural disasters which cause the most economic damage at the global level. Therefore, flood monitoring and damage estimation are very important for the population, authorities and insurance companies. The paper proposes an original solution, based on a hybrid network and complex image processing, to this problem. As first novelty, a multilevel system, with two components, terrestrial and aerial, was proposed and designed by the authors as support for image acquisition from a delimited region. The terrestrial component contains a Ground Control Station, as a coordinator at distance, which communicates via the internet with more Ground Data Terminals, as a fixed nodes network for data acquisition and communication. The aerial component contains mobile nodes—fixed wing type UAVs. In order to evaluate flood damage, two tasks must be accomplished by the network: area coverage and image processing. The second novelty of the paper consists of texture analysis in a deep neural network, taking into account new criteria for feature selection and patch classification. Color and spatial information extracted from chromatic co-occurrence matrix and mass fractal dimension were used as well. Finally, the experimental results in a real mission demonstrate the validity of the proposed methodologies and the performances of the algorithms. PMID:28241479

  4. Unmanned Aerial Vehicle Systems for Remote Estimation of Flooded Areas Based on Complex Image Processing.

    PubMed

    Popescu, Dan; Ichim, Loretta; Stoican, Florin

    2017-02-23

    Floods are natural disasters which cause the most economic damage at the global level. Therefore, flood monitoring and damage estimation are very important for the population, authorities and insurance companies. The paper proposes an original solution, based on a hybrid network and complex image processing, to this problem. As first novelty, a multilevel system, with two components, terrestrial and aerial, was proposed and designed by the authors as support for image acquisition from a delimited region. The terrestrial component contains a Ground Control Station, as a coordinator at distance, which communicates via the internet with more Ground Data Terminals, as a fixed nodes network for data acquisition and communication. The aerial component contains mobile nodes-fixed wing type UAVs. In order to evaluate flood damage, two tasks must be accomplished by the network: area coverage and image processing. The second novelty of the paper consists of texture analysis in a deep neural network, taking into account new criteria for feature selection and patch classification. Color and spatial information extracted from chromatic co-occurrence matrix and mass fractal dimension were used as well. Finally, the experimental results in a real mission demonstrate the validity of the proposed methodologies and the performances of the algorithms.

  5. A methodology for near real-time change detection between Unmanned Aerial Vehicle and wide area satellite images

    NASA Astrophysics Data System (ADS)

    Fytsilis, Anastasios L.; Prokos, Anthony; Koutroumbas, Konstantinos D.; Michail, Dimitrios; Kontoes, Charalambos C.

    2016-09-01

    In this paper a novel integrated hybrid methodology for unsupervised change detection between Unmanned Aerial Vehicle (UAV) and satellite images, which can be utilized in various fields like security applications (e.g. border surveillance) and damage assessment, is proposed. This is a challenging problem mainly due to the difference in geographic coverage and the spatial resolution of the two images, as well as to the acquisition modes which lead to misregistration errors. The methodology consists of the following steps: (a) pre-processing, where the part of the satellite image that corresponds to the UAV image is determined and the UAV image is ortho-rectified using information provided by a Digital Terrain Model, (b) the detection of potential changes, which is based exclusively on intensity and image gradient information, (c) the generation of the region map, where homogeneous regions are produced by the previous potential changes via a seeded region growing algorithm and placed on the region map, and (d) the evaluation of the above regions, in order to characterize them as true changes or not. The methodology has been applied on demanding real datasets with very encouraging results. Finally, its robustness to the misregistration errors is assessed via extensive experimentation.

  6. Highway extraction from high resolution aerial photography using a geometric active contour model

    NASA Astrophysics Data System (ADS)

    Niu, Xutong

    Highway extraction and vehicle detection are two of the most important steps in traffic-flow analysis from multi-frame aerial photographs. The traditional method of deriving traffic flow trajectories relies on manual vehicle counting from a sequence of aerial photographs, which is tedious and time-consuming. This research presents a new framework for semi-automatic highway extraction. The basis of the new framework is an improved geometric active contour (GAC) model. This novel model seeks to minimize an objective function that transforms a problem of propagation of regular curves into an optimization problem. The implementation of curve propagation is based on level set theory. By using an implicit representation of a two-dimensional curve, a level set approach can be used to deal with topological changes naturally, and the output is unaffected by different initial positions of the curve. However, the original GAC model, on which the new model is based, only incorporates boundary information into the curve propagation process. An error-producing phenomenon called leakage is inevitable wherever there is an uncertain weak edge. In this research, region-based information is added as a constraint into the original GAC model, thereby, giving this proposed method the ability of integrating both boundary and region-based information during the curve propagation. Adding the region-based constraint eliminates the leakage problem. This dissertation applies the proposed augmented GAC model to the problem of highway extraction from high-resolution aerial photography. First, an optimized stopping criterion is designed and used in the implementation of the GAC model. It effectively saves processing time and computations. Second, a seed point propagation framework is designed and implemented. This framework incorporates highway extraction, tracking, and linking into one procedure. A seed point is usually placed at an end node of highway segments close to the boundary of the

  7. A Model-Based System For Object Recognition In Aerial Scenes

    NASA Astrophysics Data System (ADS)

    Cullen, M. F.; Hord, R. M.; Miller, S. F.

    1987-03-01

    Preliminary results of a system that uses model descriptions of objects to predict and match features derived from aerial images are presented. The system is organized into several phases: 1) processing of image scenes to obtain image primitives, 2) goal-oriented sorting of primitives into classes of related features, 3) prediction of the location of object model features in the image, and 4) matching image features to the model predicted features. The matching approach is centered upon a compatibility figure of merit between a set of image features and model features chosen to direct the search. The search process utilizes an iterative hypothesis generation and verication cycle. A "search matrix" is con-structed from image features and model features according to a first approximation of compatibility based upon orientation. Currently, linear features are used as primitives. Input to the matching algorithm is in the form of line segments extracted from an image scene via edge operatiors and a Hough transform technique for grouping. Additional processing is utilized to derive closed boundaries and complete edge descriptions. Line segments are then sorted into specific classes such that, on a higher level, a priori knowledge about a particular scene can be used to control the priority of line segments in the search process. Additional knowledge about the object model under consideration is utilized to construct the search matrix with the classes of line segments most likely containing the model description. It is shown that these techniques result in a, reduction in the size of the object recognition search space and hence in the time to locate the object in the image. The current system is implemented on a Symbolics LispTM machine. While experimentation continues, we have rewritten and tested the search process and several image processing functions for parallel implementation on a Connection Machine TM computer. It is shown that several orders of magnitude faster

  8. Nonlinear Estimation Approach to Real-Time Georegistration from Aerial Images

    NASA Technical Reports Server (NTRS)

    Bayard, David S.; Padgett, Curtis W.

    2012-01-01

    When taking aerial images, it is important to know locations of specific points of interest in an Earth-centered coordinate system (latitude, longitude, height). The correspondence between a pixel location in the image and its Earth coordinate is known as georegistration. There are two main technical challenges arising in the intended application. The first is that no known features are assumed to be available in any of the images. The second is that the intended applications are real time. Here, images are taken at regular intervals (i.e. once per second), and it is desired to make decisions in real time based on the geolocation of specific objects seen in the images as they arrive. This is in sharp contrast to most current methods for geolocation that operate "after-the-fact" by processing, on the ground, a database of stored images using computationally intensive methods. The solution is a nonlinear estimation algorithm that combines processed realtime camera images with vehicle position and attitude information ob tained from an onboard GPS receiver. This approach provides accurate georegistration estimates (latitude, longitude, height) of arbitrary features and/or points of interest seen in the camera images. This solves the georegistration problem at the modest cost of augmenting the camera information with a GPS receiver carried onboard the vehicle.

  9. Comparison of binary mask defect printability analysis using virtual stepper system and aerial image microscope system

    NASA Astrophysics Data System (ADS)

    Phan, Khoi A.; Spence, Chris A.; Dakshina-Murthy, S.; Bala, Vidya; Williams, Alvina M.; Strener, Steve; Eandi, Richard D.; Li, Junling; Karklin, Linard

    1999-12-01

    As advanced process technologies in the wafer fabs push the patterning processes toward lower k1 factor for sub-wavelength resolution printing, reticles are required to use optical proximity correction (OPC) and phase-shifted mask (PSM) for resolution enhancement. For OPC/PSM mask technology, defect printability is one of the major concerns. Current reticle inspection tools available on the market sometimes are not capable of consistently differentiating between an OPC feature and a true random defect. Due to the process complexity and high cost associated with the making of OPC/PSM reticles, it is important for both mask shops and lithography engineers to understand the impact of different defect types and sizes to the printability. Aerial Image Measurement System (AIMS) has been used in the mask shops for a number of years for reticle applications such as aerial image simulation and transmission measurement of repaired defects. The Virtual Stepper System (VSS) provides an alternative method to do defect printability simulation and analysis using reticle images captured by an optical inspection or review system. In this paper, pre- programmed defects and repairs from a Defect Sensitivity Monitor (DSM) reticle with 200 nm minimum features (at 1x) will be studied for printability. The simulated resist lines by AIMS and VSS are both compared to SEM images of resist wafers qualitatively and quantitatively using CD verification.Process window comparison between unrepaired and repaired defects for both good and bad repair cases will be shown. The effect of mask repairs to resist pattern images for the binary mask case will be discussed. AIMS simulation was done at the International Sematech, Virtual stepper simulation at Zygo and resist wafers were processed at AMD-Submicron Development Center using a DUV lithographic process for 0.18 micrometer Logic process technology.

  10. Automatic aerial image shadow detection through the hybrid analysis of RGB and HIS color space

    NASA Astrophysics Data System (ADS)

    Wu, Jun; Li, Huilin; Peng, Zhiyong

    2015-12-01

    This paper presents our research on automatic shadow detection from high-resolution aerial image through the hybrid analysis of RGB and HIS color space. To this end, the spectral characteristics of shadow are firstly discussed and three kinds of spectral components including the difference between normalized blue and normalized red component - BR, intensity and saturation components are selected as criterions to obtain initial segmentation of shadow region (called primary segmentation). After that, within the normalized RGB color space and HIS color space, the shadow region is extracted again (called auxiliary segmentation) using the OTSU operation, respectively. Finally, the primary segmentation and auxiliary segmentation are combined through a logical AND-connection operation to obtain reliable shadow region. In this step, small shadow areas are removed from combined shadow region and morphological algorithms are apply to fill small holes as well. The experimental results show that the proposed approach can effectively detect the shadow region from high-resolution aerial image and in high degree of automaton.

  11. Aerial Image Microscopes for the Inspection of Defects in EUV Masks

    SciTech Connect

    Barty, A; Taylor, J S; Hudyma, R; Spiller, E; Sweeney, D W; Shelden, G; Urbach, J-P

    2002-10-22

    The high volume inspection equipment currently available to support development of EUV blanks is non-actinic. The same is anticipated for patterned EUV mask inspection. Once potential defects are identified and located by such non-actinic inspection techniques, it is essential to have instrumentation to perform detailed characterization, and if repairs are performed, re-evaluation. The ultimate metric for the acceptance or rejection of a mask due to a defect, is the wafer level impact. Thus measuring the aerial image for the site under question is required. An EUV Aerial Image Microscope (''AIM'') similar to the current AIM tools for 248nm and 193nm exposure wavelength is the natural solution for this task. Due to the complicated manufacturing process of EUV blanks, AIM measurements might also be beneficial to accurately assessing the severity of a blank defect. This is an additional application for an EUV AIM as compared to today's use In recognition of the critical role of an EUV AIM for the successful implementation of EUV blank and mask supply, International SEMATECH initiated this design study with the purpose to define the technical requirements for accurately simulating EUV scanner performance, demonstrating the feasibility to meet these requirements and to explore various technical approaches to building an EUV AIM tool.

  12. Neural-network classifiers for automatic real-world aerial image recognition

    NASA Astrophysics Data System (ADS)

    Greenberg, Shlomo; Guterman, Hugo

    1996-08-01

    We describe the application of the multilayer perceptron (MLP) network and a version of the adaptive resonance theory version 2-A (ART 2-A) network to the problem of automatic aerial image recognition (AAIR). The classification of aerial images, independent of their positions and orientations, is required for automatic tracking and target recognition. Invariance is achieved by the use of different invariant feature spaces in combination with supervised and unsupervised neural networks. The performance of neural-network-based classifiers in conjunction with several types of invariant AAIR global features, such as the Fourier-transform space, Zernike moments, central moments, and polar transforms, are examined. The advantages of this approach are discussed. The performance of the MLP network is compared with that of a classical correlator. The MLP neural-network correlator outperformed the binary phase-only filter (BPOF) correlator. It was found that the ART 2-A distinguished itself with its speed and its low number of required training vectors. However, only the MLP classifier was able to deal with a combination of shift and rotation geometric distortions.

  13. Feature-based registration of historical aerial images by Area Minimization

    NASA Astrophysics Data System (ADS)

    Nagarajan, Sudhagar; Schenk, Toni

    2016-06-01

    The registration of historical images plays a significant role in assessing changes in land topography over time. By comparing historical aerial images with recent data, geometric changes that have taken place over the years can be quantified. However, the lack of ground control information and precise camera parameters has limited scientists' ability to reliably incorporate historical images into change detection studies. Other limitations include the methods of determining identical points between recent and historical images, which has proven to be a cumbersome task due to continuous land cover changes. Our research demonstrates a method of registering historical images using Time Invariant Line (TIL) features. TIL features are different representations of the same line features in multi-temporal data without explicit point-to-point or straight line-to-straight line correspondence. We successfully determined the exterior orientation of historical images by minimizing the area formed between corresponding TIL features in recent and historical images. We then tested the feasibility of the approach with synthetic and real data and analyzed the results. Based on our analysis, this method shows promise for long-term 3D change detection studies.

  14. Fusion of aerial images with mean shift-based upsampled elevation data for improved building block classification

    NASA Astrophysics Data System (ADS)

    Gyftakis, S.; Tsenoglou, T.; Bratsolis, E.; Charou, Eleni; Vassilas, N.

    2014-10-01

    Nowadays there is an increasing demand for detailed 3D modeling of buildings using elevation data such as those acquired from LiDAR airborne scanners. The various techniques that have been developed for this purpose typically perform segmentation into homogeneous regions followed by boundary extraction and are based on some combination of LiDAR data, digital maps, satellite images and aerial orthophotographs. In the present work, our dataset includes an aerial RGB orthophoto, a DSM and a DTM with spatial resolutions of 20cm, 1m and 2m respectively. Next, a normalized DSM (nDSM) is generated and fused with the optical data in order to increase its resolution to 20cm. The proposed methodology can be described as a two-step approach. First, a nearest neighbor interpolation is applied on the low resolution nDSM to obtain a low quality, ragged, elevation image. Next, we performed a mean shift-based discontinuity preserving smoothing on the fused data. The outcome is on the one hand a more homogeneous RGB image, with smoothed terrace coloring while at the same time preserving the optical edges and on the other hand an upsampled elevation data with considerable improvement regarding region filling and "straightness" of elevation discontinuities. Besides the apparent visual assessment of the increased accuracy of building boundaries, the effectiveness of the proposed method is demonstrated using the processed dataset as input to five supervised classification methods. The performance of each method is evaluated using a subset of the test area as ground truth. Comparisons with classification results obtained with the original data demonstrate that preprocessing the input dataset using the mean shift algorithm improves significantly the performance of all tested classifiers for building block extraction.

  15. Detection of Tree Crowns Based on Reclassification Using Aerial Images and LIDAR Data

    NASA Astrophysics Data System (ADS)

    Talebi, S.; Zarea, A.; Sadeghian, S.; Arefi, H.

    2013-09-01

    Tree detection using aerial sensors in early decades was focused by many researchers in different fields including Remote Sensing and Photogrammetry. This paper is intended to detect trees in complex city areas using aerial imagery and laser scanning data. Our methodology is a hierarchal unsupervised method consists of some primitive operations. This method could be divided into three sections, in which, first section uses aerial imagery and both second and third sections use laser scanners data. In the first section a vegetation cover mask is created in both sunny and shadowed areas. In the second section Rate of Slope Change (RSC) is used to eliminate grasses. In the third section a Digital Terrain Model (DTM) is obtained from LiDAR data. By using DTM and Digital Surface Model (DSM) we would get to Normalized Digital Surface Model (nDSM). Then objects which are lower than a specific height are eliminated. Now there are three result layers from three sections. At the end multiplication operation is used to get final result layer. This layer will be smoothed by morphological operations. The result layer is sent to WG III/4 to evaluate. The evaluation result shows that our method has a good rank in comparing to other participants' methods in ISPRS WG III/4, when assessed in terms of 5 indices including area base completeness, area base correctness, object base completeness, object base correctness and boundary RMS. With regarding of being unsupervised and automatic, this method is improvable and could be integrate with other methods to get best results.

  16. Model-Based Building Detection from Low-Cost Optical Sensors Onboard Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Karantzalos, K.; Koutsourakis, P.; Kalisperakis, I.; Grammatikopoulos, L.

    2015-08-01

    The automated and cost-effective building detection in ultra high spatial resolution is of major importance for various engineering and smart city applications. To this end, in this paper, a model-based building detection technique has been developed able to extract and reconstruct buildings from UAV aerial imagery and low-cost imaging sensors. In particular, the developed approach through advanced structure from motion, bundle adjustment and dense image matching computes a DSM and a true orthomosaic from the numerous GoPro images which are characterised by important geometric distortions and fish-eye effect. An unsupervised multi-region, graphcut segmentation and a rule-based classification is responsible for delivering the initial multi-class classification map. The DTM is then calculated based on inpaininting and mathematical morphology process. A data fusion process between the detected building from the DSM/DTM and the classification map feeds a grammar-based building reconstruction and scene building are extracted and reconstructed. Preliminary experimental results appear quite promising with the quantitative evaluation indicating detection rates at object level of 88% regarding the correctness and above 75% regarding the detection completeness.

  17. Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining

    PubMed Central

    Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

    2017-01-01

    Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods. PMID:28208587

  18. Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

    PubMed

    Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

    2017-02-10

    Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

  19. Exploring the Potential of Aerial Photogrammetry for 3d Modelling of High-Alpine Environments

    NASA Astrophysics Data System (ADS)

    Legat, K.; Moe, K.; Poli, D.; Bollmannb, E.

    2016-03-01

    High-alpine areas are subject to rapid topographic changes, mainly caused by natural processes like glacial retreat and other geomorphological processes, and also due to anthropogenic interventions like construction of slopes and infrastructure in skiing resorts. Consequently, the demand for highly accurate digital terrain models (DTMs) in alpine environments has arisen. Public administrations often have dedicated resources for the regular monitoring of glaciers and natural hazard processes. In case of glaciers, traditional monitoring encompasses in-situ measurements of area and length and the estimation of volume and mass changes. Next to field measurements, data for such monitoring programs can be derived from DTMs and digital ortho photos (DOPs). Skiing resorts, on the other hand, require DTMs as input for planning and - more recently - for RTK-GNSS supported ski-slope grooming. Although different in scope, the demand of both user groups is similar: high-quality and up-to-date terrain data for extended areas often characterised by difficult accessibility and large elevation ranges. Over the last two decades, airborne laser scanning (ALS) has replaced photogrammetric approaches as state-of-the-art technology for the acquisition of high-resolution DTMs also in alpine environments. Reasons include the higher productivity compared to (manual) stereo-photogrammetric measurements, canopy-penetration capability, and limitations of photo measurements on sparsely textured surfaces like snow or ice. Nevertheless, the last few years have shown strong technological advances in the field of aerial camera technology, image processing and photogrammetric software which led to new possibilities for image-based DTM generation even in alpine terrain. At Vermessung AVT, an Austrian-based surveying company, and its subsidiary Terra Messflug, very promising results have been achieved for various projects in high-alpine environments, using images acquired by large-format digital

  20. Detection of laurel wilt disease in avocado using low altitude aerial imaging.

    PubMed

    de Castro, Ana I; Ehsani, Reza; Ploetz, Randy C; Crane, Jonathan H; Buchanon, Sherrie

    2015-01-01

    Laurel wilt is a lethal disease of plants in the Lauraceae plant family, including avocado (Persea americana). This devastating disease has spread rapidly along the southeastern seaboard of the United States and has begun to affect commercial avocado production in Florida. The main objective of this study was to evaluate the potential to discriminate laurel wilt-affected avocado trees using aerial images taken with a modified camera during helicopter surveys at low-altitude in the commercial avocado production area. The ability to distinguish laurel wilt-affected trees from other factors that produce similar external symptoms was also studied. RmodGB digital values of healthy trees and laurel wilt-affected trees, as well as fruit stress and vines covering trees were used to calculate several vegetation indices (VIs), band ratios, and VI combinations. These indices were subjected to analysis of variance (ANOVA) and an M-statistic was performed in order to quantify the separability of those classes. Significant differences in spectral values among laurel wilt affected and healthy trees were observed in all vegetation indices calculated, although the best results were achieved with Excess Red (ExR), (Red-Green) and Combination 1 (COMB1) in all locations. B/G showed a very good potential for separate the other factors with symptoms similar to laurel wilt-affected trees, such as fruit stress and vines covering trees, from laurel wilt-affected trees. These consistent results prove the usefulness of using a modified camera (RmodGB) to discriminate laurel wilt-affected avocado trees from healthy trees, as well as from other factors that cause the same symptoms and suggest performing the classification in further research. According to our results, ExR and B/G should be utilized to develop an algorithm or decision rules to classify aerial images, since they showed the highest capacity to discriminate laurel wilt-affected trees. This methodology may allow the rapid detection

  1. Detection of Laurel Wilt Disease in Avocado Using Low Altitude Aerial Imaging

    PubMed Central

    de Castro, Ana I.; Ehsani, Reza; Ploetz, Randy C.; Crane, Jonathan H.; Buchanon, Sherrie

    2015-01-01

    Laurel wilt is a lethal disease of plants in the Lauraceae plant family, including avocado (Persea americana). This devastating disease has spread rapidly along the southeastern seaboard of the United States and has begun to affect commercial avocado production in Florida. The main objective of this study was to evaluate the potential to discriminate laurel wilt-affected avocado trees using aerial images taken with a modified camera during helicopter surveys at low-altitude in the commercial avocado production area. The ability to distinguish laurel wilt-affected trees from other factors that produce similar external symptoms was also studied. RmodGB digital values of healthy trees and laurel wilt-affected trees, as well as fruit stress and vines covering trees were used to calculate several vegetation indices (VIs), band ratios, and VI combinations. These indices were subjected to analysis of variance (ANOVA) and an M-statistic was performed in order to quantify the separability of those classes. Significant differences in spectral values among laurel wilt affected and healthy trees were observed in all vegetation indices calculated, although the best results were achieved with Excess Red (ExR), (Red–Green) and Combination 1 (COMB1) in all locations. B/G showed a very good potential for separate the other factors with symptoms similar to laurel wilt-affected trees, such as fruit stress and vines covering trees, from laurel wilt-affected trees. These consistent results prove the usefulness of using a modified camera (RmodGB) to discriminate laurel wilt-affected avocado trees from healthy trees, as well as from other factors that cause the same symptoms and suggest performing the classification in further research. According to our results, ExR and B/G should be utilized to develop an algorithm or decision rules to classify aerial images, since they showed the highest capacity to discriminate laurel wilt-affected trees. This methodology may allow the rapid

  2. Building Roof Segmentation from Aerial Images Using a Line-and Region-Based Watershed Segmentation Technique

    PubMed Central

    Merabet, Youssef El; Meurie, Cyril; Ruichek, Yassine; Sbihi, Abderrahmane; Touahni, Raja

    2015-01-01

    In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans) based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc.) affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM), 84% with mean shift, 82% with color structure code (CSC), 80% with efficient graph-based segmentation algorithm (EGBIS) and 71% with JSEG. PMID:25648706

  3. Integrating Spray Plane-Based Remote Sensing and Rapid Image Processing with Variable-Rate Aerial Application.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A remote sensing and variable rate application system was configured for agricultural aircraft. This combination system has the potential of providing a completely integrated solution for all aspects of aerial site-specific application and includes remote sensing, image processing and georegistratio...

  4. EVALUATION OF THE AGDISP AERIAL SPRAY ALGORITHMS IN THE AGDRIFT MODEL

    EPA Science Inventory

    A systematic evaluation of the AgDISP algorithms, which simulate off-site drift and deposition of aerially applied pesticides, contained in the AgDRIFT model was performed by comparing model simulations to field-trial data collected by the Spray Drift Task Force. Field-trial data...

  5. AGDRIFT: A MODEL FOR ESTIMATING NEAR-FIELD SPRAY DRIFT FROM AERIAL APPLICATIONS

    EPA Science Inventory

    The aerial spray prediction model AgDRIFT(R) embodies the computational engine found in the near-wake Lagrangian model AGricultural DISPersal (AGDISP) but with several important features added that improve the speed and accuracy of its predictions. This article summarizes those c...

  6. Region-Based 3d Surface Reconstruction Using Images Acquired by Low-Cost Unmanned Aerial Systems

    NASA Astrophysics Data System (ADS)

    Lari, Z.; Al-Rawabdeh, A.; He, F.; Habib, A.; El-Sheimy, N.

    2015-08-01

    Accurate 3D surface reconstruction of our environment has become essential for an unlimited number of emerging applications. In the past few years, Unmanned Aerial Systems (UAS) are evolving as low-cost and flexible platforms for geospatial data collection that could meet the needs of aforementioned application and overcome limitations of traditional airborne and terrestrial mobile mapping systems. Due to their payload restrictions, these systems usually include consumer-grade imaging and positioning sensor which will negatively impact the quality of the collected geospatial data and reconstructed surfaces. Therefore, new surface reconstruction surfaces are needed to mitigate the impact of using low-cost sensors on the final products. To date, different approaches have been proposed to for 3D surface construction using overlapping images collected by imaging sensor mounted on moving platforms. In these approaches, 3D surfaces are mainly reconstructed based on dense matching techniques. However, generated 3D point clouds might not accurately represent the scanned surfaces due to point density variations and edge preservation problems. In order to resolve these problems, a new region-based 3D surface renostruction trchnique is introduced in this paper. This approach aims to generate a 3D photo-realistic model of individually scanned surfaces within the captured images. This approach is initiated by a Semi-Global dense Matching procedure is carried out to generate a 3D point cloud from the scanned area within the collected images. The generated point cloud is then segmented to extract individual planar surfaces. Finally, a novel region-based texturing technique is implemented for photorealistic reconstruction of the extracted planar surfaces. Experimental results using images collected by a camera mounted on a low-cost UAS demonstrate the feasibility of the proposed approach for photorealistic 3D surface reconstruction.

  7. Advanced Tie Feature Matching for the Registration of Mobile Mapping Imaging Data and Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Jende, P.; Peter, M.; Gerke, M.; Vosselman, G.

    2016-06-01

    Mobile Mapping's ability to acquire high-resolution ground data is opposing unreliable localisation capabilities of satellite-based positioning systems in urban areas. Buildings shape canyons impeding a direct line-of-sight to navigation satellites resulting in a deficiency to accurately estimate the mobile platform's position. Consequently, acquired data products' positioning quality is considerably diminished. This issue has been widely addressed in the literature and research projects. However, a consistent compliance of sub-decimetre accuracy as well as a correction of errors in height remain unsolved. We propose a novel approach to enhance Mobile Mapping (MM) image orientation based on the utilisation of highly accurate orientation parameters derived from aerial imagery. In addition to that, the diminished exterior orientation parameters of the MM platform will be utilised as they enable the application of accurate matching techniques needed to derive reliable tie information. This tie information will then be used within an adjustment solution to correct affected MM data. This paper presents an advanced feature matching procedure as a prerequisite to the aforementioned orientation update. MM data is ortho-projected to gain a higher resemblance to aerial nadir data simplifying the images' geometry for matching. By utilising MM exterior orientation parameters, search windows may be used in conjunction with a selective keypoint detection and template matching. Originating from different sensor systems, however, difficulties arise with respect to changes in illumination, radiometry and a different original perspective. To respond to these challenges for feature detection, the procedure relies on detecting keypoints in only one image. Initial tests indicate a considerable improvement in comparison to classic detector/descriptor approaches in this particular matching scenario. This method leads to a significant reduction of outliers due to the limited availability

  8. Fusing Unmanned Aerial Vehicle Imagery with High Resolution Hydrologic Modeling (Invited)

    NASA Astrophysics Data System (ADS)

    Vivoni, E. R.; Pierini, N.; Schreiner-McGraw, A.; Anderson, C.; Saripalli, S.; Rango, A.

    2013-12-01

    After decades of development and applications, high resolution hydrologic models are now common tools in research and increasingly used in practice. More recently, high resolution imagery from unmanned aerial vehicles (UAVs) that provide information on land surface properties have become available for civilian applications. Fusing the two approaches promises to significantly advance the state-of-the-art in terms of hydrologic modeling capabilities. This combination will also challenge assumptions on model processes, parameterizations and scale as land surface characteristics (~0.1 to 1 m) may now surpass traditional model resolutions (~10 to 100 m). Ultimately, predictions from high resolution hydrologic models need to be consistent with the observational data that can be collected from UAVs. This talk will describe our efforts to develop, utilize and test the impact of UAV-derived topographic and vegetation fields on the simulation of two small watersheds in the Sonoran and Chihuahuan Deserts at the Santa Rita Experimental Range (Green Valley, AZ) and the Jornada Experimental Range (Las Cruces, NM). High resolution digital terrain models, image orthomosaics and vegetation species classification were obtained from a fixed wing airplane and a rotary wing helicopter, and compared to coarser analyses and products, including Light Detection and Ranging (LiDAR). We focus the discussion on the relative improvements achieved with UAV-derived fields in terms of terrain-hydrologic-vegetation analyses and summer season simulations using the TIN-based Real-time Integrated Basin Simulator (tRIBS) model. Model simulations are evaluated at each site with respect to a high-resolution sensor network consisting of six rain gauges, forty soil moisture and temperature profiles, four channel runoff flumes, a cosmic-ray soil moisture sensor and an eddy covariance tower over multiple summer periods. We also discuss prospects for the fusion of high resolution models with novel

  9. Mapping temporal changes in connectivity using high-resolution aerial data and object based image analysis

    NASA Astrophysics Data System (ADS)

    Masselink, Rens; Anders, Niels; Keesstra, Saskia; Seeger, Manuel

    2014-05-01

    Within the field of geomorphology mapping has always been an important tool to interpret spatial and temporal distributions of phenomena and processes at the surface. In the field of connectivity however, although throughout the past decade many articles have been published, there are only very few that go into the mapping of connectivity. This study aimed at developing a new, automated method for mapping connectivity within agricultural catchments. The method, which is a combination of Object-Based Image Analysis (OBIA) and traditional geomorphological field mapping, was applied to two agricultural catchments in Navarre, Spain, both with an area of approximately 2 sq.km. An unmanned aerial vehicle (UAV) was used to take aerial photographs with a resolution of 6 cm, of which a DEM with a 12 cm resolution was created using structure-from-motion photogrammetry. Connectivity was mapped within the study areas using OBIA using a top down method, meaning that connectivity was mapped at different scale levels, starting at the largest scale. Firstly sub-catchments were automatically delineated, after which several characteristics and features that affect connectivity within the sub-catchments were classified, e.g. landuse, landslides, rills, gullies, riparian vegetation, changes in slope, ploughing direction etc. In two consecutive years (2013-2014) photographs were taken and connectivity of both catchments of both years will be compared. Future work will include a quantification of the mapped connectivity (highly connected years vs. low connected years), causes and consequences of these differences in connectivity, comparison to existing connectivity indices and comparison of mapped connectivity in sub-catchments and measured discharge.

  10. Using aerial-acquired images to improve cotton and peanut production systems

    NASA Astrophysics Data System (ADS)

    Kvien, Craig; Waters, Deborah; Pocknee, Stuart; Usery, Lynn; Wells, Natasha

    1996-11-01

    Modern agriculture management is an extraordinarily complex task. The most complex tasks are management for environmental benefits. Chemical, physical and biological characteristics are known to vary over short distances in a field. However, most fields are treated as uniform, leading to over application and environmental pollution, or under application and suboptimal yields. Affordable navigation and positioning systems linked to sensing technologies and integrated into a geographic information system (GIS) are revolutionizing the way agriculture can address environmental variabilities. One challenge to better management of within field variability is the establishment of management zones for various inputs. Our research and development group is currently using aerial acquired images to help establish management zones for nutrients, pest scouting, and to monitor crop growth and development. These images are ground truthed and coupled with additional information layers such as maps of yield, disease, insect and weed pests, soil properties, topography to help establish relationships between the various components affecting crop growth and to help improve management decisions during the growing season.

  11. Using small unmanned aerial vehicle for instream habitat evaluation and modelling

    NASA Astrophysics Data System (ADS)

    Astegiano, Luca; Vezza, Paolo; Comoglio, Claudio; Lingua, Andrea; Spairani, Michele

    2015-04-01

    Recent advances in digital image collection and processing have led to the increased use of unmanned aerial vehicles (UAV) for river research and management. In this paper, we assess the capabilities of a small UAV to characterize physical habitat for fish in three river stretches of North-Western Italy. The main aim of the study was identifying the advantages and challenges of this technology for environmental river management, in the context of the increasing river exploitation for hydropower production. The UAV used to acquire overlapping images was a small quadcopter with a two different high-resolution (non-metric) cameras (Nikon J1™ and Go-Pro Hero 3 Black Edition™). The quadcopter was preprogrammed to fly set waypoints using a small tablet PC. With the acquired imagery, we constructed a 5-cm resolution orthomosaic image and a digital surface model (DSM). The two products were used to map the distribution of aquatic and riparian habitat features, i.e., wetted area, morphological unit distributions, bathymetry, water surface gradient, substrates and grain sizes, shelters and cover for fish. The study assessed the quality of collected data and used such information to identify key reach-scale metrics and important aspects of fluvial morphology and aquatic habitat. The potential and limitations of using UAV for physical habitat survey were evaluated and the collected data were used to initialize and run common habitat simulation tools (MesoHABSIM). Several advantages of using UAV-based imagery were found, including low cost procedures, high resolution and efficiency in data collection. However, some challenges were identified for bathymetry extraction (vegetation obstructions, white waters, turbidity) and grain size assessment (preprocessing of data and automatic object detection). The application domain and possible limitation for instream habitat mapping were defined and will be used as a reference for future studies. Ongoing activities include the

  12. Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring

    USGS Publications Warehouse

    Gillan, Jeffrey K.; Karl, Jason W.; Duniway, Michael; Elaksher, Ahmed

    2014-01-01

    Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. Estimates of

  13. Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring.

    PubMed

    Gillan, Jeffrey K; Karl, Jason W; Duniway, Michael; Elaksher, Ahmed

    2014-11-01

    Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. Estimates of

  14. Low-Level Tie Feature Extraction of Mobile Mapping Data (mls/images) and Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Jende, P.; Hussnain, Z.; Peter, M.; Oude Elberink, S.; Gerke, M.; Vosselman, G.

    2016-03-01

    Mobile Mapping (MM) is a technique to obtain geo-information using sensors mounted on a mobile platform or vehicle. The mobile platform's position is provided by the integration of Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS). However, especially in urban areas, building structures can obstruct a direct line-of-sight between the GNSS receiver and navigation satellites resulting in an erroneous position estimation. Therefore, derived MM data products, such as laser point clouds or images, lack the expected positioning reliability and accuracy. This issue has been addressed by many researchers, whose aim to mitigate these effects mainly concentrates on utilising tertiary reference data. However, current approaches do not consider errors in height, cannot achieve sub-decimetre accuracy and are often not designed to work in a fully automatic fashion. We propose an automatic pipeline to rectify MM data products by employing high resolution aerial nadir and oblique imagery as horizontal and vertical reference, respectively. By exploiting the MM platform's defective, and therefore imprecise but approximate orientation parameters, accurate feature matching techniques can be realised as a pre-processing step to minimise the MM platform's three-dimensional positioning error. Subsequently, identified correspondences serve as constraints for an orientation update, which is conducted by an estimation or adjustment technique. Since not all MM systems employ laser scanners and imaging sensors simultaneously, and each system and data demands different approaches, two independent workflows are developed in parallel. Still under development, both workflows will be presented and preliminary results will be shown. The workflows comprise of three steps; feature extraction, feature matching and the orientation update. In this paper, initial results of low-level image and point cloud feature extraction methods will be discussed as well as an outline of

  15. Uav Aerial Survey: Accuracy Estimation for Automatically Generated Dense Digital Surface Model and Orthothoto Plan

    NASA Astrophysics Data System (ADS)

    Altyntsev, M. A.; Arbuzov, S. A.; Popov, R. A.; Tsoi, G. V.; Gromov, M. O.

    2016-06-01

    A dense digital surface model is one of the products generated by using UAV aerial survey data. Today more and more specialized software are supplied with modules for generating such kind of models. The procedure for dense digital model generation can be completely or partly automated. Due to the lack of reliable criterion of accuracy estimation it is rather complicated to judge the generation validity of such models. One of such criterion can be mobile laser scanning data as a source for the detailed accuracy estimation of the dense digital surface model generation. These data may be also used to estimate the accuracy of digital orthophoto plans created by using UAV aerial survey data. The results of accuracy estimation for both kinds of products are presented in the paper.

  16. Remote sensing for precision agriculture: Within-field spatial variability analysis and mapping with aerial digital multispectral images

    NASA Astrophysics Data System (ADS)

    Gopalapillai, Sreekala

    2000-10-01

    Advances in remote sensing technology and biological sensors provided the motivation for this study on the applications of aerial multispectral remote sensing in precision agriculture. The feasibility of using high-resolution multispectral remote sensing for precision farming applications such as soil type delineation, identification of crop nitrogen levels, and modeling and mapping of weed density distribution and yield potential within a crop field was explored in this study. Some of the issues such as image calibration for variable lighting conditions and soil background influence were also addressed. Intensity normalization and band ratio methods were found to be adequate image calibration methods to compensate for variable illumination and soil background influence. Several within-field variability factors such as growth stage, field conditions, nutrient availability, crop cultivar, and plant population were found to be dominant in different periods. Unsupervised clustering of color infrared (CIR) image of a field soil was able to identify soil mapping units with an average accuracy of 76%. Spectral reflectance from a crop field was highly correlated to the chlorophyll reading. A regression model developed to predict nitrogen stress in corn identified nitrogen-stressed areas from nitrogen-sufficient areas with a high accuracy (R2 = 0.93). Weed density was highly correlated to the spectral reflectance from a field. One month after planting was found to be a good time to map spatial weed density. The optimum range of resolution for weed mapping was 4 m to 4.5 m for the remote sensing system and the experimental field used in this study. Analysis of spatial yield with respect to spectral reflectance showed that the visible and NIR reflectance were negatively correlated to yield and crop population in heavily weed-infested areas. The yield potential was highly correlated to image indices, especially to normalized brightness. The ANN model developed for one of the

  17. Multi-Model Estimation Based Moving Object Detection for Aerial Video

    PubMed Central

    Zhang, Yanning; Tong, Xiaomin; Yang, Tao; Ma, Wenguang

    2015-01-01

    With the wide development of UAV (Unmanned Aerial Vehicle) technology, moving target detection for aerial video has become a popular research topic in the computer field. Most of the existing methods are under the registration-detection framework and can only deal with simple background scenes. They tend to go wrong in the complex multi background scenarios, such as viaducts, buildings and trees. In this paper, we break through the single background constraint and perceive the complex scene accurately by automatic estimation of multiple background models. First, we segment the scene into several color blocks and estimate the dense optical flow. Then, we calculate an affine transformation model for each block with large area and merge the consistent models. Finally, we calculate subordinate degree to multi-background models pixel to pixel for all small area blocks. Moving objects are segmented by means of energy optimization method solved via Graph Cuts. The extensive experimental results on public aerial videos show that, due to multi background models estimation, analyzing each pixel’s subordinate relationship to multi models by energy minimization, our method can effectively remove buildings, trees and other false alarms and detect moving objects correctly. PMID:25856330

  18. Multi-model estimation based moving object detection for aerial video.

    PubMed

    Zhang, Yanning; Tong, Xiaomin; Yang, Tao; Ma, Wenguang

    2015-04-08

    With the wide development of UAV (Unmanned Aerial Vehicle) technology, moving target detection for aerial video has become a popular research topic in the computer field. Most of the existing methods are under the registration-detection framework and can only deal with simple background scenes. They tend to go wrong in the complex multi background scenarios, such as viaducts, buildings and trees. In this paper, we break through the single background constraint and perceive the complex scene accurately by automatic estimation of multiple background models. First, we segment the scene into several color blocks and estimate the dense optical flow. Then, we calculate an affine transformation model for each block with large area and merge the consistent models. Finally, we calculate subordinate degree to multi-background models pixel to pixel for all small area blocks. Moving objects are segmented by means of energy optimization method solved via Graph Cuts. The extensive experimental results on public aerial videos show that, due to multi background models estimation, analyzing each pixel's subordinate relationship to multi models by energy minimization, our method can effectively remove buildings, trees and other false alarms and detect moving objects correctly.

  19. A Lagrangian stochastic model for aerial spray transport above an oak forest

    USGS Publications Warehouse

    Wang, Yansen; Miller, David R.; Anderson, Dean E.; McManus, Michael L.

    1995-01-01

    An aerial spray droplets' transport model has been developed by applying recent advances in Lagrangian stochastic simulation of heavy particles. A two-dimensional Lagrangian stochastic model was adopted to simulate the spray droplet dispersion in atmospheric turbulence by adjusting the Lagrangian integral time scale along the drop trajectory. The other major physical processes affecting the transport of spray droplets above a forest canopy, the aircraft wingtip vortices and the droplet evaporation, were also included in each time step of the droplets' transport.The model was evaluated using data from an aerial spray field experiment. In generally neutral stability conditions, the accuracy of the model predictions varied from run-to-run as expected. The average root-mean-square error was 24.61 IU cm−2, and the average relative error was 15%. The model prediction was adequate in two-dimensional steady wind conditions, but was less accurate in variable wind condition. The results indicated that the model can simulate successfully the ensemble; average transport of aerial spray droplets under neutral, steady atmospheric wind conditions.

  20. Image Analysis and Modeling

    DTIC Science & Technology

    1976-03-01

    This report summarizes the results of the research program on Image Analysis and Modeling supported by the Defense Advanced Research Projects Agency...The objective is to achieve a better understanding of image structure and to use this knowledge to develop improved image models for use in image ... analysis and processing tasks such as information extraction, image enhancement and restoration, and coding. The ultimate objective of this research is

  1. USGS "iCoast - Did the Coast Change?" Project: Crowd-Tagging Aerial Photographs to Improve Coastal Change Prediction Models

    NASA Astrophysics Data System (ADS)

    Liu, S. B.; Poore, B. S.; Plant, N. G.; Stockdon, H. F.; Morgan, K.; Snell, R.

    2014-12-01

    The U.S. Geological Survey (USGS) has been acquiring oblique aerial photographs of the coast before and after major storms since 1995 and has amassed a database of over 140,000 photographs of the Gulf, Atlantic, and Pacific coasts. USGS coastal scientists use these photographs to document and characterize coastal change caused by storms. The images can also be used to evaluate the accuracy of predictive models of coastal erosion. However, the USGS does not have the personnel to manually analyze all of the photographs taken after a storm. Also, computers cannot yet automatically identify damages and geomorphic changes to the coast from the oblique aerial photographs. There is a high public interest in accessing the limited number of pre- and post-storm photographic pairs the USGS is currently able to share. Recent federal policies that encourage open data and open innovation initiatives have resulted in many federal agencies developing new ways of using citizen science and crowdsourcing techniques to share data and collaborate with the public to accomplish large tasks. The USGS launched a crowdsourcing application in June 2014 called "iCoast - Did the Coast Change?" (http://coastal.er.usgs.gov/icoast) to allow citizens to help USGS scientists identify changes to the coast by comparing USGS aerial photographs taken before and after storms, and then selecting pre-defined tags like "dune scarp" and "sand on road." The tags are accompanied by text definitions and pictorial examples of these coastal morphology terms and serve to informally and passively educate users about coastal hazards. The iCoast application facilitates greater citizen awareness of coastal change and is an educational resource for teachers and students interested in learning about coastal vulnerability. We expect that the citizen observations from iCoast will assist with probabilistic model development to produce more accurate predictions of coastal vulnerability.

  2. Low-Altitude Coastal Aerial Photogrammetry for High-Resolution Seabed Imaging and Habitat Mapping of Shallow Areas

    NASA Astrophysics Data System (ADS)

    Alevizos, E.

    2012-04-01

    This paper explores the application of Kite Aerial Photography at the coastal environment along with digital photogrammetry for seabed geomorphological mapping. This method takes advantage of sea-water clearance that allows the transmission of sunlight through the water column and backscatter of seabed reflection under certain conditions of sunlight, weather and sea state. We analyze the procedure of acquisition, processing and interpretation of kite aerial imagery from the sub-littoral zone up to 5 meters depth. Using a calibrated non-metric digital compact camera we managed to acquire several vertical aerial images from two coastal sites in the Attica Peninsula (Greece) covering an area of approximately 200x100 meters. Both sites express significant geomorphological variability and they have a relatively smooth slope profile. For the photogrammetric processing we acquired topographic and bathymetric survey simultaneously with Kite Aerial Photography using a portable GPS of sub-meter accuracy. In order to deal with bottom control measurements we developed Bottom Control Points which were placed on the seabed. These act like the Ground Control Points and they can be easily deployed in the marine environment. The processing included interior and exterior orientation as well as ortho-rectification of images. This produced final orthomosaics for each site at scales 1:500 - 1:1500 with a resolution of a few centimeters. Interpretation of the seabed was based on color and texture features of certain areas with explicit seabed reflectivity and was supported by underwater photographs for ground truthing. At the final stage of image analysis, we recognized the boundaries (contrasting reflectivity) between different bottom types and digitized them as 2D objects using GIS. Concluding, this project emphasizes on the advantages and physical restrictions of Kite Aerial Photography in mapping small-scale geomorphological features in coastal, estuarine and lagoonal environments

  3. Agricultural cropland mapping using black-and-white aerial photography, Object-Based Image Analysis and Random Forests

    NASA Astrophysics Data System (ADS)

    Vogels, M. F. A.; de Jong, S. M.; Sterk, G.; Addink, E. A.

    2017-02-01

    Land-use and land-cover (LULC) conversions have an important impact on land degradation, erosion and water availability. Information on historical land cover (change) is crucial for studying and modelling land- and ecosystem degradation. During the past decades major LULC conversions occurred in Africa, Southeast Asia and South America as a consequence of a growing population and economy. Most distinct is the conversion of natural vegetation into cropland. Historical LULC information can be derived from satellite imagery, but these only date back until approximately 1972. Before the emergence of satellite imagery, landscapes were monitored by black-and-white (B&W) aerial photography. This photography is often visually interpreted, which is a very time-consuming approach. This study presents an innovative, semi-automated method to map cropland acreage from B&W photography. Cropland acreage was mapped on two study sites in Ethiopia and in The Netherlands. For this purpose we used Geographic Object-Based Image Analysis (GEOBIA) and a Random Forest classification on a set of variables comprising texture, shape, slope, neighbour and spectral information. Overall mapping accuracies attained are 90% and 96% for the two study areas respectively. This mapping method increases the timeline at which historical cropland expansion can be mapped purely from brightness information in B&W photography up to the 1930s, which is beneficial for regions where historical land-use statistics are mostly absent.

  4. Satellite Images and Aerial Photographs of the Effects of Hurricanes Katrina and Rita on Coastal Louisiana

    USGS Publications Warehouse

    Barras, John A.

    2007-01-01

    -water datasets derived from the Landsat TM satellite imagery were combined with 2001 marsh vegetative communities (Chabreck and others, unpub. data, 2001) to identify land-water configurations by marsh community before and after the hurricanes. Links to the Landsat TM images and aerial photographs are given below (figs. 1-29). Comparison of land area before the storms to land area after the storms is made possible by the inclusion of Landsat TM images and aerial photographs taken in the years and months before the storms. The figures are arranged geographically from east to west to follow the chronology of the effects of the storms. For a more detailed analysis of the changes wrought by these storms, see 'Land Area Changes in Coastal Louisiana After Hurricanes Katrina and Rita' (Barras, in press).

  5. Experimental analysis on classification of unmanned aerial vehicle images using the probabilistic latent semantic analysis

    NASA Astrophysics Data System (ADS)

    Yi, Wenbin; Tang, Hong

    2009-10-01

    In this paper, we present a novel algorithm to classify UAV images through the image annotation which is a semi-supervised method. During the annotation process, we first divide whole image into different sizes of blocks and generate suitable visual words which are the K-means clustering centers or just pixels in small size image block. Then, given a set of image blocks for each semantic concept as training data, learning is based on the Probabilistic Latent Semantic Analysis (PLSA). The probability distributions of visual words in every document can be learned through the PLSA model. The labeling of every document (image block) is done by computing the similarity of its feature distribution to the distribution of the training documents with the Kullback-Leibler (K-L) divergence. Finally, the classification of the UAV images will be done by combining all the image blocks in every block size. The UAV images using in our experiments was acquired during Sichuan earthquake in 2008. The results show that smaller size block image will get better classification results.

  6. The use of cyclone modeling in the erection of precast segmental aerial construction

    NASA Astrophysics Data System (ADS)

    Cleveland, S.

    1983-06-01

    The intent of this work is to analyze two methods of obtaining activity duration data in the field for use in the CYCLONE modeling program for determining construction productivity. One method is the traditional stopwatch-type study while the other is utilization of time-lapse photography. The construction activity which will be observed is the erection of an aerial guideway for the Metropolitan Atlanta Rapid Transit Authority (MARTA) rail line. The aerial guideway is being built using precast post-tensioned segmental concrete construction. This method of bridge construction or elevated span construction has proven to be more economical than more conventional methods of construction. One of the primary reasons for lower cost is the speed at which precast post-tensioned segmental concrete construction can be put in place. Field data for the erection procedure will be input into the CYCLONE model to obtain a production rate to be compared to actual field production.

  7. Minimum required capture radius in a coplanar model of the aerial combat problem

    NASA Technical Reports Server (NTRS)

    Breakwell, J. V.; Merz, A. W.

    1977-01-01

    Coplanar aerial combat is modeled with constant speeds and specified turn rates. The minimum capture radius which will always permit capture, regardless of the initial conditions, is calculated. This 'critical' capture radius is also the maximum range which the evader can guarantee indefinitely if the initial range, for example, is large. A composite barrier is constructed which gives the boundary, at any heading, of relative positions for which the capture radius is less than critical.

  8. Automated hotspot analysis with aerial image CD metrology for advanced logic devices

    NASA Astrophysics Data System (ADS)

    Buttgereit, Ute; Trautzsch, Thomas; Kim, Min-ho; Seo, Jung-Uk; Yoon, Young-Keun; Han, Hak-Seung; Chung, Dong Hoon; Jeon, Chan-Uk; Meyers, Gary

    2014-09-01

    Continuously shrinking designs by further extension of 193nm technology lead to a much higher probability of hotspots especially for the manufacturing of advanced logic devices. The CD of these potential hotspots needs to be precisely controlled and measured on the mask. On top of that, the feature complexity increases due to high OPC load in the logic mask design which is an additional challenge for CD metrology. Therefore the hotspot measurements have been performed on WLCD from ZEISS, which provides the benefit of reduced complexity by measuring the CD in the aerial image and qualifying the printing relevant CD. This is especially of advantage for complex 2D feature measurements. Additionally, the data preparation for CD measurement becomes more critical due to the larger amount of CD measurements and the increasing feature diversity. For the data preparation this means to identify these hotspots and mark them automatically with the correct marker required to make the feature specific CD measurement successful. Currently available methods can address generic pattern but cannot deal with the pattern diversity of the hotspots. The paper will explore a method how to overcome those limitations and to enhance the time-to-result in the marking process dramatically. For the marking process the Synopsys WLCD Output Module was utilized, which is an interface between the CATS mask data prep software and the WLCD metrology tool. It translates the CATS marking directly into an executable WLCD measurement job including CD analysis. The paper will describe the utilized method and flow for the hotspot measurement. Additionally, the achieved results on hotspot measurements utilizing this method will be presented.

  9. Influence of Gsd for 3d City Modeling and Visualization from Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Alrajhi, Muhamad; Alam, Zafare; Afroz Khan, Mohammad; Alobeid, Abdalla

    2016-06-01

    Ministry of Municipal and Rural Affairs (MOMRA), aims to establish solid infrastructure required for 3D city modelling, for decision making to set a mark in urban development. MOMRA is responsible for the large scale mapping 1:1,000; 1:2,500; 1:10,000 and 1:20,000 scales for 10cm, 20cm and 40 GSD with Aerial Triangulation data. As 3D city models are increasingly used for the presentation exploration, and evaluation of urban and architectural designs. Visualization capabilities and animations support of upcoming 3D geo-information technologies empower architects, urban planners, and authorities to visualize and analyze urban and architectural designs in the context of the existing situation. To make use of this possibility, first of all 3D city model has to be created for which MOMRA uses the Aerial Triangulation data and aerial imagery. The main concise for 3D city modelling in the Kingdom of Saudi Arabia exists due to uneven surface and undulations. Thus real time 3D visualization and interactive exploration support planning processes by providing multiple stakeholders such as decision maker, architects, urban planners, authorities, citizens or investors with a three - dimensional model. Apart from advanced visualization, these 3D city models can be helpful for dealing with natural hazards and provide various possibilities to deal with exotic conditions by better and advanced viewing technological infrastructure. Riyadh on one side is 5700m above sea level and on the other hand Abha city is 2300m, this uneven terrain represents a drastic change of surface in the Kingdom, for which 3D city models provide valuable solutions with all possible opportunities. In this research paper: influence of different GSD (Ground Sample Distance) aerial imagery with Aerial Triangulation is used for 3D visualization in different region of the Kingdom, to check which scale is more sophisticated for obtaining better results and is cost manageable, with GSD (7.5cm, 10cm, 20cm and 40cm

  10. Assessment of the Quality of Digital Terrain Model Produced from Unmanned Aerial System Imagery

    NASA Astrophysics Data System (ADS)

    Kosmatin Fras, M.; Kerin, A.; Mesarič, M.; Peterman, V.; Grigillo, D.

    2016-06-01

    Production of digital terrain model (DTM) is one of the most usual tasks when processing photogrammetric point cloud generated from Unmanned Aerial System (UAS) imagery. The quality of the DTM produced in this way depends on different factors: the quality of imagery, image orientation and camera calibration, point cloud filtering, interpolation methods etc. However, the assessment of the real quality of DTM is very important for its further use and applications. In this paper we first describe the main steps of UAS imagery acquisition and processing based on practical test field survey and data. The main focus of this paper is to present the approach to DTM quality assessment and to give a practical example on the test field data. For data processing and DTM quality assessment presented in this paper mainly the in-house developed computer programs have been used. The quality of DTM comprises its accuracy, density, and completeness. Different accuracy measures like RMSE, median, normalized median absolute deviation and their confidence interval, quantiles are computed. The completeness of the DTM is very often overlooked quality parameter, but when DTM is produced from the point cloud this should not be neglected as some areas might be very sparsely covered by points. The original density is presented with density plot or map. The completeness is presented by the map of point density and the map of distances between grid points and terrain points. The results in the test area show great potential of the DTM produced from UAS imagery, in the sense of detailed representation of the terrain as well as good height accuracy.

  11. 3D Modelling of Inaccessible Areas using UAV-based Aerial Photography and Structure from Motion

    NASA Astrophysics Data System (ADS)

    Obanawa, Hiroyuki; Hayakawa, Yuichi; Gomez, Christopher

    2014-05-01

    In hardly accessible areas, the collection of 3D point-clouds using TLS (Terrestrial Laser Scanner) can be very challenging, while airborne equivalent would not give a correct account of subvertical features and concave geometries like caves. To solve such problem, the authors have experimented an aerial photography based SfM (Structure from Motion) technique on a 'peninsular-rock' surrounded on three sides by the sea at a Pacific coast in eastern Japan. The research was carried out using UAS (Unmanned Aerial System) combined with a commercial small UAV (Unmanned Aerial Vehicle) carrying a compact camera. The UAV is a DJI PHANTOM: the UAV has four rotors (quadcopter), it has a weight of 1000 g, a payload of 400 g and a maximum flight time of 15 minutes. The camera is a GoPro 'HERO3 Black Edition': resolution 12 million pixels; weight 74 g; and 0.5 sec. interval-shot. The 3D model has been constructed by digital photogrammetry using a commercial SfM software, Agisoft PhotoScan Professional®, which can generate sparse and dense point-clouds, from which polygonal models and orthophotographs can be calculated. Using the 'flight-log' and/or GCPs (Ground Control Points), the software can generate digital surface model. As a result, high-resolution aerial orthophotographs and a 3D model were obtained. The results have shown that it was possible to survey the sea cliff and the wave cut-bench, which are unobservable from land side. In details, we could observe the complexity of the sea cliff that is nearly vertical as a whole while slightly overhanging over the thinner base. The wave cut bench is nearly flat and develops extensively at the base of the cliff. Although there are some evidences of small rockfalls at the upper part of the cliff, there is no evidence of very recent activity, because no fallen rock exists on the wave cut bench. This system has several merits: firstly lower cost than the existing measuring methods such as manned-flight survey and aerial laser

  12. Combined aerial and terrestrial images for complete 3D documentation of Singosari Temple based on Structure from Motion algorithm

    NASA Astrophysics Data System (ADS)

    Hidayat, Husnul; Cahyono, A. B.

    2016-11-01

    Singosaritemple is one of cultural heritage building in East Java, Indonesia which was built in 1300s and restorated in 1934-1937. Because of its history and importance, complete documentation of this temple is required. Nowadays with the advent of low cost UAVs combining aerial photography with terrestrial photogrammetry gives more complete data for 3D documentation. This research aims to make complete 3D model of this landmark from aerial and terrestrial photographs with Structure from Motion algorithm. To establish correct scale, position, and orientation, the final 3D model was georeferenced with Ground Control Points in UTM 49S coordinate system. The result shows that all facades, floor, and upper structures can be modeled completely in 3D. In terms of 3D coordinate accuracy, the Root Mean Square Errors (RMSEs) are RMSEx=0,041 m; RMSEy=0,031 m; RMSEz=0,049 m which represent 0.071 m displacement in 3D space. In addition the mean difference of lenght measurements of the object is 0,057 m. With this accuracy, this method can be used to map the site up to 1:237 scale. Although the accuracy level is still in centimeters, the combined aerial and terrestrial photographs with Structure from Motion algorithm can provide complete and visually interesting 3D model.

  13. Model to predict aerial dispersal of bacteria during environmental release.

    PubMed Central

    Knudsen, G R

    1989-01-01

    Risk assessment for genetically engineered bacteria sprayed onto crops includes determination of off-site dispersal and deposition. The ability to predict microbial dispersal patterns is essential to characterize the uncertainty (risk) associated with environmental release of recombinant organisms. Toward this end, a particle dispersal model was developed to predict recovery of bacteria on fallout plates at various distances and directions about a test site. The microcomputer simulation incorporates particle size distribution, wind speed and direction, turbulence, evaporation, sedimentation, and mortality, with a time step of 0.5 s. The model was tested against data reported from three field applications of nonrecombinant bacteria and two applications of recombinant bacteria. Simulated dispersal of 10(5) particles was compared with reported deposition measurements. The model may be useful in defining appropriate populations of organisms for release, methods of release or application, characteristics of a release site that influence containment or dispersal, and in developing an appropriate sampling methodology for monitoring the dispersal of organisms such as genetically engineered bacteria. PMID:2604402

  14. Assessing the quality of digital elevation models obtained from mini unmanned aerial vehicles for overland flow modelling in urban areas

    NASA Astrophysics Data System (ADS)

    Leitão, João P.; Moy de Vitry, Matthew; Scheidegger, Andreas; Rieckermann, Jörg

    2016-04-01

    Precise and detailed digital elevation models (DEMs) are essential to accurately predict overland flow in urban areas. Unfortunately, traditional sources of DEM, such as airplane light detection and ranging (lidar) DEMs and point and contour maps, remain a bottleneck for detailed and reliable overland flow models, because the resulting DEMs are too coarse to provide DEMs of sufficient detail to inform urban overland flows. Interestingly, technological developments of unmanned aerial vehicles (UAVs) suggest that they have matured enough to be a competitive alternative to satellites or airplanes. However, this has not been tested so far. In this study we therefore evaluated whether DEMs generated from UAV imagery are suitable for urban drainage overland flow modelling. Specifically, 14 UAV flights were conducted to assess the influence of four different flight parameters on the quality of generated DEMs: (i) flight altitude, (ii) image overlapping, (iii) camera pitch, and (iv) weather conditions. In addition, we compared the best-quality UAV DEM to a conventional lidar-based DEM. To evaluate both the quality of the UAV DEMs and the comparison to lidar-based DEMs, we performed regression analysis on several qualitative and quantitative metrics, such as elevation accuracy, quality of object representation (e.g. buildings, walls and trees) in the DEM, which were specifically tailored to assess overland flow modelling performance, using the flight parameters as explanatory variables. Our results suggested that, first, as expected, flight altitude influenced the DEM quality most, where lower flights produce better DEMs; in a similar fashion, overcast weather conditions are preferable, but weather conditions and other factors influence DEM quality much less. Second, we found that for urban overland flow modelling, the UAV DEMs performed competitively in comparison to a traditional lidar-based DEM. An important advantage of using UAVs to generate DEMs in urban areas is

  15. ISSUES IN DIGITAL IMAGE PROCESSING OF AERIAL PHOTOGRAPHY FOR MAPPING SUBMERSED AQUATIC VEGETATION

    EPA Science Inventory

    The paper discusses the numerous issues that needed to be addressed when developing a methodology for mapping Submersed Aquatic Vegetation (SAV) from digital aerial photography. Specifically, we discuss 1) choice of film; 2) consideration of tide and weather constraints; 3) in-s...

  16. Geomatics techniques applied to time series of aerial images for multitemporal geomorphological analysis of the Miage Glacier (Mont Blanc).

    NASA Astrophysics Data System (ADS)

    Perotti, Luigi; Carletti, Roberto; Giardino, Marco; Mortara, Giovanni

    2010-05-01

    The Miage glacier is the major one in the Italian side of the Mont Blanc Massif, the third by area and the first by longitudinal extent among Italian glaciers. It is a typical debris covered glacier, since the end of the L.I.A. The debris coverage reduces ablation, allowing a relative stability of the glacier terminus, which is characterized by a wide and articulated moraine apparatus. For its conservative landforms, the Miage Glacier has a great importance for the analysis of the geomorphological response to recent climatic changes. Thanks to an organized existing archive of multitemporal aerial images (1935 to present) a photogrammetric approach has been applied to detect recent geomorphological changes in the Miage glacial basin. The research team provided: a) to digitize all the available images (still in analogic form) through photogrammetric scanners (very low image distortions devices) taking care of correctly defining the resolution of the acquisition compared to the scale mapping images are suitable for; b) to import digitized images into an appropriate digital photogrammetry software environment; c) to manage images in order, where possible, to carried out the stereo models orientation necessary for 3D navigation and plotting of critical geometric features of the glacier. Recognized geometric feature, referring to different periods, can be transferred to vector layers and imported in a GIS for further comparisons and investigations; d) to produce multi-temporal Digital Elevation Models for glacier volume changes; e) to perform orthoprojection of such images to obtain multitemporal orthoimages useful for areal an planar terrain evaluation and thematic analysis; f) to evaluate both planimetric positioning and height determination accuracies reachable through the photogrammetric process. Users have to known reliability of the measures they can do over such products. This can drive them to define the applicable field of this approach and this can help them to

  17. Towards digital terrain modeling with unmanned aerial vehicles and SfM point clouds

    NASA Astrophysics Data System (ADS)

    Anders, Niels; Masselink, Rens; Keesstra, Saskia

    2015-04-01

    Unmanned Aerial Vehicles (UAVs) are excellent tools for the acquisition of very high-resolution digital surface models using low altitude aerial photography and photogrammetric, 'Structure-from-Motion' (SfM), processing. Terrain reconstructions are produced by interpolating ground points after removal of non-ground points. While extremely detailed in non-vegetated areas, UAV point clouds are less suitable for terrain reconstructions of vegetated areas due to the inability of aerial photography to penetrate through vegetation for collecting ground points. This hinders for example detailed modeling of sediment transport on hillslopes towards vegetated lower areas and channels with riparian vegetation. We propose complementing UAV SfM point cloud data with alternative data sources to fill in the data gaps in vegetated areas. Firstly, SfM point clouds are classified into ground and non-ground points based on both color values and neighborhood statistics. Secondly, non-ground points are removed and data gaps are complemented with external data points. Thirdly, the combined point cloud is interpolated into a digital terrain model (DTM) using the natural neighbor interpolation technique. We demonstrate the methodology with three scenarios of terrain reconstructions in two study areas in North and Southeast Spain: i.e. a linear slope below sparsely distributed trees without the need of supplementary data points (1), and a gully with riparian vegetation combined with 5 m LiDAR data (2) or with manually measured dGPS data points (3). While the spatial resolution is significantly less below vegetated areas compared to non-vegetated areas, the results suggest significant improvements of the reconstructed topography, making the DTM more useful for soil erosion studies and sediment modeling.

  18. Planialtimetric Accuracy Evaluation of Digital Surface Model (dsm) and Digital Terrain Model (dtm) Obtained from Aerial Survey with LIDAR

    NASA Astrophysics Data System (ADS)

    Cruz, C. B. M.; Barros, R. S.; Rabaco, L. M. L.

    2012-07-01

    It's noticed a significant increase in the development of orbital and airborne sensors that enable the extraction of three-dimensional data. Consequently, it's important the increment of studies about the quality of altimetric values derived from these sensors to verify if the improvements implemented in the acquisition of data may influence the results. In this context, as part of a larger project that aims to evaluate the accuracy of various sensors, this work aims to analysis the planialtimetric accuracy of DSM and DTM generated from an aerial survey with LIDAR, using as reference for the planimetric analysis of the orthophotos obtained. The project was developed for an area of São Sebastião city, located in the basin of the North Coast of São Paulo state. The area's relief is very steep, with a predominance of dense forest vegetation, typical of the Atlantic Forest. All points have been established in the field, with the use of GNSS of one frequency (L1) through static relative positioning, acquiring a minimum of 1,500 epochs, for a distance less than 20 km to the base. In this work it's considered the Brazilian standard specifications for classification of cartographic bases (PEC). The Brazilian company responsible for the aerial survey (LACTEC) gave the following products for analysis: point clouds in raw format (x, y, z) using orthometric heights; point clouds (first and last pulse) for each range of flight to verify systematic errors; DTM uniformly spaced, filtering small natural obstacles, buildings and vegetation, in Geotiff format; DSM also uniformly spaced, in Geotiff format; and the mosaic of georeferenced digital images. The analysis realized on products from the LIDAR indicated their adoption to the scales 1:2,000 (Class A for the orthophotos and Class B for the DTM) and 1:5,000 (class C for the DSM). There were no indications of trends in the results. The average error was 0.01 m. It's important that new areas with different topographic

  19. [Building Change Detection Based on Multi-Level Rules Classification with Airborne LiDAR Data and Aerial Images].

    PubMed

    Gong, Yi-long; Yan, Li

    2015-05-01

    The present paper proposes a new building change detection method combining Lidar point cloud with aerial image, using multi-level rules classification algorithm, to solve building change detection problem between these two kinds of heterogeneous data. Then, a morphological post-processing method combined with area threshold is proposed. Thus, a complete building change detection processing flow that can be applied to actual production is proposed. Finally, the effectiveness of the building change detection method is evaluated, processing the 2010 airborne LiDAR point cloud data and 2009 high resolution aerial image of Changchun City, Jilin province, China; in addition, compared with the object-oriented building change detection method based on support vector machine (SVM) classification, more analysis and evaluation of the suggested method is given. Experiment results show that the performance of the proposed building change detection method is ideal. Its Kappa index is 0. 90, and correctness is 0. 87, which is higher than the object-oriented building change detection method based on SVM classification.

  20. Using GPS/INS data to enhance image matching for real-time aerial triangulation

    NASA Astrophysics Data System (ADS)

    Tanathong, Supannee; Lee, Impyeong

    2014-11-01

    Direct georeferencing is a promising technique for determining the exterior orientation parameters (EO) of a camera in real-time through the integration of GPS/INS sensors. Instead of using expensive devices, we improve the accuracy of the directly measured EOs through aerial triangulation (AT) and rely on tie-points. In this work, using GPS/INS data, we enhance the KLT tracker to achieve accuracy and speed that is compatible with real-time aerial triangulation. Given GPS/INS data from medium-grade sensors, the proposed system is 48% faster than the original work and tie-points extracted by our system are 6.33% more accurate and more evenly distributed than tie-points extracted by the original work. The AT processing results show that tie-points from the proposed work can reduce the RMSE of the directly measured EOs by 17.87% for position and 23.37% for attitude. Thus, we conclude that our proposed system can be integrated with real-time aerial triangulation.

  1. MaNIAC-UAV - a methodology for automatic pavement defects detection using images obtained by Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Henrique Castelo Branco, Luiz; César Lima Segantine, Paulo

    2015-09-01

    Intelligent Transportation Systems - ITS is a set of integrated technologies (Remote Sensing, Image Processing, Communications Systems and others) that aim to offer services and advanced traffic management for the several transportation modes (road, air and rail). Collect data on the characteristics and conditions of the road surface and keep them update is an important and difficult task that needs to be currently managed in order to reduce accidents and vehicle maintenance costs. Nowadays several roads and highways are paved, but usually there is insufficient updated data about current condition and status. There are different types of pavement defects on the roads and to keep them in good condition they should be constantly monitored and maintained according to pavement management strategy. This paper presents a methodology to obtain, automatically, information about the conditions of the highway asphalt pavement. Data collection was done through remote sensing using an UAV (Unmanned Aerial Vehicle) and the image processing and pattern recognition techniques through Geographic Information System.

  2. Assessing the Accuracy of Ortho-image using Photogrammetric Unmanned Aerial System

    NASA Astrophysics Data System (ADS)

    Jeong, H. H.; Park, J. W.; Kim, J. S.; Choi, C. U.

    2016-06-01

    Smart-camera can not only be operated under network environment anytime and any place but also cost less than the existing photogrammetric UAV since it provides high-resolution image, 3D location and attitude data on a real-time basis from a variety of built-in sensors. This study's proposed UAV photogrammetric method, low-cost UAV and smart camera were used. The elements of interior orientation were acquired through camera calibration. The image triangulation was conducted in accordance with presence or absence of consideration of the interior orientation (IO) parameters determined by camera calibration, The Digital Elevation Model (DEM) was constructed using the image data photographed at the target area and the results of the ground control point survey. This study also analyzes the proposed method's application possibility by comparing a Ortho-image the results of the ground control point survey. Considering these study findings, it is suggested that smartphone is very feasible as a payload for UAV system. It is also expected that smartphone may be loaded onto existing UAV playing direct or indirect roles significantly.

  3. Semi-automted analysis of high-resolution aerial images to quantify docks in Upper Midwest glacial lakes

    USGS Publications Warehouse

    Beck, Marcus W.; Vondracek, Bruce C.; Hatch, Lorin K.; Vinje, Jason

    2013-01-01

    Lake resources can be negatively affected by environmental stressors originating from multiple sources and different spatial scales. Shoreline development, in particular, can negatively affect lake resources through decline in habitat quality, physical disturbance, and impacts on fisheries. The development of remote sensing techniques that efficiently characterize shoreline development in a regional context could greatly improve management approaches for protecting and restoring lake resources. The goal of this study was to develop an approach using high-resolution aerial photographs to quantify and assess docks as indicators of shoreline development. First, we describe a dock analysis workflow that can be used to quantify the spatial extent of docks using aerial images. Our approach incorporates pixel-based classifiers with object-based techniques to effectively analyze high-resolution digital imagery. Second, we apply the analysis workflow to quantify docks for 4261 lakes managed by the Minnesota Department of Natural Resources. Overall accuracy of the analysis results was 98.4% (87.7% based on ) after manual post-processing. The analysis workflow was also 74% more efficient than the time required for manual digitization of docks. These analyses have immediate relevance for resource planning in Minnesota, whereas the dock analysis workflow could be used to quantify shoreline development in other regions with comparable imagery. These data can also be used to better understand the effects of shoreline development on aquatic resources and to evaluate the effects of shoreline development relative to other stressors.

  4. Quantitative analysis of drainage obtained from aerial photographs and RBV/LANDSAT images

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Formaggio, A. R.; Epiphanio, J. C. N.; Filho, M. V.

    1981-01-01

    Data obtained from aerial photographs (1:60,000) and LANDSAT return beam vidicon imagery (1:100,000) concerning drainage density, drainage texture, hydrography density, and the average length of channels were compared. Statistical analysis shows that significant differences exist in data from the two sources. The highly drained area lost more information than the less drained area. In addition, it was observed that the loss of information about the number of rivers was higher than that about the length of the channels.

  5. Object Based Agricultural Land Cover Classification Map of Shadowed Areas from Aerial Image and LIDAR Data Using Support Vector Machine

    NASA Astrophysics Data System (ADS)

    Alberto, R. T.; Serrano, S. C.; Damian, G. B.; Camaso, E. E.; Celestino, A. B.; Hernando, P. J. C.; Isip, M. F.; Orge, K. M.; Quinto, M. J. C.; Tagaca, R. C.

    2016-06-01

    Aerial image and LiDAR data offers a great possibility for agricultural land cover mapping. Unfortunately, these images leads to shadowy pixels. Management of shadowed areas for classification without image enhancement were investigated. Image segmentation approach using three different segmentation scales were used and tested to segment the image for ground features since only the ground features are affected by shadow caused by tall features. The RGB band and intensity were the layers used for the segmentation having an equal weights. A segmentation scale of 25 was found to be the optimal scale that will best fit for the shadowed and non-shadowed area classification. The SVM using Radial Basis Function kernel was then applied to extract classes based on properties extracted from the Lidar data and orthophoto. Training points for different classes including shadowed areas were selected homogeneously from the orthophoto. Separate training points for shadowed areas were made to create additional classes to reduced misclassification. Texture classification and object-oriented classifiers have been examined to reduced heterogeneity problem. The accuracy of the land cover classification using 25 scale segmentation after accounting for the shadow detection and classification was significantly higher compared to higher scale of segmentation.

  6. Thermal Imaging of Subsurface Coal Fires by means of an Unmanned Aerial Vehicle (UAV) in the Autonomous Province Xinjiang, PRC

    NASA Astrophysics Data System (ADS)

    Vasterling, Margarete; Schloemer, Stefan; Fischer, Christian; Ehrler, Christoph

    2010-05-01

    Spontaneous combustion of coal and resulting coal fires lead to very high temperatures in the subsurface. To a large amount the heat is transferred to the surface by convective and conductive transport inducing a more or less pronounced thermal anomaly. During the past decade satellite-based infrared-imaging (ASTER, MODIS) was the method of choice for coal fire detection on a local and regional scale. However, the resolution is by far too low for a detailed analysis of single coal fires which is essential prerequisite for corrective measures (i.e. fire fighting) and calculation of carbon dioxide emission based on a complex correlation between energy release and CO2 generation. Consequently, within the framework of the Sino-German research project "Innovative Technologies for Exploration, Extinction and Monitoring of Coal Fires in Northern China", a new concept was developed and successfully tested. An unmanned aerial vehicle (UAV) was equipped with a lightweight camera for thermografic (resolution 160 by 120 pixel, dynamic range -20 to 250°C) and for visual imaging. The UAV designed as an octocopter is able to hover at GPS controlled waypoints during predefined flight missions. The application of a UAV has several advantages. Compared to point measurements on the ground the thermal imagery quickly provides the spatial distribution of the temperature anomaly with a much better resolution. Areas otherwise not accessible (due to topography, fire induced cracks, etc.) can easily be investigated. The results of areal surveys on two coal fires in Xinjiang are presented. Georeferenced thermal and visual images were mosaicked together and analyzed. UAV-born data do well compared to temperatures measured directly on the ground and cover large areas in detail. However, measuring surface temperature alone is not sufficient. Simultaneous measurements made at the surface and in roughly 15cm depth proved substantial temperature gradients in the upper soil. Thus the temperature

  7. Mathematical model of unmanned aerial vehicle used for endurance autonomous monitoring

    SciTech Connect

    Chelaru, Teodor-Viorel; Chelaru, Adrian

    2014-12-10

    The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used to local observations, surveillance and monitoring interest area. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using nonlinear model, as well as a linear one for obtaining guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and autonomous control system. This theoretical development allows us to build stability matrix, command matrix and control matrix and finally to analyse the stability of autonomous UAV flight. A robust guidance system, based on uncoupled state will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analysed.

  8. Coastal Digital Surface Model on Low Contrast Images

    NASA Astrophysics Data System (ADS)

    Rosu, A.-M.; Assenbaum, M.; De la Torre, Y.; Pierrot-Deseilligny, M.

    2015-08-01

    Coastal sandy environments are extremely dynamic and require regular monitoring that can easily be achieved by using an unmanned aerial system (UAS) including a drone and a photo camera. The acquired images have low contrast and homogeneous texture. Using these images and with very few, if any, ground control points (GCPs), it is difficult to obtain a digital surface model (DSM) by classical correlation and automatic interest points determination approach. A possible response to this problem is to work with enhanced, contrast filtered images. To achieve this, we use and tune the free open-source software MicMac.

  9. A Mobile System for Measuring Water Surface Velocities Using Unmanned Aerial Vehicle and Large-Scale Particle Image Velocimetry

    NASA Astrophysics Data System (ADS)

    Chen, Y. L.

    2015-12-01

    Measurement technologies for velocity of river flow are divided into intrusive and nonintrusive methods. Intrusive method requires infield operations. The measuring process of intrusive methods are time consuming, and likely to cause damages of operator and instrument. Nonintrusive methods require fewer operators and can reduce instrument damages from directly attaching to the flow. Nonintrusive measurements may use radar or image velocimetry to measure the velocities at the surface of water flow. The image velocimetry, such as large scale particle image velocimetry (LSPIV) accesses not only the point velocity but the flow velocities in an area simultaneously. Flow properties of an area hold the promise of providing spatially information of flow fields. This study attempts to construct a mobile system UAV-LSPIV by using an unmanned aerial vehicle (UAV) with LSPIV to measure flows in fields. The mobile system consists of a six-rotor UAV helicopter, a Sony nex5T camera, a gimbal, an image transfer device, a ground station and a remote control device. The activate gimbal helps maintain the camera lens orthogonal to the water surface and reduce the extent of images being distorted. The image transfer device can monitor the captured image instantly. The operator controls the UAV by remote control device through ground station and can achieve the flying data such as flying height and GPS coordinate of UAV. The mobile system was then applied to field experiments. The deviation of velocities measured by UAV-LSPIV of field experiments and handhold Acoustic Doppler Velocimeter (ADV) is under 8%. The results of the field experiments suggests that the application of UAV-LSPIV can be effectively applied to surface flow studies.

  10. Modeling and control for heave dynamics of a flexible wing micro aerial vehicle distributed parameter system

    NASA Astrophysics Data System (ADS)

    Kuhn, Lisa M.

    2011-07-01

    In recent years, much research has been motivated by the idea of biologically-inspired flight. It is a conjecture of the United States Air Force that incorporating characteristics of biological flight into air vehicles will significantly improve the maneuverability and performance of modern aircraft. Although there are studies which involve the aerodynamics, structural dynamics, modeling, and control of flexible wing micro aerial vehicles (MAVs), issues of control and vehicular modeling as a whole are largely unexplored. Modeling with such dynamics lends itself to systems of partial differential equations (PDEs) with nonlinearities, and limited control theory is available for such systems. In this work, a multiple component structure consisting of two Euler-Bernoulli beams connected to a rigid mass is used to model the heave dynamics of an aeroelastic wing MAV, which is acted upon by a nonlinear aerodynamic lift force. We seek to employ tools from distributed parameter modeling and linear control theory in an effort to achieve agile flight potential of flexible, morphable wing MAV airframes. Theoretical analysis of the model is conducted, which includes generating solutions to the eigenvalue problem for the system and determining well-posedness and the attainment of a C 0-semigroup for the linearly approximated model. In order to test the model's ability to track to a desired state and to gain insight into optimal morphing trajectories, two control objectives are employed on the model: target state tracking and morphing trajectory over time.

  11. Aerial Explorers

    NASA Technical Reports Server (NTRS)

    Young, Larry A.; Pisanich, Greg; Ippolito, Corey

    2005-01-01

    This paper presents recent results from a mission architecture study of planetary aerial explorers. In this study, several mission scenarios were developed in simulation and evaluated on success in meeting mission goals. This aerial explorer mission architecture study is unique in comparison with previous Mars airplane research activities. The study examines how aerial vehicles can find and gain access to otherwise inaccessible terrain features of interest. The aerial explorer also engages in a high-level of (indirect) surface interaction, despite not typically being able to takeoff and land or to engage in multiple flights/sorties. To achieve this goal, a new mission paradigm is proposed: aerial explorers should be considered as an additional element in the overall Entry, Descent, Landing System (EDLS) process. Further, aerial vehicles should be considered primarily as carrier/utility platforms whose purpose is to deliver air-deployed sensors and robotic devices, or symbiotes, to those high-value terrain features of interest.

  12. Research on the processing technology of low-altitude unmanned aerial vehicle images

    NASA Astrophysics Data System (ADS)

    Tang, Shihua; Liu, Yintao; Li, Feida; Zhou, Conglin; Huang, Qing; Xu, Hongwei

    2015-12-01

    The UAV system acts as one of the infrastructure of earth observation, with its mobility, high speed, flexibility, economy and other remarkable technical advantages, has been widely used in various fields of the national economic construction, such as agricultural monitoring, resource development, disaster emergency treatment. Taking an actual engineering as a case study in this paper, the method and the skill of making digital orthophoto map was stated by using the UASMaster, the professional UAV data processing software, based on the eBee unmanned aerial vehicle. Finally, the precision of the DOM was analyzed in detail through two methods, overlapping the DOM with the existing DLG of the region and contrasting the points of the existing DLG of 1:1000 scale with the corresponding checkpoints of the stereomodel.

  13. An Automated Approach to Agricultural Tile Drain Detection and Extraction Utilizing High Resolution Aerial Imagery and Object-Based Image Analysis

    NASA Astrophysics Data System (ADS)

    Johansen, Richard A.

    Subsurface drainage from agricultural fields in the Maumee River watershed is suspected to adversely impact the water quality and contribute to the formation of harmful algal blooms (HABs) in Lake Erie. In early August of 2014, a HAB developed in the western Lake Erie Basin that resulted in over 400,000 people being unable to drink their tap water due to the presence of a toxin from the bloom. HAB development in Lake Erie is aided by excess nutrients from agricultural fields, which are transported through subsurface tile and enter the watershed. Compounding the issue within the Maumee watershed, the trend within the watershed has been to increase the installation of tile drains in both total extent and density. Due to the immense area of drained fields, there is a need to establish an accurate and effective technique to monitor subsurface farmland tile installations and their associated impacts. This thesis aimed at developing an automated method in order to identify subsurface tile locations from high resolution aerial imagery by applying an object-based image analysis (OBIA) approach utilizing eCognition. This process was accomplished through a set of algorithms and image filters, which segment and classify image objects by their spectral and geometric characteristics. The algorithms utilized were based on the relative location of image objects and pixels, in order to maximize the robustness and transferability of the final rule-set. These algorithms were coupled with convolution and histogram image filters to generate results for a 10km2 study area located within Clay Township in Ottawa County, Ohio. The eCognition results were compared to previously collected tile locations from an associated project that applied heads-up digitizing of aerial photography to map field tile. The heads-up digitized locations were used as a baseline for the accuracy assessment. The accuracy assessment generated a range of agreement values from 67.20% - 71.20%, and an average

  14. Estimation of aerial deposition and foliar uptake of xenobiotics: Assessment of current models

    SciTech Connect

    Link, S.O.; Fellows, R.J.; Cataldo, D.A.; Droppo, J.G.; Van Voris, P.

    1987-10-01

    This report reviews existing mathematical and/or computer simulation models that estimate xenobiotic deposition to and transport through (both curricular and stomatal) vegetative surfaces. The report evaluates the potential for coupling the best of those models to the existing Uptake, Translocation, Accumulation, and Biodegradation model to be used for future xenobiotic exposure assessments. Here xenobiotic compounds are defined as airborne contaminants, both organic and gaseous pollutants, that are introduced into the environment by man. Specifically this document provides a detailed review of the state-of-the-art models that addressed aerial deposition of particles and gases to foliage; foliar and cuticular transport, metabolism, and uptake of organic xenobiotics; and stomatal transport of gaseous and volatile organic xenobiotic pollutants. Where detailed information was available, parameters for each model are provided on a chemical by chemical as well as species by species basis. Sufficient detail is provided on each model to assess the potential for adapting or coupling the model to the existing UTAB plant exposure model. 126 refs., 6 figs., 10 tabs.

  15. From the air to digital landscapes: generating reach-scale topographic models from aerial photography in gravel-bed rivers

    NASA Astrophysics Data System (ADS)

    Vericat, Damià; Narciso, Efrén; Béjar, Maria; Tena, Álvaro; Brasington, James; Gibbins, Chris; Batalla, Ramon J.

    2014-05-01

    Digital Terrain Models are fundamental to characterise landscapes, to support numerical modelling and to monitor topographic changes. Recent advances in topography, remote sensing and geomatics are providing new opportunities to obtain high density/quality and rapid topographic data. In this paper we present an integrated methodology to rapidly obtain reach scale topographic models of fluvial systems. This methodology has been tested and is being applied to develop event-scale terrain models of a 11-km river reach in the highly dynamic Upper Cinca (NE Iberian Peninsula). This research is conducted in the background of the project MorphSed. The methodology integrates (a) the acquisition of dense point clouds of the exposed floodplain (aerial photography and digital photogrammetry); (b) the registration of all observations to the same coordinate system (using RTK-GPS surveyed GCPs); (c) the acquisition of bathymetric data (using aDcp measurements integrated with RTK-GPS); (d) the intelligent decimation of survey observations (using the open source TopCat toolkit) and, finally, (e) data fusion (elaborating Digital Elevation Models). In this paper special emphasis is given to the acquisition and registration of point clouds. 3D point clouds are obtained from aerial photography and by means of automated digital photogrammetry. Aerial photographs are taken at 275 meters above the ground by means of a SLR digital camera manually operated from an autogyro. Four flight paths are defined in order to cover the 11 km long and 500 meters wide river reach. A total of 45 minutes are required to fly along these paths. Camera has been previously calibrated with the objective to ensure image resolution at around 5 cm. A total of 220 GCPs are deployed and RTK-GPS surveyed before the flight is conducted. Two people and one full workday are necessary to deploy and survey the full set of GCPs. Field data acquisition may be finalised in less than 2 days. Structure-from-Motion is

  16. Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

    PubMed

    Ma, Xu; Cheng, Yongmei; Hao, Shuai

    2016-12-10

    Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

  17. Automated Identification of Rivers and Shorelines in Aerial Imagery Using Image Texture

    DTIC Science & Technology

    2011-01-01

    defining the criteria for segmenting the image. For these cases certain automated, unsupervised (or minimally supervised), image classification ...banks, image analysis, edge finding, photography, satellite, texture, entropy 16. SECURITY CLASSIFICATION OF: a. REPORT Unclassified b. ABSTRACT...high resolution bank geometry. Much of the globe is covered by various sorts of multi- or hyperspectral imagery and numerous techniques have been

  18. Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods

    NASA Astrophysics Data System (ADS)

    Osipov, Gennady

    2013-04-01

    includes noncontact registration of eye motion, reconstruction of "attention landscape" fixed by the expert, recording the comments of the expert who is a specialist in the field of images` interpretation, and transfer this information into knowledge base.Creation of base of ophthalmologic images (OI) includes making semantic contacts from great number of OI based on analysis of OI and expert's comments.Processing of OI and making generalized OI (GOI) is realized by inductive logic algorithms and consists in synthesis of structural invariants of OI. The mode of recognition and interpretation of unknown images consists of several stages, which include: comparison of unknown image with the base of structural invariants of OI; revealing of structural invariants in unknown images; ynthesis of interpretive message of the structural invariants base and OI base (the experts` comments stored in it). We want to emphasize that the training mode does not assume special involvement of experts to teach the system - it is realized in the process of regular experts` work on image interpretation and it becomes possible after installation of a special apparatus for non contact registration of experts` attention. Consequently, the technology, which principles is described there, provides fundamentally new effective solution to the problem of exploration of mineral resource deposits based on computer analysis of aerial and satellite image data.

  19. Validation of Vehicle Candidate Areas in Aerial Images Using Color Co-Occurrence Histograms

    NASA Astrophysics Data System (ADS)

    Leister, W.; Tuermer, S.; Reinartz, P.; Hoffmann, K. H.; Stilla, U.

    2013-10-01

    Traffic monitoring plays an important role in transportation management. In addition, airborne acquisition enables a flexible and realtime mapping for special traffic situations e.g. mass events and disasters. Also the automatic extraction of vehicles from aerial imagery is a common application. However, many approaches focus on the target object only. As an extension to previously developed car detection techniques, a validation scheme is presented. The focus is on exploiting the background of the vehicle candidates as well as their color properties in the HSV color space. Therefore, texture of the vehicle background is described by color co-occurrence histograms. From all resulting histograms a likelihood function is calculated giving a quantity value to indicate whether the vehicle candidate is correctly classified. Only a few robust parameters have to be determined. Finally, the strategy is tested with a dataset of dense urban areas from the inner city of Munich, Germany. First results show that certain regions which are often responsible for false positive detections, such as vegetation or road markings, can be excluded successfully.

  20. Weakly-Supervised Multimodal Kernel for Categorizing Aerial Photographs.

    PubMed

    Xia, Yingjie; Zhang, Luming; Liu, Zhenguang; Nie, Liqiang; Li, Xuelong

    2016-12-14

    Accurately distinguishing aerial photographs from different categories is a promising technique in computer vision. It can facilitate a series of applications such as video surveillance and vehicle navigation. In the paper, a new image kernel is proposed for effectively recognizing aerial photographs. The key is to encode high-level semantic cues into local image patches in a weakly-supervised way, and integrate multimodal visual features using a newly-developed hashing algorithm. The flowchart can be elaborated as follows. Given an aerial photo, we first extract a number of graphlets to describe its topological structure. For each graphlet, we utilize color and texture to capture its appearance, and a weakly-supervised algorithm to capture its semantics. Thereafter, aerial photo categorization can be naturally formulated as graphlet-to-graphlet matching. As the number of graphlets from each aerial photo is huge, to accelerate matching, we present a hashing algorithm to seamlessly fuze the multiple visual features into binary codes. Finally, an image kernel is calculated by fast matching the binary codes corresponding to each graphlet. And a multi-class SVM is learned for aerial photo categorization. We demonstrate the advantage of our proposed model by comparing it with state-of-the-art image descriptors. Moreover, an in-depth study of the descriptiveness of the hash-based graphlet is presented.

  1. Assessing the accuracy and repeatability of automated photogrammetrically generated digital surface models from unmanned aerial system imagery

    NASA Astrophysics Data System (ADS)

    Chavis, Christopher

    Using commercial digital cameras in conjunction with Unmanned Aerial Systems (UAS) to generate 3-D Digital Surface Models (DSMs) and orthomosaics is emerging as a cost-effective alternative to Light Detection and Ranging (LiDAR). Powerful software applications such as Pix4D and APS can automate the generation of DSM and orthomosaic products from a handful of inputs. However, the accuracy of these models is relatively untested. The objectives of this study were to generate multiple DSM and orthomosaic pairs of the same area using Pix4D and APS from flights of imagery collected with a lightweight UAS. The accuracy of each individual DSM was assessed in addition to the consistency of the method to model one location over a period of time. Finally, this study determined if the DSMs automatically generated using lightweight UAS and commercial digital cameras could be used for detecting changes in elevation and at what scale. Accuracy was determined by comparing DSMs to a series of reference points collected with survey grade GPS. Other GPS points were also used as control points to georeference the products within Pix4D and APS. The effectiveness of the products for change detection was assessed through image differencing and observance of artificially induced, known elevation changes. The vertical accuracy with the optimal data and model is ≈ 25 cm and the highest consistency over repeat flights is a standard deviation of ≈ 5 cm. Elevation change detection based on such UAS imagery and DSM models should be viable for detecting infrastructure change in urban or suburban environments with little dense canopy vegetation.

  2. A Texture Thesaurus for Browsing Large Aerial Photographs.

    ERIC Educational Resources Information Center

    Ma, Wei-Ying; Manjunath, B. S.

    1998-01-01

    Presents a texture-based image-retrieval system for browsing large-scale aerial photographs. System components include texture-feature extraction, image segmentation and grouping, learning-similarity measure, and a texture-thesaurus model for fast search and indexing. Testing has demonstrated the system's effectiveness in searching and selecting…

  3. 3D city models completion by fusing lidar and image data

    NASA Astrophysics Data System (ADS)

    Grammatikopoulos, L.; Kalisperakis, I.; Petsa, E.; Stentoumis, C.

    2015-05-01

    A fundamental step in the generation of visually detailed 3D city models is the acquisition of high fidelity 3D data. Typical approaches employ DSM representations usually derived from Lidar (Light Detection and Ranging) airborne scanning or image based procedures. In this contribution, we focus on the fusion of data from both these methods in order to enhance or complete them. Particularly, we combine an existing Lidar and orthomosaic dataset (used as reference), with a new aerial image acquisition (including both vertical and oblique imagery) of higher resolution, which was carried out in the area of Kallithea, in Athens, Greece. In a preliminary step, a digital orthophoto and a DSM is generated from the aerial images in an arbitrary reference system, by employing a Structure from Motion and dense stereo matching framework. The image-to-Lidar registration is performed by 2D feature (SIFT and SURF) extraction and matching among the two orthophotos. The established point correspondences are assigned with 3D coordinates through interpolation on the reference Lidar surface, are then backprojected onto the aerial images, and finally matched with 2D image features located in the vicinity of the backprojected 3D points. Consequently, these points serve as Ground Control Points with appropriate weights for final orientation and calibration of the images through a bundle adjustment solution. By these means, the aerial imagery which is optimally aligned to the reference dataset can be used for the generation of an enhanced and more accurately textured 3D city model.

  4. Validating high-resolution California coastal flood modeling with Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR)

    NASA Astrophysics Data System (ADS)

    O'Neill, A.

    2015-12-01

    The Coastal Storm Modeling System (CoSMoS) is a numerical modeling scheme used to predict coastal flooding due to sea level rise and storms influenced by climate change, currently in use in central California and in development for Southern California (Pt. Conception to the Mexican border). Using a framework of circulation, wave, analytical, and Bayesian models at different geographic scales, high-resolution results are translated as relevant hazards projections at the local scale that include flooding, wave heights, coastal erosion, shoreline change, and cliff failures. Ready access to accurate, high-resolution coastal flooding data is critical for further validation and refinement of CoSMoS and improved coastal hazard projections. High-resolution Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) provides an exceptional data source as appropriately-timed flights during extreme tides or storms provide a geographically-extensive method for determining areas of inundation and flooding extent along expanses of complex and varying coastline. Landward flood extents are numerically identified via edge-detection in imagery from single flights, and can also be ascertained via change detection using additional flights and imagery collected during average wave/tide conditions. The extracted flooding positions are compared against CoSMoS results for similar tide, water level, and storm-intensity conditions, allowing for robust testing and validation of CoSMoS and providing essential feedback for supporting regional and local model improvement.

  5. Image Understanding Research and Its Application to Cartography and Computer-Based Analysis of Aerial Imagery

    DTIC Science & Technology

    1983-05-01

    manipulation routines, David Smith for the image access software, and David McKeown, assisted by Steve Clark, Joe Mattis , and Jerry Denlinger, for the...1980. [PietikainenB2] M. Pietikainen . A. Rosenfeld, and I. Walter, "Split-and-Link Algorithms for Image Seg- mentation," Pattern Recognition, Vol. 15

  6. Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images.

    PubMed

    Peña, José Manuel; Torres-Sánchez, Jorge; de Castro, Ana Isabel; Kelly, Maggi; López-Granados, Francisca

    2013-01-01

    The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r(2)=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (<5% weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance.

  7. Weed Mapping in Early-Season Maize Fields Using Object-Based Analysis of Unmanned Aerial Vehicle (UAV) Images

    PubMed Central

    Peña, José Manuel; Torres-Sánchez, Jorge; de Castro, Ana Isabel; Kelly, Maggi; López-Granados, Francisca

    2013-01-01

    The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r2=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (<5% weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance. PMID:24146963

  8. Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978–1987

    PubMed Central

    Korsgaard, Niels J.; Nuth, Christopher; Khan, Shfaqat A.; Kjeldsen, Kristian K.; Bjørk, Anders A.; Schomacker, Anders; Kjær, Kurt H.

    2016-01-01

    Digital Elevation Models (DEMs) play a prominent role in glaciological studies for the mass balance of glaciers and ice sheets. By providing a time snapshot of glacier geometry, DEMs are crucial for most glacier evolution modelling studies, but are also important for cryospheric modelling in general. We present a historical medium-resolution DEM and orthophotographs that consistently cover the entire surroundings and margins of the Greenland Ice Sheet 1978–1987. About 3,500 aerial photographs of Greenland are combined with field surveyed geodetic ground control to produce a 25 m gridded DEM and a 2 m black-and-white digital orthophotograph. Supporting data consist of a reliability mask and a photo footprint coverage with recording dates. Through one internal and two external validation tests, this DEM shows an accuracy better than 10 m horizontally and 6 m vertically while the precision is better than 4 m. This dataset proved successful for topographical mapping and geodetic mass balance. Other uses include control and calibration of remotely sensed data such as imagery or InSAR velocity maps. PMID:27164457

  9. Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978-1987.

    PubMed

    Korsgaard, Niels J; Nuth, Christopher; Khan, Shfaqat A; Kjeldsen, Kristian K; Bjørk, Anders A; Schomacker, Anders; Kjær, Kurt H

    2016-05-10

    Digital Elevation Models (DEMs) play a prominent role in glaciological studies for the mass balance of glaciers and ice sheets. By providing a time snapshot of glacier geometry, DEMs are crucial for most glacier evolution modelling studies, but are also important for cryospheric modelling in general. We present a historical medium-resolution DEM and orthophotographs that consistently cover the entire surroundings and margins of the Greenland Ice Sheet 1978-1987. About 3,500 aerial photographs of Greenland are combined with field surveyed geodetic ground control to produce a 25 m gridded DEM and a 2 m black-and-white digital orthophotograph. Supporting data consist of a reliability mask and a photo footprint coverage with recording dates. Through one internal and two external validation tests, this DEM shows an accuracy better than 10 m horizontally and 6 m vertically while the precision is better than 4 m. This dataset proved successful for topographical mapping and geodetic mass balance. Other uses include control and calibration of remotely sensed data such as imagery or InSAR velocity maps.

  10. Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978-1987

    NASA Astrophysics Data System (ADS)

    Korsgaard, Niels J.; Nuth, Christopher; Khan, Shfaqat A.; Kjeldsen, Kristian K.; Bjørk, Anders A.; Schomacker, Anders; Kjær, Kurt H.

    2016-05-01

    Digital Elevation Models (DEMs) play a prominent role in glaciological studies for the mass balance of glaciers and ice sheets. By providing a time snapshot of glacier geometry, DEMs are crucial for most glacier evolution modelling studies, but are also important for cryospheric modelling in general. We present a historical medium-resolution DEM and orthophotographs that consistently cover the entire surroundings and margins of the Greenland Ice Sheet 1978-1987. About 3,500 aerial photographs of Greenland are combined with field surveyed geodetic ground control to produce a 25 m gridded DEM and a 2 m black-and-white digital orthophotograph. Supporting data consist of a reliability mask and a photo footprint coverage with recording dates. Through one internal and two external validation tests, this DEM shows an accuracy better than 10 m horizontally and 6 m vertically while the precision is better than 4 m. This dataset proved successful for topographical mapping and geodetic mass balance. Other uses include control and calibration of remotely sensed data such as imagery or InSAR velocity maps.

  11. Pantir - a Dual Camera Setup for Precise Georeferencing and Mosaicing of Thermal Aerial Images

    NASA Astrophysics Data System (ADS)

    Weber, I.; Jenal, A.; Kneer, C.; Bongartz, J.

    2015-03-01

    Research and monitoring in fields like hydrology and agriculture are applications of airborne thermal infrared (TIR) cameras, which suffer from low spatial resolution and low quality lenses. Common ground control points (GCPs), lacking thermal activity and being relatively small in size, cannot be used in TIR images. Precise georeferencing and mosaicing however is necessary for data analysis. Adding a high resolution visible light camera (VIS) with a high quality lens very close to the TIR camera, in the same stabilized rig, allows us to do accurate geoprocessing with standard GCPs after fusing both images (VIS+TIR) using standard image registration methods.

  12. An Automated Approach to Extracting River Bank Locations from Aerial Imagery Using Image Texture

    DTIC Science & Technology

    2015-11-04

    being analyzed, rl is the local range of values across the pixels and rm is the maximum possible range of values. Algorithm Imagery must first be...River, LA The case presented in Figures 1 and 6 represents an ideal case for demonstrating the algorithm in that the surface of the water appears uniform...x 1400 pixel image. A human operator loaded the image in the open source Quantum GIS programme and traced the edges to create a ESRI shape file, which

  13. Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar

    PubMed Central

    Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin

    2017-01-01

    Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R2 = 0.340, root-mean-square error (RMSE) = 81.89 g·m−2, and relative error of 14.1%). The improvement of multiple regressions to the R2 and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns. PMID:28106819

  14. Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar.

    PubMed

    Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin

    2017-01-19

    Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R² = 0.340, root-mean-square error (RMSE) = 81.89 g·m(-2), and relative error of 14.1%). The improvement of multiple regressions to the R² and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns.

  15. Evaluation of unmanned aerial vehicle (UAV) imagery to model vegetation heights in Hulun Buir grassland ecosystem

    NASA Astrophysics Data System (ADS)

    Wang, D.; Xin, X.; Li, Z.

    2015-12-01

    Vertical vegetation structure in grassland ecosystem is needed to assess grassland health and monitor available forage for livestock and wildlife habitat. Traditional ground-based field methods for measuring vegetation heights are time consuming. Most emerging airborne remote sensing techniques capable of measuring surface and vegetation height (e.g., LIDAR) are too expensive to apply at broad scales. Aerial or spaceborne stereo imagery has the cost advantage for mapping height of tall vegetation, such as forest. However, the accuracy and uncertainty of using stereo imagery for modeling heights of short vegetation, such as grass (generally lower than 50cm) needs to be investigated. In this study, 2.5-cm resolution UAV stereo imagery are used to model vegetation heights in Hulun Buir grassland ecosystem. Strong correlations were observed (r > 0.9) between vegetation heights derived from UAV stereo imagery and those field-measured ones at individual and plot level. However, vegetation heights tended to be underestimated in the imagery especially for those areas with high vegetation coverage. The strong correlations between field-collected vegetation heights and metrics derived from UAV stereo imagery suggest that UAV stereo imagery can be used to estimate short vegetation heights such as those in grassland ecosystem. Future work will be needed to verify the extensibility of the methods to other sites and vegetation types.

  16. Knowledge Based 3d Building Model Recognition Using Convolutional Neural Networks from LIDAR and Aerial Imageries

    NASA Astrophysics Data System (ADS)

    Alidoost, F.; Arefi, H.

    2016-06-01

    In recent years, with the development of the high resolution data acquisition technologies, many different approaches and algorithms have been presented to extract the accurate and timely updated 3D models of buildings as a key element of city structures for numerous applications in urban mapping. In this paper, a novel and model-based approach is proposed for automatic recognition of buildings' roof models such as flat, gable, hip, and pyramid hip roof models based on deep structures for hierarchical learning of features that are extracted from both LiDAR and aerial ortho-photos. The main steps of this approach include building segmentation, feature extraction and learning, and finally building roof labeling in a supervised pre-trained Convolutional Neural Network (CNN) framework to have an automatic recognition system for various types of buildings over an urban area. In this framework, the height information provides invariant geometric features for convolutional neural network to localize the boundary of each individual roofs. CNN is a kind of feed-forward neural network with the multilayer perceptron concept which consists of a number of convolutional and subsampling layers in an adaptable structure and it is widely used in pattern recognition and object detection application. Since the training dataset is a small library of labeled models for different shapes of roofs, the computation time of learning can be decreased significantly using the pre-trained models. The experimental results highlight the effectiveness of the deep learning approach to detect and extract the pattern of buildings' roofs automatically considering the complementary nature of height and RGB information.

  17. Mobile Aerial Tracking and Imaging System (MATrIS) for Aeronautical Research

    NASA Technical Reports Server (NTRS)

    Banks, Daniel W.; Blanchard, Robert C.; Miller, Geoffrey M.

    2004-01-01

    A mobile, rapidly deployable ground-based system to track and image targets of aeronautical interest has been developed. Targets include reentering reusable launch vehicles as well as atmospheric and transatmospheric vehicles. The optics were designed to image targets in the visible and infrared wavelengths. To minimize acquisition cost and development time, the system uses commercially available hardware and software where possible. The conception and initial funding of this system originated with a study of ground-based imaging of global aerothermal characteristics of reusable launch vehicle configurations. During that study the National Aeronautics and Space Administration teamed with the Missile Defense Agency/Innovative Science and Technology Experimentation Facility to test techniques and analysis on two Space Shuttle flights.

  18. Infrared Surveys of Hawaiian Volcanoes: Aerial surveys with infrared imaging radiometer depict volcanic thermal patterns and structural features.

    PubMed

    Fisher, W A; Moxham, R M; Polcyn, F; Landis, G H

    1964-11-06

    Aerial infrared-sensor surveys of Kilauea volcano have depicted the areal extent and the relative intensity of abnormal thermal features in the caldera area of the volcano and along its associated rift zones. Many of these anomalies show correlation with visible steaming and reflect convective transfer of heat to the surface from subterranean sources. Structural details of the volcano, some not evident from surface observation, are also delineated by their thermal abnormalities. Several changes were observed in the patterns of infrared emission during the period of study; two such changes show correlation in location with subsequent eruptions, but the cause-and-effect relationship is uncertain. Thermal anomalies were also observed on the southwest flank of Mauna Loa; images of other volcanoes on the island of Hawaii, and of Haleakala on the island of Maui, revealed no thermal abnormalities. Approximately 25 large springs issuing into the ocean around the periphery of Hawaii have been detected. Infrared emission varies widely with surface texture and composition, suggesting that similar observations may have value for estimating surface conditions on the moon or planets.

  19. Development of test methods for scale model simulation of aerial applications in the NASA Langley Vortex Research Facility. [agricultural aircraft

    NASA Technical Reports Server (NTRS)

    Jordan, F. L., Jr.

    1980-01-01

    As part of basic research to improve aerial applications technology, methods were developed at the Langley Vortex Research Facility to simulate and measure deposition patterns of aerially-applied sprays and granular materials by means of tests with small-scale models of agricultural aircraft and dynamically-scaled test particles. Interactions between the aircraft wake and the dispersed particles are being studied with the objective of modifying wake characteristics and dispersal techniques to increase swath width, improve deposition pattern uniformity, and minimize drift. The particle scaling analysis, test methods for particle dispersal from the model aircraft, visualization of particle trajectories, and measurement and computer analysis of test deposition patterns are described. An experimental validation of the scaling analysis and test results that indicate improved control of chemical drift by use of winglets are presented to demonstrate test methods.

  20. Analyzing the evolution of the Tessina landslide using aerial photographs and digital elevation models

    NASA Astrophysics Data System (ADS)

    van Westen, C. J.; Lulie Getahun, F.

    2003-08-01

    Evolution of the Tessina landslide near Belluno, Italy, from 1954 to the present situation has been documented using multitemporal landslide maps. The maps were produced through the interpretation of sequential aerial photographs and direct field-mapping of the landslide in 1998 and 1999. The interpretations were converted to large-scale multitemporal topographical maps and digitized, resulting in detailed geomorphological maps of the Tessina landslide for the following periods: 1954, 1961, 1969, 1980, 1991, 1993, 1998 and 1999. A quantitative volumetric analysis was also carried out using a series of digital elevation models derived from the available 1:5000 scale digital contour maps with 5-m contour interval for 1948, 1964, 1980, 1991 and 1993. The total volume of material removed and accumulated was calculated for the entire Tessina landslide for the different time steps available. Results indicate that the Tessina landslide existed prior to its main reactivation in 1960, after which the landslide reduced in activity. From 1991, however, very large reactivations have taken place, and the landslide continues to be active. Although the landslide has reached the lateral boundaries of the old pre-1960 landslide, it is now expanding upslope where it may still mobilize large amounts of material.

  1. Effects of light pollution revealed during a nocturnal aerial survey by two hyperspectral imagers

    NASA Astrophysics Data System (ADS)

    Barducci, Alessandro; Marcoionni, Paolo; Pippi, Ivan; Poggesi, Marco

    2003-07-01

    A remote-sensing campaign was performed in September 2001 at nighttime under clear-sky conditions before moonrise to assess the level of light pollution of urban and industrial origin. Two hyperspectral sensors, namely, the Multispectral Infrared and Visible Imaging Spectrometer and the Visible Infrared Scanner-200, which provide spectral coverage from the visible to the thermal infrared, were flown over the Tuscany coast (Italy) on board a Casa 212 airplane. The acquired images were processed to produce radiometrically calibrated data, which were then analyzed and compared with ground-based spectral measurements. Calibrated data acquired at high spectral resolution (~2.5 nm) showed a maximum scene brightness almost of the same order of magnitude as that observed during similar daytime measurements, whereas their average luminosity was 3 orders of magnitude lower. The measurement analysis confirmed that artificial illumination hinders astronomical observations and produces noticeable effects even at great distances from the sources of the illumination.

  2. Effects of light pollution revealed during a nocturnal aerial survey by two hyperspectral imagers.

    PubMed

    Barducci, Alessandro; Marcoionni, Paolo; Pippi, Ivan; Poggesi, Marco

    2003-07-20

    A remote-sensing campaign was performed in September 2001 at nighttime under clear-sky conditions before moonrise to assess the level of light pollution of urban and industrial origin. Two hyperspectral sensors, namely, the Multispectral Infrared and Visible Imaging Spectrometer and the Visible Infrared Scanner-200, which provide spectral coverage from the visible to the thermal infrared, were flown over the Tuscany coast (Italy) on board a Casa 212 airplane. The acquired images were processed to produce radiometrically calibrated data, which were then analyzed and compared with ground-based spectral measurements. Calibrated data acquired at high spectral resolution (approximately 2.5 nm) showed a maximum scene brightness almost of the same order of magnitude as that observed during similar daytime measurements, whereas their average luminosity was 3 orders of magnitude lower. The measurement analysis confirmed that artificial illumination hinders astronomical observations and produces noticeable effects even at great distances from the sources of the illumination.

  3. Spatial Feature Evaluation for Aerial Scene Analysis

    SciTech Connect

    Swearingen, Thomas S; Cheriyadat, Anil M

    2013-01-01

    High-resolution aerial images are becoming more readily available, which drives the demand for robust, intelligent and efficient systems to process increasingly large amounts of image data. However, automated image interpretation still remains a challenging problem. Robust techniques to extract and represent features to uniquely characterize various aerial scene categories is key for automated image analysis. In this paper we examined the role of spatial features to uniquely characterize various aerial scene categories. We studied low-level features such as colors, edge orientations, and textures, and examined their local spatial arrangements. We computed correlograms representing the spatial correlation of features at various distances, then measured the distance between correlograms to identify similar scenes. We evaluated the proposed technique on several aerial image databases containing challenging aerial scene categories. We report detailed evaluation of various low-level features by quantitatively measuring accuracy and parameter sensitivity. To demonstrate the feature performance, we present a simple query-based aerial scene retrieval system.

  4. Deposition of aerially applied BT in an oak forest and its prediction with the FSCBG model

    USGS Publications Warehouse

    Anderson, Dean E.; Miller, David R.; Wang, Yansen; Yendol, William G.; Mierzejewski, Karl; McManus, Michael L.

    1992-01-01

    Data are provided from 17 single-swath aerial spray trials that were conducted over a fully leafed, 16-m tall, mixed oak forest. The distribution of cross-swath spray deposits was sampled at the top of the canopy and below the canopy. Micrometeorological conditions were measured above and within the canopy during the spray trials. The USDA Forest Service FSCBG (Forest Service-Cramer-Barry-Grim) model was run to predict the target sampler catch for each trial using forest stand, airplane-application-equipment configuration, and micrometeorological conditions as inputs. Observations showed an average cross-swath deposition of 100 IU cm−2 with large run-to-run variability in deposition patterns, magnitudes, and drift. Eleven percent of the spray material that reached the top of the canopy penetrated through the tree canopy to the forest floor.The FSCBG predictions of the ensemble-averaged deposition were within 17% of the measured deposition at the canopy top and within 8% on the ground beneath the canopy. Run-to-run deposit predictions by FSCBG were considerably less variable than the measured deposits. Individual run predictions were much less accurate than the ensemble-averaged predictions as demonstrated by an average root-mean-square-error (rmse) of 27.9 IU CM−2 at the top of the canopy. Comparisons of the differences between predicted and observed deposits indicated that the model accuracy was sensitive to atmospheric stability conditions. In neutral and stable conditions, a regular pattern of error was indicated by overprediction of the canopy-top deposit at distances from 0 to 20 m downwind from the flight line and underprediction of the deposit both farther downwind than 20 m and upwind of the flight line. In unstable conditions the model generally underpredicted the deposit downwind from the flight line, but showed no regular pattern of error.

  5. Data fusion of aerial and terrestrial LiDAR datasets for sediment transport modelling

    NASA Astrophysics Data System (ADS)

    De Luca, Alberto; Cucchiaro, Sara; Blasone, Giacomo; Cavalli, Marco; Cazorzi, Federico

    2015-04-01

    Availability of high-resolution morphometric survey datasets is not an issue any longer, especially after the wide adoption of laser scanning technology to collect data. Nevertheless, this abundance of data is not always matched by the techniques and the procedures used to process it and to turn it into information useful for decision makers. The work we present here was aimed at exploiting high-resolution morphometric data collected using two different technologies, i.e. Aerial Laser Scanner (ALS) and Terrestrial Laser Scanner (TLS). The two datasets were combined to generate a series of Digital Elevation Models (DTMs) that were in turn used to assess the effects of the construction of a new check dam on sediment transport modelling in a small Italian mountain catchment (Rio Moscardo). The fusion of the two datasets allowed the generation of three DTMs. The first DTM (scenario 1, from ALS data only) describes the morphology before the check dam construction. The second DTM (scenario 2, from ALS and TLS data) describes the morphology right after the check dam construction, therefore without upstream debris deposition. The third DTM (scenario 3, from ALS and TLS, modified) describes the morphology a few years after the dam construction, with consistent upstream debris deposition. The three DTMs were used as a basis for the calculation of a spatial sediment Connectivity Index (IC), to assess how different portions of the catchment are connected to the catchment outlet (target) in terms of debris flow delivery. The modelling results clearly show that in scenario 2 the check dam acts as an effective sink for the debris, almost disconnecting the catchment portion upstream to the dam (15% of the catchment area) from the catchment outlet. In scenario 3, where due to debris deposition the slope of the area just upslope to the dam has strongly decreased, the IC values of the catchment portion upstream to the dam revert to the ones shown in scenario 1, where strong

  6. A new technique for the detection of large scale landslides in glacio-lacustrine deposits using image correlation based upon aerial imagery: A case study from the French Alps

    NASA Astrophysics Data System (ADS)

    Fernandez, Paz; Whitworth, Malcolm

    2016-10-01

    Landslide monitoring has benefited from recent advances in the use of image correlation of high resolution optical imagery. However, this approach has typically involved satellite imagery that may not be available for all landslides depending on their time of movement and location. This study has investigated the application of image correlation techniques applied to a sequence of aerial imagery to an active landslide in the French Alps. We apply an indirect landslide monitoring technique (COSI-Corr) based upon the cross-correlation between aerial photographs, to obtain horizontal displacement rates. Results for the 2001-2003 time interval are presented, providing a spatial model of landslide activity and motion across the landslide, which is consistent with previous studies. The study has identified areas of new landslide activity in addition to known areas and through image decorrelation has identified and mapped two new lateral landslides within the main landslide complex. This new approach for landslide monitoring is likely to be of wide applicability to other areas characterised by complex ground displacements.

  7. Integration of historical aerial and satellite photos, recent satellite images and geophysical surveys for the knowledge of the ancient Dyrrachium (Durres, Albania)

    NASA Astrophysics Data System (ADS)

    Malfitana, Daniele; Shehi, Eduard; Masini, Nicola; Scardozzi, Giuseppe

    2010-05-01

    The paper presents the preliminary results of an integrated multidiscipliary research project concerning the urban area of the modern Durres (ancient Dyrrachium). Here a joint Italian and Albanian researcher are starting preliminary investigations on the place of an ancient roman villa placed in the urban centre of the modern town. In a initial phase are offering interesting results the use of a rich multitemporal remote sensing data-set, historical aerial photos of 1920s and 1930s, photos of USA spy satellites of 1960s and 1970s (Corona KH-4A and KH-4B), and very high resolution satellite imagery. The historical aerial documentation is very rich and includes aerial photogrammetrich flights of two Italian Institutions: the private company SARA - Società Anonima Rilevamenti Aerofotogrammetrici in Rome (1928) and the IGM - Istituto Geografico Militare (1936, 1937 e 1941), which flew on Durres for purposes of cartographic production and military. These photos offer an image of the city before the urban expansion after the Second World War and in recent decades, progressively documented by satellite images of the 1960s-1970s and recent years. They enable a reconstruction of the ancient topography of the urban area, even with the possibility of detailed analysis, as in the case of the the Roman villa, nowadays buried under a modern garden, but also investigated with a GPR survey, in order to rebuild its plan and contextualize the villa in relation to the urban area of the ancient Dyrrachium.

  8. Unsupervised Change Detection in SAR Images Using Gaussian Mixture Models

    NASA Astrophysics Data System (ADS)

    Kiana, E.; Homayouni, S.; Sharifi, M. A.; Farid-Rohani, M.

    2015-12-01

    In this paper, we propose a method for unsupervised change detection in Remote Sensing Synthetic Aperture Radar (SAR) images. This method is based on the mixture modelling of the histogram of difference image. In this process, the difference image is classified into three classes; negative change class, positive change class and no change class. However the SAR images suffer from speckle noise, the proposed method is able to map the changes without speckle filtering. To evaluate the performance of this method, two dates of SAR data acquired by Uninhabited Aerial Vehicle Synthetic from an agriculture area are used. Change detection results show better efficiency when compared to the state-of-the-art methods.

  9. Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models

    NASA Astrophysics Data System (ADS)

    Abayowa, Bernard O.; Yilmaz, Alper; Hardie, Russell C.

    2015-08-01

    This paper presents a framework for automatic registration of both the optical and 3D structural information extracted from oblique aerial imagery to a Light Detection and Ranging (LiDAR) point cloud without prior knowledge of an initial alignment. The framework employs a coarse to fine strategy in the estimation of the registration parameters. First, a dense 3D point cloud and the associated relative camera parameters are extracted from the optical aerial imagery using a state-of-the-art 3D reconstruction algorithm. Next, a digital surface model (DSM) is generated from both the LiDAR and the optical imagery-derived point clouds. Coarse registration parameters are then computed from salient features extracted from the LiDAR and optical imagery-derived DSMs. The registration parameters are further refined using the iterative closest point (ICP) algorithm to minimize global error between the registered point clouds. The novelty of the proposed approach is in the computation of salient features from the DSMs, and the selection of matching salient features using geometric invariants coupled with Normalized Cross Correlation (NCC) match validation. The feature extraction and matching process enables the automatic estimation of the coarse registration parameters required for initializing the fine registration process. The registration framework is tested on a simulated scene and aerial datasets acquired in real urban environments. Results demonstrates the robustness of the framework for registering optical and 3D structural information extracted from aerial imagery to a LiDAR point cloud, when co-existing initial registration parameters are unavailable.

  10. Wind-tunnel tests and modeling indicate that aerial dispersant delivery operations are highly accurate

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The United States Department of Agriculture’s high-speed wind tunnel facility in College Station, Texas, USA was used to determine droplet size distributions generated by dispersant delivery nozzles at wind speeds comparable to those used in aerial dispersant application. A laser particle size anal...

  11. A practical interpretation and use of the USDA aerial fixed-wing nozzle models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Proper selection and operation of spray nozzles associated with aerial applications is critical to insuring efficacy while mitigating off-target movement. Labels for most agrochemical products applied in the U.S. specifically define the droplet size or spray classification that can be used to apply...

  12. CATV Aerial Construction Course. Model Vocational Education Project for Special Needs Incarcerated Youth.

    ERIC Educational Resources Information Center

    Elgin Community Coll., IL.

    This curriculum guide provides materials for a course to enable a student to meet the entry-level requirements of the cable industry as an aerial construction crew member. It is appropriate for a juvenile correctional facility, high school, or junior college. The course is intended to be completed in a minimum of 150 hours, including time in both…

  13. A fast and mobile system for registration of low-altitude visual and thermal aerial images using multiple small-scale UAVs

    NASA Astrophysics Data System (ADS)

    Yahyanejad, Saeed; Rinner, Bernhard

    2015-06-01

    The use of multiple small-scale UAVs to support first responders in disaster management has become popular because of their speed and low deployment costs. We exploit such UAVs to perform real-time monitoring of target areas by fusing individual images captured from heterogeneous aerial sensors. Many approaches have already been presented to register images from homogeneous sensors. These methods have demonstrated robustness against scale, rotation and illumination variations and can also cope with limited overlap among individual images. In this paper we focus on thermal and visual image registration and propose different methods to improve the quality of interspectral registration for the purpose of real-time monitoring and mobile mapping. Images captured by low-altitude UAVs represent a very challenging scenario for interspectral registration due to the strong variations in overlap, scale, rotation, point of view and structure of such scenes. Furthermore, these small-scale UAVs have limited processing and communication power. The contributions of this paper include (i) the introduction of a feature descriptor for robustly identifying corresponding regions of images in different spectrums, (ii) the registration of image mosaics, and (iii) the registration of depth maps. We evaluated the first method using a test data set consisting of 84 image pairs. In all instances our approach combined with SIFT or SURF feature-based registration was superior to the standard versions. Although we focus mainly on aerial imagery, our evaluation shows that the presented approach would also be beneficial in other scenarios such as surveillance and human detection. Furthermore, we demonstrated the advantages of the other two methods in case of multiple image pairs.

  14. Aerial Photography

    NASA Technical Reports Server (NTRS)

    1985-01-01

    John Hill, a pilot and commercial aerial photographer, needed an information base. He consulted NERAC and requested a search of the latest developments in camera optics. NERAC provided information; Hill contacted the manufacturers of camera equipment and reduced his photographic costs significantly.

  15. Ultrasound Imaging and Its Modeling

    NASA Astrophysics Data System (ADS)

    Jensen, Jorgen A.

    Modern medical ultrasound scanners are used to image nearly all soft tissue structures in the body. The anatomy can be studied from gray-scale B-mode images, where the reflectivity and scattering strength of the tissues are displayed. The imaging is performed in real time with 20 to 100 images per second. The technique is widely used, since it does not use ionizing radiation and is safe and painless for the patient. This chapter gives a short introduction to modern ultrasound imaging using array transducers. It includes a description of the different imaging methods, the beam-forming strategies used, and the resulting fields and their modeling.

  16. Assessing the quality of Digital Elevation Models obtained from mini-Unmanned Aerial Vehicles for overland flow modelling in urban areas

    NASA Astrophysics Data System (ADS)

    Leitão, J. P.; Moy de Vitry, M.; Scheidegger, A.; Rieckermann, J.

    2015-06-01

    Precise and detailed Digital Elevation Models (DEMs) are essential to accurately predict overland flow in urban areas. Unfortunately, traditional sources of DEM remain a bottleneck for detailed and reliable overland flow models, because the resulting DEMs are too coarse to provide DEMs of sufficient detail to inform urban overland flows. Interestingly, technological developments of Unmanned Aerial Vehicles (UAVs) suggest that they have matured enough to be a competitive alternative to satellites or airplanes. However, this has not been tested so far. In this this study we therefore evaluated whether DEMs generated from UAV imagery are suitable for urban drainage overland flow modelling. Specifically, fourteen UAV flights were conducted to assess the influence of four different flight parameters on the quality of generated DEMs: (i) flight altitude, (ii) image overlapping, (iii) camera pitch and (iv) weather conditions. In addition, we compared the best quality UAV DEM to a conventional Light Detection and Ranging (LiDAR)-based DEM. To evaluate both the quality of the UAV DEMs and the comparison to LiDAR-based DEMs, we performed regression analysis on several qualitative and quantitative metrics, such as elevation accuracy, quality of object representation (e.g., buildings, walls and trees) in the DEM, which were specifically tailored to assess overland flow modelling performance, using the flight parameters as explanatory variables. Our results suggested that, first, as expected, flight altitude influenced the DEM quality most, where lower flights produce better DEMs; in a similar fashion, overcast weather conditions are preferable, but weather conditions and other factors influence DEM quality much less. Second, we found that for urban overland flow modelling, the UAV DEMs performed competitively in comparison to a traditional LiDAR-based DEM. An important advantage of using UAVs to generate DEMs in urban areas is their flexibility that enables more frequent

  17. Tidal Flooding and Vegetation Patterns in a Salt Marsh Tidal Creek Imaged by Low-altitude Balloon Aerial Photography

    NASA Astrophysics Data System (ADS)

    White, S. M.; Madsen, E.

    2013-12-01

    soil water content. These other factors are all directly affected by the hydroperiod, creating a complex system of feedbacks. Inundation frequencies show a pronounced relationship to zonation. Creek bank height and the hydroperiod have a curvilinear relationship at low bank heights such that small decreases in creek bank height can result in large increases in inundation frequency. Biological zonation is not simply a result of bank height and inundation frequency, other contributing factors include species competition, adaptability, and groundwater flow. Vegetation patterns delineated by a ground-based GPS survey and image classification from the aerial photos show that not all changes in eco-zonation are a direct function of elevation. Some asymmetry across the creek is observed in plant habitat, and eliminating topography (and thereby tidal inundation) as a factor, we attribute the remaining variability to groundwater flow.

  18. Mass and heat flux balance of La Soufrière volcano (Guadeloupe) from aerial infrared thermal imaging

    NASA Astrophysics Data System (ADS)

    Gaudin, Damien; Beauducel, François; Coutant, Olivier; Delacourt, Christophe; Richon, Patrick; de Chabalier, Jean-Bernard; Hammouya, Gilbert

    2016-06-01

    La Soufrière of Guadeloupe is an active volcano of Lesser Antilles that is closely monitored due to a high eruptive hazard potential. Since 1992 it exhibits a medium-level but sustained background hydrothermal activity with low-energy and shallow seismicity, hot springs temperature increase and high flux acidic gas fumaroles at the summit. The problem of estimating the heat balance and quantifying the evolution of hydrothermal activity has become a key challenge for surveillance. This work is the first attempt of a global mapping and quantification of La Soufrière thermal activity performed in February 2010 using aerial thermal infrared imagery. After instrument calibration and data processing, we present a global map of thermal anomalies allowing to spot the main active sites: the summit area (including the fumaroles of Tarissan Pit and South Crater), the Ty Fault fumarolic zone, and the hot springs located at the vicinity of the dome. In a second step, we deduce the mass and the energy fluxes released by the volcano. In particular, we propose a simple model of energy balance to estimate the mass flux of the summit fumaroles from their brightness temperature and size. In February 2010, Tarissan Pit had a 22.8 ± 8.1 kg s -1 flux (1970 ± 704 tons day -1), while South Crater vents had a total of 19.5 ± 4.0 kg s -1 (1687 ± 348 tons day -1). Once converted into energy flux, summit fumaroles represent 98% of the 106 ± 30 MW released by the volcano, the 2% remaining being split between the hot springs and the thermal anomalies at the summit and at the Ty Fault fumarolic zone. These values are in the high range of the previous estimations, highlighting the short-term variability of the expelled fluxes. Such a heat flux requires the cooling of 1500 m 3 of magma per day, in good agreement with previous geochemical studies.

  19. Flapping Wings of an Inclined Stroke Angle: Experiments and Reduced-Order Models in Dual Aerial/Aquatic Flight

    NASA Astrophysics Data System (ADS)

    Izraelevitz, Jacob; Triantafyllou, Michael

    2016-11-01

    Flapping wings in nature demonstrate a large force actuation envelope, with capabilities beyond the limits of static airfoil section coefficients. Puffins, guillemots, and other auks particularly showcase this mechanism, as they are able to both generate both enough thrust to swim and lift to fly, using the same wing, by changing the wing motion trajectory. The wing trajectory is therefore an additional design criterion to be optimized along with traditional aircraft parameters, and could possibly enable dual aerial/aquatic flight. We showcase finite aspect-ratio flapping wing experiments, dynamic similarity arguments, and reduced-order models for predicting the performance of flapping wings that carry out complex motion trajectories.

  20. Thermal Imaging Using Small-Aerial Platforms for Assessment of Crop Water Stress in Humid Subtropical Climates

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Leaf- or canopy-to-air temperature difference (hereafter called CATD) can provide information on crop energy status. Thermal imagery from agricultural aircraft or Unmanned Aerial Vehicles (UAVs) have the potential of providing thermal data for calculation of CATD and visual snapshots that can guide ...

  1. Development of an object-based classification model for mapping mountainous forest cover at high elevation using aerial photography

    NASA Astrophysics Data System (ADS)

    Lateb, Mustapha; Kalaitzidis, Chariton; Tompoulidou, Maria; Gitas, Ioannis

    2016-08-01

    Climate change and overall temperature increase results in changes in forest cover in high elevations. Due to the long life cycle of trees, these changes are very gradual and can be observed over long periods of time. In order to use remote sensing imagery for this purpose it needs to have very high spatial resolution and to have been acquired at least 50 years ago. At the moment, the only type of remote sensing imagery with these characteristics is historical black and white aerial photographs. This study used an aerial photograph from 1945 in order to map the forest cover at the Olympus National Park, at that date. An object-based classification (OBC) model was developed in order to classify forest and discriminate it from other types of vegetation. Due to the lack of near-infrared information, the model had to rely solely on the tone of the objects, as well as their geometric characteristics. The model functioned on three segmentation levels, using sub-/super-objects relationships and utilising vegetation density to discriminate forest and non-forest vegetation. The accuracy of the classification was assessed using 503 visually interpreted and randomly distributed points, resulting in a 92% overall accuracy. The model is using unbiased parameters that are important for differentiating between forest and non-forest vegetation and should be transferrable to other study areas of mountainous forests at high elevations.

  2. Parameter optimization of image classification techniques to delineate crowns of coppice trees on UltraCam-D aerial imagery in woodlands

    NASA Astrophysics Data System (ADS)

    Erfanifard, Yousef; Stereńczak, Krzysztof; Behnia, Negin

    2014-01-01

    Estimating the optimal parameters of some classification techniques becomes their negative aspect as it affects their performance for a given dataset and reduces classification accuracy. It was aimed to optimize the combination of effective parameters of support vector machine (SVM), artificial neural network (ANN), and object-based image analysis (OBIA) classification techniques by the Taguchi method. The optimized techniques were applied to delineate crowns of Persian oak coppice trees on UltraCam-D very high spatial resolution aerial imagery in Zagros semiarid woodlands, Iran. The imagery was classified and the maps were assessed by receiver operating characteristic curve and other performance metrics. The results showed that Taguchi is a robust approach to optimize the combination of effective parameters in these image classification techniques. The area under curve (AUC) showed that the optimized OBIA could well discriminate tree crowns on the imagery (AUC=0.897), while SVM and ANN yielded slightly less AUC performances of 0.819 and 0.850, respectively. The indices of accuracy (0.999) and precision (0.999) and performance metrics of specificity (0.999) and sensitivity (0.999) in the optimized OBIA were higher than with other techniques. The optimization of effective parameters of image classification techniques by the Taguchi method, thus, provided encouraging results to discriminate the crowns of Persian oak coppice trees on UltraCam-D aerial imagery in Zagros semiarid woodlands.

  3. Multifunctional aerial display through use of polarization-processing display

    NASA Astrophysics Data System (ADS)

    Uchida, Keitaro; Ito, Shusei; Yamamoto, Hirotsugu

    2017-02-01

    We have realized a multifunctional aerial display. An aerial image of a polarization-processing display is formed through aerial imaging by retro-reflection. By changing the polarization modulation patterns, we can switch between a three-layered display and a secure display.

  4. Hyperspatial Thermal Imaging of Surface Hydrothermal Features at Pilgrim Hot Springs, Alaska using a small Unmanned Aerial System (sUAS)

    NASA Astrophysics Data System (ADS)

    Haselwimmer, C. E.; Wilson, R.; Upton, C.; Prakash, A.; Holdmann, G.; Walker, G.

    2013-12-01

    Thermal remote sensing provides a valuable tool for mapping and monitoring surface hydrothermal features associated with geothermal activity. The increasing availability of low-cost, small Unmanned Aerial Systems (sUAS) with integrated thermal imaging sensors offers a means to undertake very high spatial resolution (hyperspatial), quantitative thermal remote sensing of surface geothermal features in support of exploration and long-term monitoring efforts. Results from the deployment of a quadcopter sUAS equipped with a thermal camera over Pilgrim Hot Springs, Alaska for detailed mapping and heat flux estimation for hot springs, seeps, and thermal pools are presented. Hyperspatial thermal infrared imagery (4 cm pixels) was acquired over Pilgrim Hot Springs in July 2013 using a FLIR TAU 640 camera operating from an Aeryon Scout sUAS flying at an altitude of 40m. The registered and mosaicked thermal imagery is calibrated to surface temperature values using in-situ measurements of uniform blackbody tarps and the temperatures of geothermal and other surface pools acquired with a series of water temperature loggers. Interpretation of the pre-processed thermal imagery enables the delineation of hot springs, the extents of thermal pools, and the flow and mixing of individual geothermal outflow plumes with an unprecedented level of detail. Using the surface temperatures of thermal waters derived from the FLIR data and measured in-situ meteorological parameters the hot spring heat flux and outflow rate is calculated using a heat budget model for a subset of the thermal drainage. The heat flux/outflow rate estimates derived from the FLIR data are compared against in-situ measurements of the hot spring outflow rate recorded at the time of the thermal survey.

  5. Modeling and Inverse Controller Design for an Unmanned Aerial Vehicle Based on the Self-Organizing Map

    NASA Technical Reports Server (NTRS)

    Cho, Jeongho; Principe, Jose C.; Erdogmus, Deniz; Motter, Mark A.

    2005-01-01

    The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a SOM-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.

  6. Modeling and inverse controller design for an unmanned aerial vehicle based on the self-organizing map.

    PubMed

    Cho, Jeongho; Principe, Jose C; Erdogmus, Deniz; Motter, Mark A

    2006-03-01

    The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a self-organizing map (SOM)-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.

  7. Terrestrial and Aerial Laser Scanning Data Integration Using Wavelet Analysis for the Purpose of 3D Building Modeling

    PubMed Central

    Kedzierski, Michal; Fryskowska, Anna

    2014-01-01

    Visualization techniques have been greatly developed in the past few years. Three-dimensional models based on satellite and aerial imagery are now being enhanced by models generated using Aerial Laser Scanning (ALS) data. The most modern of such scanning systems have the ability to acquire over 50 points per square meter and to register a multiple echo, which allows the reconstruction of the terrain together with the terrain cover. However, ALS data accuracy is less than 10 cm and the data is often incomplete: there is no information about ground level (in most scanning systems), and often around the facade or structures which have been covered by other structures. However, Terrestrial Laser Scanning (TLS) not only acquires higher accuracy data (1–5 cm) but is also capable of registering those elements which are incomplete or not visible using ALS methods (facades, complicated structures, interiors, etc.). Therefore, to generate a complete 3D model of a building in high Level of Details, integration of TLS and ALS data is necessary. This paper presents the wavelet-based method of processing and integrating data from ALS and TLS. Methods of choosing tie points to combine point clouds in different datum will be analyzed. PMID:25004157

  8. Terrestrial and aerial laser scanning data integration using wavelet analysis for the purpose of 3D building modeling.

    PubMed

    Kedzierski, Michal; Fryskowska, Anna

    2014-07-07

    Visualization techniques have been greatly developed in the past few years. Three-dimensional models based on satellite and aerial imagery are now being enhanced by models generated using Aerial Laser Scanning (ALS) data. The most modern of such scanning systems have the ability to acquire over 50 points per square meter and to register a multiple echo, which allows the reconstruction of the terrain together with the terrain cover. However, ALS data accuracy is less than 10 cm and the data is often incomplete: there is no information about ground level (in most scanning systems), and often around the facade or structures which have been covered by other structures. However, Terrestrial Laser Scanning (TLS) not only acquires higher accuracy data (1-5 cm) but is also capable of registering those elements which are incomplete or not visible using ALS methods (facades, complicated structures, interiors, etc.). Therefore, to generate a complete 3D model of a building in high Level of Details, integration of TLS and ALS data is necessary. This paper presents the wavelet-based method of processing and integrating data from ALS and TLS. Methods of choosing tie points to combine point clouds in different datum will be analyzed.

  9. Quantifying depression storage of snowmelt runoff over frozen ground using aerial photography and digital elevation model

    NASA Astrophysics Data System (ADS)

    Hayashi, M.; Donovan, K.; Sjogren, D.

    2004-05-01

    The northern prairie region of North America is characterized by undulating terrains with very low regional gradient, underlain by clay-rich glacial tills. The soils derived from clay-rich tills have very low permeability when they are frozen. As a result a large amount of snowmelt runoff is generated over frozen ground. Numerous depressions on the undulating terrains trap snowmelt water and focus the infiltration flux under the depressions. Therefore, the depressions have important hydrologic functions regarding runoff retention and groundwater recharge. Previous studies have investigated the storage of snowmelt runoff and subsequent infiltration at a scale of each depression (102-103 m2). However, to understand the roles of depressions in regional hydrology, depression storage needs to be evaluated at a much larger scale. Our ultimate goal is to quantify depression storage at the scale of watersheds (102-103km 2) and represent it properly in a large-scale hydrologic model. As the first step towards this goal, we quantified depression storage at 1-km2 scale using infrared (IR) aerial photographs and digital elevation model combined with the measurement of water depth in depressions. Two parcels of land were selected for the study in the watershed of West Nose Creek, located immediately north of Calgary, Alberta, Canada. Each site contained a subsection of native prairie grass and cultivated field. Snow surveys were conducted at each site to estimate the average snow water equivalent (SWE) on the ground prior to melt. SWE ranged between 26 mm and 39 mm. Water depth was measured in 111 depressions when they were filled up to the peak level, and IR photographs were taken simultaneously at a scale of 1:10,000. The soil was frozen to a depth of 1 m or greater as indicated by several thermocouple arrays installed at the site. Detailed elevation survey was conducted in summer using a total station and differential global positioning system for 10 selected depressions to

  10. Performance modeling of unmanned aerial vehicles with on-board energy harvesting

    NASA Astrophysics Data System (ADS)

    Anton, Steven R.; Inman, Daniel J.

    2011-03-01

    The concept of energy harvesting in unmanned aerial vehicles (UAVs) has received much attention in recent years. Solar powered flight of small aircraft dates back to the 1970s when the first fully solar flight of an unmanned aircraft took place. Currently, research has begun to investigate harvesting ambient vibration energy during the flight of UAVs. The authors have recently developed multifunctional piezoelectric self-charging structures in which piezoelectric devices are combined with thin-film lithium batteries and a substrate layer in order to simultaneously harvest energy, store energy, and carry structural load. When integrated into mass and volume critical applications, such as unmanned aircraft, multifunctional devices can provide great benefit over conventional harvesting systems. A critical aspect of integrating any energy harvesting system into a UAV, however, is the potential effect that the additional system has on the performance of the aircraft. Added mass and increased drag can significantly degrade the flight performance of an aircraft, therefore, it is important to ensure that the addition of an energy harvesting system does not adversely affect the efficiency of a host aircraft. In this work, a system level approach is taken to examine the effects of adding both solar and piezoelectric vibration harvesting to a UAV test platform. A formulation recently presented in the literature is applied to describe the changes to the flight endurance of a UAV based on the power available from added harvesters and the mass of the harvesters. Details of the derivation of the flight endurance model are reviewed and the formulation is applied to an EasyGlider remote control foam hobbyist airplane, which is selected as the test platform for this study. A theoretical study is performed in which the normalized change in flight endurance is calculated based on the addition of flexible thin-film solar panels to the upper surface of the wings, as well as the addition

  11. Evaluation of a gully headcut retreat model using multitemporal aerial photographs and digital elevation models

    NASA Astrophysics Data System (ADS)

    Campo-Bescós, M. A.; Flores-Cervantes, J. H.; Bras, R. L.; Casalí, J.; Giráldez, J. V.

    2013-12-01

    large fraction of soil erosion in temperate climate systems proceeds from gully headcut growth processes. Nevertheless, headcut retreat is not well understood. Few erosion models include gully headcut growth processes, and none of the existing headcut retreat models have been tested against long-term retreat rate estimates. In this work the headcut retreat resulting from plunge pool erosion in the Channel Hillslope Integrated Landscape Development (CHILD) model is calibrated and compared to long-term evolution measurements of six gullies at the Bardenas Reales, northeast Spain. The headcut retreat module of CHILD was calibrated by adjusting the shape factor parameter to fit the observed retreat and volumetric soil loss of one gully during a 36 year period, using reported and collected field data to parameterize the rest of the model. To test the calibrated model, estimates by CHILD were compared to observations of headcut retreat from five other neighboring gullies. The differences in volumetric soil loss rates between the simulations and observations were less than 0.05 m3 yr-1, on average, with standard deviations smaller than 0.35 m3 yr-1. These results are the first evaluation of the headcut retreat module implemented in CHILD with a field data set. These results also show the usefulness of the model as a tool for simulating long-term volumetric gully evolution due to plunge pool erosion.

  12. A Groud and Aerial BattleField Spatio-Temporal Data Unified OrganizeModel and Aplication

    NASA Astrophysics Data System (ADS)

    Feng, LI; Qin, Li; Gang, WAN; Xuefeng, CAO

    2016-11-01

    Aiming at the requirement of battlefield environment data model in joint operations, this paper proposed a groud and aerial battlefield spatio-temporal data unified organize model based on grid division. The thought of shere grid division is adopt to divide the space, and extend to the time dimension. Also, the spatio-temporal grid coding is designed. The field and object are combined to build the BSTD organization model, where the panet layer unit and panet volume unit are considered as the reference space separately to quantitatively describe the field, and the spatio-temporal grid coding is adopt to describe the space and time attributes of the objects. The relevant experiment is designed in paratroop tactics wargame simulation, and the results verify the feasibility of the model.

  13. Integration of a Generalised Building Model Into the Pose Estimation of Uas Images

    NASA Astrophysics Data System (ADS)

    Unger, J.; Rottensteiner, F.; Heipke, C.

    2016-06-01

    A hybrid bundle adjustment is presented that allows for the integration of a generalised building model into the pose estimation of image sequences. These images are captured by an Unmanned Aerial System (UAS) equipped with a camera flying in between the buildings. The relation between the building model and the images is described by distances between the object coordinates of the tie points and building model planes. Relations are found by a simple 3D distance criterion and are modelled as fictitious observations in a Gauss-Markov adjustment. The coordinates of model vertices are part of the adjustment as directly observed unknowns which allows for changes in the model. Results of first experiments using a synthetic and a real image sequence demonstrate improvements of the image orientation in comparison to an adjustment without the building model, but also reveal limitations of the current state of the method.

  14. Modeling and Optimization of Multiple Unmanned Aerial Vehicles System Architecture Alternatives

    PubMed Central

    Wang, Weiping; He, Lei

    2014-01-01

    Unmanned aerial vehicle (UAV) systems have already been used in civilian activities, although very limitedly. Confronted different types of tasks, multi UAVs usually need to be coordinated. This can be extracted as a multi UAVs system architecture problem. Based on the general system architecture problem, a specific description of the multi UAVs system architecture problem is presented. Then the corresponding optimization problem and an efficient genetic algorithm with a refined crossover operator (GA-RX) is proposed to accomplish the architecting process iteratively in the rest of this paper. The availability and effectiveness of overall method is validated using 2 simulations based on 2 different scenarios. PMID:25140328

  15. Modeling and optimization of multiple unmanned aerial vehicles system architecture alternatives.

    PubMed

    Qin, Dongliang; Li, Zhifei; Yang, Feng; Wang, Weiping; He, Lei

    2014-01-01

    Unmanned aerial vehicle (UAV) systems have already been used in civilian activities, although very limitedly. Confronted different types of tasks, multi UAVs usually need to be coordinated. This can be extracted as a multi UAVs system architecture problem. Based on the general system architecture problem, a specific description of the multi UAVs system architecture problem is presented. Then the corresponding optimization problem and an efficient genetic algorithm with a refined crossover operator (GA-RX) is proposed to accomplish the architecting process iteratively in the rest of this paper. The availability and effectiveness of overall method is validated using 2 simulations based on 2 different scenarios.

  16. Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Longmore, S. N.; Collins, R. P.; Pfeifer, S.; Fox, S. E.; Mulero-Pazmany, M.; Bezombes, F.; Goodwind, A.; de Juan Ovelar, M.; Knapen, J. H.; Wich, S. A.

    2017-02-01

    In this paper we describe an unmanned aerial system equipped with a thermal-infrared camera and software pipeline that we have developed to monitor animal populations for conservation purposes. Taking a multi-disciplinary approach to tackle this problem, we use freely available astronomical source detection software and the associated expertise of astronomers, to efficiently and reliably detect humans and animals in aerial thermal-infrared footage. Combining this astronomical detection software with existing machine learning algorithms into a single, automated, end-to-end pipeline, we test the software using aerial video footage taken in a controlled, field-like environment. We demonstrate that the pipeline works reliably and describe how it can be used to estimate the completeness of different observational datasets to objects of a given type as a function of height, observing conditions etc. - a crucial step in converting video footage to scientifically useful information such as the spatial distribution and density of different animal species. Finally, having demonstrated the potential utility of the system, we describe the steps we are taking to adapt the system for work in the field, in particular systematic monitoring of endangered species at National Parks around the world.

  17. Blending zone determination for aerial orthimage mosaicking

    NASA Astrophysics Data System (ADS)

    Lin, Chao-Hung; Chen, Bo-Heng; Lin, Bo-Yi; Chou, Han-Szu

    2016-09-01

    Creating a composed image from a set of aerial images is a fundamental step in orthomosaic generation. One of the processes involved in this technique is determining an optimal seamline in an overlapping region to stitch image patches seamlessly. Most previous studies have solved this optimization problem by searching for a one-pixel-wide seamline with an objective function. This strategy significantly reduced pixel mismatches on the seamline caused by geometric distortions of images but did not fully consider color discontinuity and mismatch problems that occur around the seamline, which sometimes cause mosaicking artifacts. This study proposes a blending zone determination scheme with a novel path finding algorithm to reduce the occurrence of unwanted artifacts. Instead of searching for a one-pixel-wide seamline, a blending zone, which is a k-pixel-wide seamline that passes through high-similarity pixels in the overlapping region, is determined using a hierarchical structure. This strategy allows for not only seamless stitching but also smooth color blending of neighboring image patches. Moreover, the proposed method searches for a blending zone without the pre-process of highly mismatched pixel removal and additional geographic data of road vectors and digital surface/elevation models, which increases the usability of the approach. Qualitative and quantitative analyses of aerial images demonstrate the superiority of the proposed method to related methods in terms of avoidance of passing highly mismatched pixels.

  18. D Surface Generation from Aerial Thermal Imagery

    NASA Astrophysics Data System (ADS)

    Khodaei, B.; Samadzadegan, F.; Dadras Javan, F.; Hasani, H.

    2015-12-01

    Aerial thermal imagery has been recently applied to quantitative analysis of several scenes. For the mapping purpose based on aerial thermal imagery, high accuracy photogrammetric process is necessary. However, due to low geometric resolution and low contrast of thermal imaging sensors, there are some challenges in precise 3D measurement of objects. In this paper the potential of thermal video in 3D surface generation is evaluated. In the pre-processing step, thermal camera is geometrically calibrated using a calibration grid based on emissivity differences between the background and the targets. Then, Digital Surface Model (DSM) generation from thermal video imagery is performed in four steps. Initially, frames are extracted from video, then tie points are generated by Scale-Invariant Feature Transform (SIFT) algorithm. Bundle adjustment is then applied and the camera position and orientation parameters are determined. Finally, multi-resolution dense image matching algorithm is used to create 3D point cloud of the scene. Potential of the proposed method is evaluated based on thermal imaging cover an industrial area. The thermal camera has 640×480 Uncooled Focal Plane Array (UFPA) sensor, equipped with a 25 mm lens which mounted in the Unmanned Aerial Vehicle (UAV). The obtained results show the comparable accuracy of 3D model generated based on thermal images with respect to DSM generated from visible images, however thermal based DSM is somehow smoother with lower level of texture. Comparing the generated DSM with the 9 measured GCPs in the area shows the Root Mean Square Error (RMSE) value is smaller than 5 decimetres in both X and Y directions and 1.6 meters for the Z direction.

  19. Aerial vehicles collision avoidance using monocular vision

    NASA Astrophysics Data System (ADS)

    Balashov, Oleg; Muraviev, Vadim; Strotov, Valery

    2016-10-01

    In this paper image-based collision avoidance algorithm that provides detection of nearby aircraft and distance estimation is presented. The approach requires a vision system with a single moving camera and additional information about carrier's speed and orientation from onboard sensors. The main idea is to create a multi-step approach based on a preliminary detection, regions of interest (ROI) selection, contour segmentation, object matching and localization. The proposed algorithm is able to detect small targets but unlike many other approaches is designed to work with large-scale objects as well. To localize aerial vehicle position the system of equations relating object coordinates in space and observed image is solved. The system solution gives the current position and speed of the detected object in space. Using this information distance and time to collision can be estimated. Experimental research on real video sequences and modeled data is performed. Video database contained different types of aerial vehicles: aircrafts, helicopters, and UAVs. The presented algorithm is able to detect aerial vehicles from several kilometers under regular daylight conditions.

  20. Small unmanned aerial vehicles (micro-UAVs, drones) in plant ecology1

    PubMed Central

    Cruzan, Mitchell B.; Weinstein, Ben G.; Grasty, Monica R.; Kohrn, Brendan F.; Hendrickson, Elizabeth C.; Arredondo, Tina M.; Thompson, Pamela G.

    2016-01-01

    Premise of the study: Low-elevation surveys with small aerial drones (micro–unmanned aerial vehicles [UAVs]) may be used for a wide variety of applications in plant ecology, including mapping vegetation over small- to medium-sized regions. We provide an overview of methods and procedures for conducting surveys and illustrate some of these applications. Methods: Aerial images were obtained by flying a small drone along transects over the area of interest. Images were used to create a composite image (orthomosaic) and a digital surface model (DSM). Vegetation classification was conducted manually and using an automated routine. Coverage of an individual species was estimated from aerial images. Results: We created a vegetation map for the entire region from the orthomosaic and DSM, and mapped the density of one species. Comparison of our manual and automated habitat classification confirmed that our mapping methods were accurate. A species with high contrast to the background matrix allowed adequate estimate of its coverage. Discussion: The example surveys demonstrate that small aerial drones are capable of gathering large amounts of information on the distribution of vegetation and individual species with minimal impact to sensitive habitats. Low-elevation aerial surveys have potential for a wide range of applications in plant ecology. PMID:27672518

  1. Preliminary applications of Landsat images and aerial photography for determining land-use, geologic, and hydrologic characteristics, Yampa River basin, Colorado and Wyoming

    USGS Publications Warehouse

    Heimes, F.J.; Moore, G.K.; Steele, T.D.

    1978-01-01

    Expanded energy- and recreation-related activities in the Yampa River basin, Colorado and Wyoming, have caused a rapid increase in economic development which will result in increased demand and competition for natural resources. In planning for efficient allocation of the basin 's natural resources, Landsat images and small-scale color and color-infrared photographs were used for selected geologic, hydrologic and land-use applications within the Yampa River basin. Applications of Landsat data included: (1) regional land-use classification and mapping, (2) lineament mapping, and (3) areal snow-cover mapping. Results from the Landsat investigations indicated that: (1) Landsat land-use classification maps, at a regional level, compared favorably with areal land-use patterns that were defined from available ground information, (2) lineaments were mapped in sufficient detail using recently developed techniques for interpreting aerial photographs, (3) snow cover generally could be mapped for large areas with the exception of some densely forested areas of the basin and areas having a large percentage of winter-season cloud cover. Aerial photographs were used for estimation of turbidity for eight stream locations in the basin. Spectral reflectance values obtained by digitizing photographs were compared with measured turbidity values. Results showed strong correlations (variances explained of greater than 90 percent) between spectral reflectance obtained from color photographs and measured turbidity values. (Woodard-USGS)

  2. Identification of disrupted surfaces due to military activity at the Ft. Irwin National Training Center: An aerial photograph and satellite image analysis

    SciTech Connect

    McCarthy, L.E.; Marsh, S.E.; Lee, C.

    1996-07-01

    Concern for environmental management of our natural resources is most often focused on the anthropogenic impacts placed upon these resources. Desert landscapes, in particular, are fragile environments, and minimal stresses on surficial materials can greatly increase the rate and character of erosional responses. The National Training Center, Ft. Irwin, located in the middle of the Mojave Desert, California, provides an isolated study area of intense ORV activity occurring over a 50-year period. Geomorphic surfaces, and surficial disruption from two study sites within the Ft. Irwin area were mapped from 1947, 1:28,400, and 1993 1:12,000 black and white aerial photographs. Several field checks were conducted to verify this mapping. However, mapping from black and white aerial photography relies heavily on tonal differences, patterns, and morphological criteria. Satellite imagery, sensitive to changes in mineralogy, can help improve the ability to distinguish geomorphic units in desert regions. In order to assess both the extent of disrupted surfaces and the surficial geomorphology discemable from satellite imagery, analysis was done on SPOT panchromatic and Landsat Thematic Mapper (TM) multispectral imagery acquired during the spring of 1987 and 1993. The resulting classified images provide a clear indication of the capabilities of the satellite data to aid in the delineation of disrupted geomorphic surfaces.

  3. Image segmentation using hidden Markov Gauss mixture models.

    PubMed

    Pyun, Kyungsuk; Lim, Johan; Won, Chee Sun; Gray, Robert M

    2007-07-01

    Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

  4. Segmentation and Reconstruction of Buildings with Aerial Oblique Photography Point Clouds

    NASA Astrophysics Data System (ADS)

    Liu, P.; Li, Y. C.; Hu, W.; Ding, X. B.

    2015-06-01

    Oblique photography technology as an excellent method for 3-D city model construction has brought itself to large-scale recognition and undeniable high social status. Tilt and vertical images with the high overlaps and different visual angles can produce a large number of dense matching point clouds data with spectral information. This paper presents a method of buildings reconstruction with stereo matching dense point clouds from aerial oblique images, which includes segmentation of buildings and reconstruction of building roofs. We summarize the characteristics of stereo matching point clouds from aerial oblique images and outline the problems with existing methods. Then we present the method for segmentation of building roofs, which based on colors and geometrical derivatives such as normal and curvature. Finally, a building reconstruction approach is developed based on the geometrical relationship. The experiment and analysis show that the methods are effective on building reconstruction with stereo matching point clouds from aerial oblique images.

  5. The Kilauea 1974 Flow: Quantitative Morphometry of Lava Flows using Low Altitude Aerial Image Data using a Kite-based Platform in the Field

    NASA Astrophysics Data System (ADS)

    Scheidt, S. P.; Whelley, P.; Hamilton, C.; Bleacher, J. E.; Garry, W. B.

    2015-12-01

    The December 31, 1974 lava flow from Kilauea Caldera, Hawaii within the Hawaii Volcanoes National Park was selected for field campaigns as a terrestrial analog for Mars in support of NASA Planetary Geology and Geophysics (PGG) research and the Remote, In Situ and Synchrotron Studies for Science and Exploration (RIS4E) node of the Solar System Exploration Research Virtual Institute (SSERVI) program). The lava flow was a rapidly emplaced unit that was strongly influenced by existing topography, which favored the formation of a tributary lava flow system. The unit includes a diverse range of surface textures (e.g., pāhoehoe, ´áā, and transitional lavas), and structural features (e.g., streamlined islands, pits, and interactions with older tumuli). However, these features are generally below the threshold of visibility within previously acquired airborne and spacecraft data. In this study, we have generated unique, high-resolution digital images using low-altitude Kite Aerial Photography (KAP) system during field campaigns in 2014 and 2015 (National Park Service permit #HAVO-2012-SCI-0025). The kite-based mapping platform (nadir-viewing) and a radio-controlled gimbal (allowing pointing) provided similar data as from an unmanned aerial vehicle (UAV), but with longer flight time, larger total data volumes per sortie, and fewer regulatory challenges and cost. Images acquired from KAP and UAVs are used to create orthomosaics and DEMs using Multi-View Stereo-Photogrammetry (MVSP) software. The 3-Dimensional point clouds are extremely dense, resulting in a grid resolution of < 2 cm. Airborne Light Detection and Ranging (LiDAR) / Terrestrial Laser Scanning (TLS) data have been collected for these areas and provide a basis of comparison or "ground truth" for the photogrammetric data. Our results show a good comparison with LiDAR/TLS data, each offering their own unique advantages and potential for data fusion.

  6. Detailed and Highly Accurate 3d Models of High Mountain Areas by the Macs-Himalaya Aerial Camera Platform

    NASA Astrophysics Data System (ADS)

    Brauchle, J.; Hein, D.; Berger, R.

    2015-04-01

    Remote sensing in areas with extreme altitude differences is particularly challenging. In high mountain areas specifically, steep slopes result in reduced ground pixel resolution and degraded quality in the DEM. Exceptionally high brightness differences can in part no longer be imaged by the sensors. Nevertheless, detailed information about mountainous regions is highly relevant: time and again glacier lake outburst floods (GLOFs) and debris avalanches claim dozens of victims. Glaciers are sensitive to climate change and must be carefully monitored. Very detailed and accurate 3D maps provide a basic tool for the analysis of natural hazards and the monitoring of glacier surfaces in high mountain areas. There is a gap here, because the desired accuracies are often not achieved. It is for this reason that the DLR Institute of Optical Sensor Systems has developed a new aerial camera, the MACS-Himalaya. The measuring unit comprises four camera modules with an overall aperture angle of 116° perpendicular to the direction of flight. A High Dynamic Range (HDR) mode was introduced so that within a scene, bright areas such as sun-flooded snow and dark areas such as shaded stone can be imaged. In 2014, a measuring survey was performed on the Nepalese side of the Himalayas. The remote sensing system was carried by a Stemme S10 motor glider. Amongst other targets, the Seti Valley, Kali-Gandaki Valley and the Mt. Everest/Khumbu Region were imaged at heights up to 9,200 m. Products such as dense point clouds, DSMs and true orthomosaics with a ground pixel resolution of up to 15 cm were produced. Special challenges and gaps in the investigation of high mountain areas, approaches for resolution of these problems, the camera system and the state of evaluation are presented with examples.

  7. Quantifying Aerial Concentrations of Maize Pollen in the Atmospheric Surface Layer Using Remote-Piloted Airplanes and Lagrangian Stochastic Modeling

    NASA Astrophysics Data System (ADS)

    Aylor, Donald E.; Boehm, Matthew T.; Shields, Elson J.

    2006-07-01

    The extensive adoption of genetically modified crops has led to a need to understand better the dispersal of pollen in the atmosphere because of the potential for unwanted movement of genetic traits via pollen flow in the environment. The aerial dispersal of maize pollen was studied by comparing the results of a Lagrangian stochastic (LS) model with pollen concentration measurements made over cornfields using a combination of tower-based rotorod samplers and airborne radio-controlled remote-piloted vehicles (RPVs) outfitted with remotely operated pollen samplers. The comparison between model and measurements was conducted in two steps. In the first step, the LS model was used in combination with the rotorod samplers to estimate the pollen release rate Q for each sampling period. In the second step, a modeled value for the concentration Cmodel, corresponding to each RPV measured value Cmeasure, was calculated by simulating the RPV flight path through the LS model pollen plume corresponding to the atmospheric conditions, field geometry, wind direction, and source strength. The geometric mean and geometric standard deviation of the ratio Cmodel/Cmeasure over all of the sampling periods, except those determined to be upwind of the field, were 1.42 and 4.53, respectively, and the lognormal distribution corresponding to these values was found to fit closely the PDF of Cmodel/Cmeasure. Model output was sensitive to the turbulence parameters, with a factor-of-100 difference in the average value of Cmodel over the range of values encountered during the experiment. In comparison with this large potential variability, it is concluded that the average factor of 1.4 between Cmodel and Cmeasure found here indicates that the LS model is capable of accurately predicting, on average, concentrations over a range of atmospheric conditions.

  8. Quantitative extraction of bedrock exposed rate based on unmanned aerial vehicle data and TM image in Karst Environment

    NASA Astrophysics Data System (ADS)

    wang, hongyan; li, qiangzi; du, xin; zhao, longcai

    2016-04-01

    In the karst regions of Southwest China, rocky desertification is one of the most serious problems of land degradation. The bedrock exposed rate is one of the important indexes to assess the degree of rocky desertification in the karst regions. Because of the inherent merits of macro scale, frequency, efficiency and synthesis, remote sensing is the promising method to monitor and assess karst rocky desertification on large scale. However, the actual measurement of bedrock exposed rate is difficult and existing remote sensing methods cannot directly be exploited to extract the bedrock exposed rate owing to the high complexity and heterogeneity of karst environments. Therefore, based on the UAV and TM data, the paper selected Xingren County as the research area, and the quantitative extraction of the bedrock exposed rate based on the multi scale remote sensing data was developed. Firstly, we used the object oriented method to carry out the accurate classification of UAV image and based on the results of rock extraction, the bedrock exposed rate was calculated in the 30m grid scale. Parts of the calculated samples were as training data and another samples were as the model validation data. Secondly, in each grid the band reflectivity of TM data was extracted and we also calculated a variety of rock index and vegetation index (NDVI, SAVI etc.). Finally, the network model was established to extract the bedrock exposed rate, the correlation coefficient (R) of the network model was 0.855 and the correlation coefficient (R) of the validation model was 0.677, the root mean square error (RMSE) was 0.073. Based on the quantitative inversion model, the distribution map of the bedrock exposed rate in Xingren County was obtained. Keywords: Bedrock exposed rate, quantitative extraction, UAV and TM data, Karst rocky desertification.

  9. Scaling Sap Flow Results Over Wide Areas Using High-Resolution Aerial Multispectral Digital Imaging, Leaf Area Index (LAI) and MODIS Satellite Imagery in Saltcedar Stands on the Lower Colorado River

    NASA Astrophysics Data System (ADS)

    Murray, R.; Neale, C.; Nagler, P. L.; Glenn, E. P.

    2008-12-01

    Heat-balance sap flow sensors provide direct estimates of water movement through plant stems and can be used to accurately measure leaf-level transpiration (EL) and stomatal conductance (GS) over time scales ranging from 20-minutes to a month or longer in natural stands of plants. However, their use is limited to relatively small branches on shrubs or trees, as the gauged stem section needs to be uniformly heated by the heating coil to produce valid measurements. This presents a scaling problem in applying the results to whole plants, stands of plants, and larger landscape areas. We used high-resolution aerial multispectral digital imaging with green, red and NIR bands as a bridge between ground measurements of EL and GS, and MODIS satellite imagery of a flood plain on the Lower Colorado River dominated by saltcedar (Tamarix ramosissima). Saltcedar is considered to be a high-water-use plant, and saltcedar removal programs have been proposed to salvage water. Hence, knowledge of actual saltcedar ET rates is needed on western U.S. rivers. Scaling EL and GS to large landscape units requires knowledge of leaf area index (LAI) over large areas. We used a LAI model developed for riparian habitats on Bosque del Apache, New Mexico, to estimate LAI at our study site on the Colorado River. We compared the model estimates to ground measurements of LAI, determined with a Li-Cor LAI-2000 Plant Canopy Analyzer calibrated by leaf harvesting to determine Specific Leaf Area (SLA) (m2 leaf area per g dry weight leaves) of the different species on the floodplain. LAI could be adequately predicted from NDVI from aerial multispectral imagery and could be cross-calibrated with MODIS NDVI and EVI. Hence, we were able to project point measurements of sap flow and LAI over multiple years and over large areas of floodplain using aerial multispectral imagery as a bridge between ground and satellite data. The methods are applicable to riparian corridors throughout the western U.S.

  10. The future of structural fieldwork - UAV assisted aerial photogrammetry

    NASA Astrophysics Data System (ADS)

    Vollgger, Stefan; Cruden, Alexander

    2015-04-01

    Unmanned aerial vehicles (UAVs), commonly referred to as drones, are opening new and low cost possibilities to acquire high-resolution aerial images and digital surface models (DSM) for applications in structural geology. UAVs can be programmed to fly autonomously along a user defined grid to systematically capture high-resolution photographs, even in difficult to access areas. The photographs are subsequently processed using software that employ SIFT (scale invariant feature transform) and SFM (structure from motion) algorithms. These photogrammetric routines allow the extraction of spatial information (3D point clouds, digital elevation models, 3D meshes, orthophotos) from 2D images. Depending on flight altitude and camera setup, sub-centimeter spatial resolutions can be achieved. By "digitally mapping" georeferenced 3D models and images, orientation data can be extracted directly and used to analyse the structural framework of the mapped object or area. We present UAV assisted aerial mapping results from a coastal platform near Cape Liptrap (Victoria, Australia), where deformed metasediments of the Palaeozoic Lachlan Fold Belt are exposed. We also show how orientation and spatial information of brittle and ductile structures extracted from the photogrammetric model can be linked to the progressive development of folds and faults in the region. Even though there are both technical and legislative limitations, which might prohibit the use of UAVs without prior commercial licensing and training, the benefits that arise from the resulting high-resolution, photorealistic models can substantially contribute to the collection of new data and insights for applications in structural geology.

  11. Hierarchical modeling for image classification

    NASA Technical Reports Server (NTRS)

    Likens, W.; Maw, K.

    1982-01-01

    As part of the California Integrated Remote Sensing System's (CIRSS) San Bernardino County Project, the use of data layers from a geographic information system (GIS) as an integral part of the Landsat image classification process was investigated. Through a hierarchical modeling technique, elevation, aspect, land use, vegetation, and growth management data from the project's data base were used to guide class labeling decisions in a 1976 Landsat MSS land cover classification. A similar model, incorporating 1976-1979 Landsat spectral change data in addition to other data base elements, was used in the classification of a 1979 Landsat image. The resultant Landsat products were integrated as additional layers into the data base for use in growth management, fire hazard, and hydrological modeling.

  12. A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications

    PubMed Central

    Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong

    2015-01-01

    It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks. PMID:26076404

  13. A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications.

    PubMed

    Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong

    2015-06-12

    It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs' route planning for small and medium-scale networks.

  14. The Potential of Unmanned Aerial Vehicle for Large Scale Mapping of Coastal Area

    NASA Astrophysics Data System (ADS)

    Darwin, N.; Ahmad, A.; Zainon, O.

    2014-02-01

    Many countries in the tropical region are covered with cloud for most of the time, hence, it is difficult to get clear images especially from high resolution satellite imagery. Aerial photogrammetry can be used but most of the time the cloud problem still exists. Today, this problem could be solved using a system known as unmanned aerial vehicle (UAV) where the aerial images can be acquired at low altitude and the system can fly under the cloud. The UAV system could be used in various applications including mapping coastal area. The UAV system is equipped with an autopilot system and automatic method known as autonomous flying that can be utilized for data acquisition. To achieve high resolution imagery, a compact digital camera of high resolution was used to acquire the aerial images at an altitude. In this study, the UAV system was employed to acquire aerial images of a coastal simulation model at low altitude. From the aerial images, photogrammetric image processing was executed to produce photogrammetric outputs such a digital elevation model (DEM), contour line and orthophoto. In this study, ground control point (GCP) and check point (CP) were established using conventional ground surveying method (i.e total station). The GCP is used for exterior orientation in photogrammetric processes and CP for accuracy assessment based on Root Mean Square Error (RMSE). From this study, it was found that the UAV system can be used for large scale mapping of coastal simulation model with accuracy at millimeter level. It is anticipated that the same system could be used for large scale mapping of real coastal area and produces good accuracy. Finally, the UAV system has great potential to be used for various applications that require accurate results or products at limited time and less man power.

  15. Near infrared-red models for the remote estimation of chlorophyll- a concentration in optically complex turbid productive waters: From in situ measurements to aerial imagery

    NASA Astrophysics Data System (ADS)

    Gurlin, Daniela

    Today the water quality of many inland and coastal waters is compromised by cultural eutrophication in consequence of increased human agricultural and industrial activities and remote sensing is widely applied to monitor the trophic state of these waters. This study explores near infrared-red models for the remote estimation of chlorophyll-a concentration in turbid productive waters and compares several near infrared-red models developed within the last 35 years. Three of these near infrared-red models were calibrated for a dataset with chlorophyll-a concentrations from 2.3 to 81.2 mg m -3 and validated for independent and statistically significantly different datasets with chlorophyll-a concentrations from 4.0 to 95.5 mg m-3 and 4.0 to 24.2 mg m-3 for the spectral bands of the MEdium Resolution Imaging Spectrometer (MERIS) and Moderate-resolution Imaging Spectroradiometer (MODIS). The developed MERIS two-band algorithm estimated chlorophyll-a concentrations from 4.0 to 24.2 mg m-3, which are typical for many inland and coastal waters, very accurately with a mean absolute error 1.2 mg m-3. These results indicate a high potential of the simple MERIS two-band algorithm for the reliable estimation of chlorophyll-a concentration without any reduction in accuracy compared to more complex algorithms, even though more research seems required to analyze the sensitivity of this algorithm to differences in the chlorophyll-a specific absorption coefficient of phytoplankton. Three near infrared-red models were calibrated and validated for a smaller dataset of atmospherically corrected multi-temporal aerial imagery collected by the hyperspectral airborne imaging spectrometer for applications (AisaEAGLE). The developed algorithms successfully captured the spatial and temporal variability of the chlorophyll-a concentrations and estimated chlorophyll- a concentrations from 2.3 to 81.2 mg m-3 with mean absolute errors from 4.4 mg m-3 for the AISA two band algorithm to 5.2 mg m-3

  16. Aerial Vehicle Surveys of Other Planetary Atmospheres and Surfaces: Imaging, Remote-Sensing, and Autonomy Technology Requirements

    DTIC Science & Technology

    2005-01-01

    hillsides possibly created by water. Sensitive (scanning laser ) altimeter to map terrain. Imaging comparison against known classifier forms at...create overlay maps of different spectral images in parallel. Laser and/or Radar altimeter Can image downward, forward, and off axis. Sensitive to...terrain following autopilot was then designed that closed the loop on an auxiliary sensor, ( laser altimeter), since terrain altitude is an indirect

  17. Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery

    NASA Astrophysics Data System (ADS)

    Ma, Lei; Cheng, Liang; Li, Manchun; Liu, Yongxue; Ma, Xiaoxue

    2015-04-01

    Unmanned Aerial Vehicle (UAV) has been used increasingly for natural resource applications in recent years due to their greater availability and the miniaturization of sensors. In addition, Geographic Object-Based Image Analysis (GEOBIA) has received more attention as a novel paradigm for remote sensing earth observation data. However, GEOBIA generates some new problems compared with pixel-based methods. In this study, we developed a strategy for the semi-automatic optimization of object-based classification, which involves an area-based accuracy assessment that analyzes the relationship between scale and the training set size. We found that the Overall Accuracy (OA) increased as the training set ratio (proportion of the segmented objects used for training) increased when the Segmentation Scale Parameter (SSP) was fixed. The OA increased more slowly as the training set ratio became larger and a similar rule was obtained according to the pixel-based image analysis. The OA decreased as the SSP increased when the training set ratio was fixed. Consequently, the SSP should not be too large during classification using a small training set ratio. By contrast, a large training set ratio is required if classification is performed using a high SSP. In addition, we suggest that the optimal SSP for each class has a high positive correlation with the mean area obtained by manual interpretation, which can be summarized by a linear correlation equation. We expect that these results will be applicable to UAV imagery classification to determine the optimal SSP for each class.

  18. Toward autonomous avian-inspired grasping for micro aerial vehicles.

    PubMed

    Thomas, Justin; Loianno, Giuseppe; Polin, Joseph; Sreenath, Koushil; Kumar, Vijay

    2014-06-01

    Micro aerial vehicles, particularly quadrotors, have been used in a wide range of applications. However, the literature on aerial manipulation and grasping is limited and the work is based on quasi-static models. In this paper, we draw inspiration from agile, fast-moving birds such as raptors, that are able to capture moving prey on the ground or in water, and develop similar capabilities for quadrotors. We address dynamic grasping, an approach to prehensile grasping in which the dynamics of the robot and its gripper are significant and must be explicitly modeled and controlled for successful execution. Dynamic grasping is relevant for fast pick-and-place operations, transportation and delivery of objects, and placing or retrieving sensors. We show how this capability can be realized (a) using a motion capture system and (b) without external sensors relying only on onboard sensors. In both cases we describe the dynamic model, and trajectory planning and control algorithms. In particular, we present a methodology for flying and grasping a cylindrical object using feedback from a monocular camera and an inertial measurement unit onboard the aerial robot. This is accomplished by mapping the dynamics of the quadrotor to a level virtual image plane, which in turn enables dynamically-feasible trajectory planning for image features in the image space, and a vision-based controller with guaranteed convergence properties. We also present experimental results obtained with a quadrotor equipped with an articulated gripper to illustrate both approaches.

  19. Bayesian image reconstruction - The pixon and optimal image modeling

    NASA Technical Reports Server (NTRS)

    Pina, R. K.; Puetter, R. C.

    1993-01-01

    In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.

  20. Bayesian image reconstruction - The pixon and optimal image modeling

    NASA Astrophysics Data System (ADS)

    Pina, R. K.; Puetter, R. C.

    1993-06-01

    In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.

  1. High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling

    PubMed Central

    Watanabe, Kakeru; Guo, Wei; Arai, Keigo; Takanashi, Hideki; Kajiya-Kanegae, Hiromi; Kobayashi, Masaaki; Yano, Kentaro; Tokunaga, Tsuyoshi; Fujiwara, Toru; Tsutsumi, Nobuhiro; Iwata, Hiroyoshi

    2017-01-01

    Genomics-assisted breeding methods have been rapidly developed with novel technologies such as next-generation sequencing, genomic selection and genome-wide association study. However, phenotyping is still time consuming and is a serious bottleneck in genomics-assisted breeding. In this study, we established a high-throughput phenotyping system for sorghum plant height and its response to nitrogen availability; this system relies on the use of unmanned aerial vehicle (UAV) remote sensing with either an RGB or near-infrared, green and blue (NIR-GB) camera. We evaluated the potential of remote sensing to provide phenotype training data in a genomic prediction model. UAV remote sensing with the NIR-GB camera and the 50th percentile of digital surface model, which is an indicator of height, performed well. The correlation coefficient between plant height measured by UAV remote sensing (PHUAV) and plant height measured with a ruler (PHR) was 0.523. Because PHUAV was overestimated (probably because of the presence of taller plants on adjacent plots), the correlation coefficient between PHUAV and PHR was increased to 0.678 by using one of the two replications (that with the lower PHUAV value). Genomic prediction modeling performed well under the low-fertilization condition, probably because PHUAV overestimation was smaller under this condition due to a lower plant height. The predicted values of PHUAV and PHR were highly correlated with each other (r = 0.842). This result suggests that the genomic prediction models generated with PHUAV were almost identical and that the performance of UAV remote sensing was similar to that of traditional measurements in genomic prediction modeling. UAV remote sensing has a high potential to increase the throughput of phenotyping and decrease its cost. UAV remote sensing will be an important and indispensable tool for high-throughput genomics-assisted plant breeding.

  2. High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling.

    PubMed

    Watanabe, Kakeru; Guo, Wei; Arai, Keigo; Takanashi, Hideki; Kajiya-Kanegae, Hiromi; Kobayashi, Masaaki; Yano, Kentaro; Tokunaga, Tsuyoshi; Fujiwara, Toru; Tsutsumi, Nobuhiro; Iwata, Hiroyoshi

    2017-01-01

    Genomics-assisted breeding methods have been rapidly developed with novel technologies such as next-generation sequencing, genomic selection and genome-wide association study. However, phenotyping is still time consuming and is a serious bottleneck in genomics-assisted breeding. In this study, we established a high-throughput phenotyping system for sorghum plant height and its response to nitrogen availability; this system relies on the use of unmanned aerial vehicle (UAV) remote sensing with either an RGB or near-infrared, green and blue (NIR-GB) camera. We evaluated the potential of remote sensing to provide phenotype training data in a genomic prediction model. UAV remote sensing with the NIR-GB camera and the 50th percentile of digital surface model, which is an indicator of height, performed well. The correlation coefficient between plant height measured by UAV remote sensing (PHUAV) and plant height measured with a ruler (PHR) was 0.523. Because PHUAV was overestimated (probably because of the presence of taller plants on adjacent plots), the correlation coefficient between PHUAV and PHR was increased to 0.678 by using one of the two replications (that with the lower PHUAV value). Genomic prediction modeling performed well under the low-fertilization condition, probably because PHUAV overestimation was smaller under this condition due to a lower plant height. The predicted values of PHUAV and PHR were highly correlated with each other (r = 0.842). This result suggests that the genomic prediction models generated with PHUAV were almost identical and that the performance of UAV remote sensing was similar to that of traditional measurements in genomic prediction modeling. UAV remote sensing has a high potential to increase the throughput of phenotyping and decrease its cost. UAV remote sensing will be an important and indispensable tool for high-throughput genomics-assisted plant breeding.

  3. Using occupancy models to accommodate uncertainty in the interpretation of aerial photograph data: status of beaver in Central Oregon, USA

    USGS Publications Warehouse

    Pearl, Christopher A.; Adams, Michael J.; Haggerty, Patricia K.; Urban, Leslie

    2015-01-01

    Beavers (Castor canadensis) influence habitat for many species and pose challenges in developed landscapes. They are increasingly viewed as a cost-efficient means of riparian habitat restoration and water storage. Still, information on their status is rare, particularly in western North America. We used aerial photography to evaluate changes in beaver occupancy between 1942–1968 and 2009 in upper portions of 2 large watersheds in Oregon, USA. We used multiple observers and occupancy modeling to account for bias related to photo quality, observers, and imperfect detection of beaver impoundments. Our analysis suggested a slightly higher rate of beaver occupancy in the upper Deschutes than the upper Klamath basin. We found weak evidence for beaver increases in the west and declines in eastern parts of the study area. Our study presents a method for dealing with observer variation in photo interpretation and provides the first assessment of the extent of beaver influence in 2 basins with major water-use challenges. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

  4. Area and Elevation Changes of a Debris-Covered Glacier and a Clean-Ice Glacier Between 1952-2013 Using Aerial Images and Structure-from-Motion

    NASA Astrophysics Data System (ADS)

    Lardeux, P.; Glasser, N. F.; Holt, T.; Irvine-Fynn, T. D.; Hubbard, B. P.

    2015-12-01

    Since 1952, the clean-ice Glacier Blanc has retreated twice as fast as the adjacent debris-covered Glacier Noir. Located in the French Alps and separated by only 1 km, both glaciers experience the same climatic conditions, making them ideal to evaluate the impact of debris cover on glacier evolution. We used aerial photographs from 16 acquisitions from 1952 to 2013 to reconstruct and analyze glacier elevation changes using Structure-from-Motion (SfM) techniques. Here, we present the process of developing sub-metric resolution digital elevation models (DEMs) from these aerial photographs. By combining 16 DEMs, we produced a dataset of elevation changes of Glacier Noir and Glacier Blanc, including time-series analysis of lateral and longitudinal profiles, glacier hypsometry and mass balance variation. Our preliminary results indicate that Glacier Noir and Glacier Blanc have both thinned to a similar magnitude, ≤ 20 m, despite a 1 km retreat for Glacier Blanc and only 500 m for Glacier Noir. However, these elevation change reconstructions are hampered by large uncertainties, principally due to the lack of independent camera calibration on the historical imagery. Initial attempts using posteriori correction grids have proven to significantly increase the accuracy of these data. We will present some of the uncertainties and solutions linked to the use of SfM on such a large scale and on such an old dataset. This study demonstrates how SfM can be used to investigate long-term trends in environmental change, allowing glacier monitoring to be up-scaled. It also highlights the need for on-going validation of methods to increase the accuracy and precision of SfM in glaciology. This work is not only advancing our understanding of the role of the debris layer, but will also aid glacial geology more generally with, for example, detailed geomorphological analysis of proglacial terrain and Quaternary sciences with quick and accurate reconstruction of a glacial paleo-environment.

  5. Seismic Imaging of Sandbox Models

    NASA Astrophysics Data System (ADS)

    Buddensiek, M. L.; Krawczyk, C. M.; Kukowski, N.; Oncken, O.

    2009-04-01

    Analog sandbox simulations have been applied to study structural geological processes to provide qualitative and quantitative insights into the evolution of mountain belts and basins. These sandbox simulations provide either two-dimensional and dynamic or pseudo-three-dimensional and static information. To extend the dynamic simulations to three dimensions, we combine the analog sandbox simulation techniques with seismic physical modeling of these sandbox models. The long-term objective of this approach is to image seismic and seismological events of static and actively deforming 3D analog models. To achieve this objective, a small-scale seismic apparatus, composed of a water tank, a PC control unit including piezo-electric transducers, and a positioning system, was built for laboratory use. For the models, we use granular material such as sand and glass beads, so that the simulations can evolve dynamically. The granular models are required to be completely water saturated so that the sources and receivers are directly and well coupled to the propagating medium. Ultrasonic source frequencies (˜500 kHz) corresponding to wavelengths ˜5 times the grain diameter are necessary to be able to resolve small scale structures. In three experiments of different two-layer models, we show that (1) interfaces of layers of granular materials can be resolved depending on the interface preparation more than on the material itself. Secondly, we show that the dilation between the sand grains caused by a string that has been pulled through the grains, simulating a shear zone, causes a reflection that can be detected in the seismic data. In the third model, we perform a seismic reflection survey across a model that contains both the prepared interface and a shear zone, and apply 2D-seismic reflection processing to improve the resolution. Especially for more complex models, the clarity and penetration depth need to be improved to study the evolution of geological structures in dynamic

  6. Classification of Urban Feature from Unmanned Aerial Vehicle Images Using Gasvm Integration and Multi-Scale Segmentation

    NASA Astrophysics Data System (ADS)

    Modiri, M.; Salehabadi, A.; Mohebbi, M.; Hashemi, A. M.; Masumi, M.

    2015-12-01

    The use of UAV in the application of photogrammetry to obtain cover images and achieve the main objectives of the photogrammetric mapping has been a boom in the region. The images taken from REGGIOLO region in the province of, Italy Reggio -Emilia by UAV with non-metric camera Canon Ixus and with an average height of 139.42 meters were used to classify urban feature. Using the software provided SURE and cover images of the study area, to produce dense point cloud, DSM and Artvqvtv spatial resolution of 10 cm was prepared. DTM area using Adaptive TIN filtering algorithm was developed. NDSM area was prepared with using the difference between DSM and DTM and a separate features in the image stack. In order to extract features, using simultaneous occurrence matrix features mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation for each of the RGB band image was used Orthophoto area. Classes used to classify urban problems, including buildings, trees and tall vegetation, grass and vegetation short, paved road and is impervious surfaces. Class consists of impervious surfaces such as pavement conditions, the cement, the car, the roof is stored. In order to pixel-based classification and selection of optimal features of classification was GASVM pixel basis. In order to achieve the classification results with higher accuracy and spectral composition informations, texture, and shape conceptual image featureOrthophoto area was fencing. The segmentation of multi-scale segmentation method was used.it belonged class. Search results using the proposed classification of urban feature, suggests the suitability of this method of classification complications UAV is a city using images. The overall accuracy and kappa coefficient method proposed in this study, respectively, 47/93% and 84/91% was.

  7. Time synchronization of consumer cameras on Micro Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Rehak, M.; Skaloud, J.

    2017-01-01

    This article discusses the problem of time registration between navigation and imaging components on Micro Aerial Vehicles (MAVs). Accurate mapping with MAVs is gaining importance in applications such as corridor mapping, road and pipeline inspections or mapping of large areas with homogeneous surface structure, e.g. forests or agricultural fields. Therefore, accurate aerial control plays a major role in efficient reconstruction of the terrain and artifact-free ortophoto generation. A key prerequisite is correct time stamping of images in global time frame as the sensor exterior orientation changes rapidly and its determination by navigation sensors influence the mapping accuracy on the ground. A majority of MAVs is equipped with consumer-grade, non-metric cameras for which the precise time registration with navigation components is not trivial to realize and its performance not easy to assess. In this paper, we study the problematic of synchronization by implementing and evaluating spatio-temporal observation models of aerial control to estimate residual delay of the imaging sensor. Such modeling is possible through inclusion of additional velocity and angular rate observations into the adjustment. This moves the optimization problem from 3D to 4D. The benefit of this approach is verified on real mapping projects using a custom build MAV and an off-the-shelf camera.

  8. Collection and Analysis of Crowd Data with Aerial, Rooftop, and Ground Views

    DTIC Science & Technology

    2014-11-10

    and cost, as well as a brief description of the projects on which they were used. We have purchased aerial platforms, imaging systems, and flight...have purchased aerial platforms, imaging systems, and flight control systems and used them different projects that will be discussed in the following...servos Aerial Platform Long flight-time aerial paltform for imaging applications UavFactory Ltd $15,885.00 80W Onboard Generator upgrade Power

  9. Aerial radiation surveys

    SciTech Connect

    Jobst, J.

    1980-01-01

    A recent aerial radiation survey of the surroundings of the Vitro mill in Salt Lake City shows that uranium mill tailings have been removed to many locations outside their original boundary. To date, 52 remote sites have been discovered within a 100 square kilometer aerial survey perimeter surrounding the mill; 9 of these were discovered with the recent aerial survey map. Five additional sites, also discovered by aerial survey, contained uranium ore, milling equipment, or radioactive slag. Because of the success of this survey, plans are being made to extend the aerial survey program to other parts of the Salt Lake valley where diversions of Vitro tailings are also known to exist.

  10. Development of a biologically inspired multi-modal wing model for aerial-aquatic robotic vehicles through empirical and numerical modelling of the common guillemot, Uria aalge.

    PubMed

    Lock, Richard J; Vaidyanathan, Ravi; Burgess, Stuart C; Loveless, John

    2010-12-01

    The common guillemot, Uria aalge, a member of the auk family of seabirds, exhibits locomotive capabilities in both aerial and aquatic substrates. Simplistic forms of this ability have yet to be achieved by robotic vehicle designs and offer significant potential as inspiration for future concept designs. In this investigation, we initially investigate the power requirements of the guillemot associated with different modes of locomotion, empirically determining the saving associated with the retraction of the wing during aquatic operations. A numerical model of a morphing wing is then created to allow power requirements to be determined for different wing orientations, taking into account the complex kinematic and inertial dynamics associated with the motion. Validation of the numerical model is achieved by comparisons with the actual behaviour of the guillemot, which is done by considering specific mission tasks, where by the optimal solutions are found utilizing an evolutionary algorithm, which are found to be in close agreement with the biological case.

  11. Analysis of aerial multispectral imagery to assess water quality parameters of Mississippi water bodies

    NASA Astrophysics Data System (ADS)

    Irvin, Shane Adison

    The goal of this study was to demonstrate the application of aerial imagery as a tool in detecting water quality indicators in a three mile segment of Tibbee Creek in, Clay County, Mississippi. Water samples from 10 transects were collected per sampling date over two periods in 2010 and 2011. Temperature and dissolved oxygen (DO) were measured at each point, and water samples were tested for turbidity and total suspended solids (TSS). Relative reflectance was extracted from high resolution (0.5 meter) multispectral aerial images. A regression model was developed for turbidity and TSS as a function of values for specific sampling dates. The best model was used to predict turbidity and TSS using datasets outside the original model date. The development of an appropriate predictive model for water quality assessment based on the relative reflectance of aerial imagery is affected by the quality of imagery and time of sampling.

  12. Digital image mosaics of the nearshore coastal waters of selected areas on the Hawaiian Islands of Hawai‘i, Maui, Moloka‘i, and O‘ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

    USGS Publications Warehouse

    Chavez, P. S.; Isbrecht, JoAnn; Velasco, Miguel G.; Cochran, Susan

    2016-01-01

    The lack of geographic and thematic maps of coral reefs limits our understanding of reefs and our ability to assess change. The U.S. Geological Survey (USGS) has the capability to compile digital image mosaics that are useful for creating detailed map products. Image maps covering the shallow near-shore coastal waters have been produced for several of the main Hawaiian Islands, including Hawai‘i, Maui, Moloka‘i, and O‘ahu and are presented in JPEG2000 (.jp2) format. The digital-image mosaics were generated by first scanning historical aerial photographs. At the time, available satellite image resolutions were not acceptable and the aerial photographs used were the best option. The individually scanned digital images were tone-and color-matched and then digitally mosaicked together using spatial matching. Separately, black and white digital orthophoto quads (DOQs) or digital raster graphics (DRGs) of the same areas were merged with shaded-relief images generated from lidar bathymetry data. The resulting black and white images covering both near-shore coastal waters and on-land areas became the geometric ‘masters’ for the mosaics generated from the aerial photographs. The aerial-photograph mosaics were geometrically corrected to overlay the master data set by using hundreds of image-to-image geometric control points and ‘slaving’ the mosaic onto the master. The USGS has been investigating the use of remotely sensed image and spatial data to help map and study coral reef environments. Interpretation of these data is corroborated by extensive field mapping and correlation with field measured distribution and density of coral cover and other coral reef cover types. An immediate result of this effort was the generation of very-high spatial resolution georeferenced image maps of critical coral reef habitat areas being studied by the USGS and others.

  13. Statistical modeling of SAR images: a survey.

    PubMed

    Gao, Gui

    2010-01-01

    Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last.

  14. Improvement of erosion risk modelling using soil information derived from aerial Vis-NIR imagery

    NASA Astrophysics Data System (ADS)

    Ciampalini, Rossano; Raclot, Damien; Le Bissonnais, Yves

    2016-04-01

    The aim of this research is to test the benefit of the hyperspectral imagery in soil surface properties characterisation for soil erosion modelling purposes. The research area is the Lebna catchment located in the in the north of Tunisia (Cap Bon Region). Soil erosion is evaluated with the use of two different soil erosion models: PESERA (Pan-European Soil Erosion Risk Assessment already used for the soil erosion risk mapping for the European Union, Kirkby et al., 2008) and Mesales (Regional Modelling of Soil Erosion Risk developed by Le Bissonnais et al., 1998, 2002); for that, different sources for soil properties and derived parameters such as soil erodibility map and soil crusting map have been evaluated with use of four different supports: 1) IAO soil map (IAO, 2000), 2) Carte Agricole - CA - (Ministry of Agriculture, Tunisia), 3) Hyperspectral VIS-NIR map - HY - (Gomez et al., 2012; Ciampalini t al., 2012), and, 3) a here developed Hybrid map - CY - integrating information from Hyperspectral VIS-NIR and pedological maps. Results show that the data source has a high influence on the estimation of the parameters for both the models with a more evident sensitivity for Pesera. With regard to the classical pedological data, the VIS-NIR data clearly ameliorates the spatialization of the texture, then, the spatial detail of the results. Differences in the output using different maps are more important in Pesera model than in Mesales showing no-change ranges of about 15 to 41% and 53 to 67%, respectively.

  15. Reconnaissance mapping from aerial photographs

    NASA Technical Reports Server (NTRS)

    Weeden, H. A.; Bolling, N. B. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. Engineering soil and geology maps were successfully made from Pennsylvania aerial photographs taken at scales from 1:4,800 to 1:60,000. The procedure involved a detailed study of a stereoscopic model while evaluating landform, drainage, erosion, color or gray tones, tone and texture patterns, vegetation, and cultural or land use patterns.

  16. Dynamic modeling, simulation and control design of a parafoil-payload system for ship launched aerial delivery system (SLADS)

    NASA Astrophysics Data System (ADS)

    Puranik, Anand S.

    The objective of this research was to develop a high-fidelity dynamic model of a parafoil-payload system with respect to its application for the Ship Launched Aerial Delivery System (SLADS). SLADS is a concept in which cargo can be transfered from ship to shore using a parafoil-payload system. It is accomplished in two phases: An initial towing phase when the glider follows the towing vessel in a passive lift mode and an autonomous gliding phase when the system is guided to the desired point. While many previous researchers have analyzed the parafoil-payload system when it is released from another airborne vehicle, limited work has been done in the area of towing up the system from ground or sea. One of the main contributions of this research was the development of a nonlinear dynamic model of a towed parafoil-payload system. After performing an extensive literature review of the existing methods of modeling a parafoil-payload system, a five degree-of-freedom model was developed. The inertial and geometric properties of the system were investigated to predict accurate results in the simulation environment. Since extensive research has been done in determining the aerodynamic characteristics of a paraglider, an existing aerodynamic model was chosen to incorporate the effects of air flow around the flexible paraglider wing. During the towing phase, it is essential that the parafoil-payload system follow the line of the towing vessel path to prevent an unstable flight condition called 'lockout'. A detailed study of the causes of lockout, its mathematical representation and the flight conditions and the parameters related to lockout, constitute another contribution of this work. A linearized model of the parafoil-payload system was developed and used to analyze the stability of the system about equilibrium conditions. The relationship between the control surface inputs and the stability was investigated. In addition to stability of flight, one more important objective

  17. Multicriteria Cost Assessment and Logistics Modeling for Military Humanitarian Assistance and Disaster Relief Aerial Delivery Operations

    DTIC Science & Technology

    2015-03-01

    of Defense (DOD) may be called to respond to global disasters (hurricanes, earthquakes, tsunamis, flood, volcanic eruption , epidemic, fire, etc.) to...Model Implementation and Solutions 25 4.4 Sensitivity Analyses 31 5. Concluding Remarks 38 6. References 40 Appendix A. Screenshots of MCDA Framework 43...33 Fig. 8 Supply chain network design bi-criteria solution sets from

  18. Oblique Aerial Photography Tool for Building Inspection and Damage Assessment

    NASA Astrophysics Data System (ADS)

    Murtiyoso, A.; Remondino, F.; Rupnik, E.; Nex, F.; Grussenmeyer, P.

    2014-11-01

    Aerial photography has a long history of being employed for mapping purposes due to some of its main advantages, including large area imaging from above and minimization of field work. Since few years multi-camera aerial systems are becoming a practical sensor technology across a growing geospatial market, as complementary to the traditional vertical views. Multi-camera aerial systems capture not only the conventional nadir views, but also tilted images at the same time. In this paper, a particular use of such imagery in the field of building inspection as well as disaster assessment is addressed. The main idea is to inspect a building from four cardinal directions by using monoplotting functionalities. The developed application allows to measure building height and distances and to digitize man-made structures, creating 3D surfaces and building models. The realized GUI is capable of identifying a building from several oblique points of views, as well as calculates the approximate height of buildings, ground distances and basic vectorization. The geometric accuracy of the results remains a function of several parameters, namely image resolution, quality of available parameters (DEM, calibration and orientation values), user expertise and measuring capability.

  19. Building Information Modelling (BIM) and Unmanned Aerial Vehicle (UAV) technologies in infrastructure construction project management and delay and disruption analysis

    NASA Astrophysics Data System (ADS)

    Vacanas, Yiannis; Themistocleous, Kyriacos; Agapiou, Athos; Hadjimitsis, Diofantos

    2015-06-01

    Time in infrastructure construction projects has always been a fundamental issue as early as from the inception of a project, during the construction process and often after the completion and delivery. In a typical construction contract time related matters such as the completion date and possible delays are among the most important issues that are dealt with by the contract provisions. In the event of delay there are usually provisions for extension of time award to the contractor with possible reimbursement for the extra cost and expenses caused by this extension of time to the contract duration. In the case the contractor is not entitled to extension of time, the owner will be possibly entitled to amounts as compensation for the time prohibited from using his development. Even in the event of completion within the time agreed, under certain circumstances a contractor may have claims for reimbursement for extra costs incurred due to induced acceleration measures he had to take in order to mitigate disruption effects caused to the progress of the works by the owner or his representatives. Depending on the size of the project and the agreement amount, these reimbursement sums may be extremely high. Therefore innovative methods with the exploitation of new technologies for effective project management for the avoidance of delays, delay analysis and mitigation measures are essential; moreover, methods for collecting efficiently information during the construction process so that disputes regarding time are avoided or resolved in a quick and fair manner are required. This paper explores the state of art for existing use of Building Information Modelling (BIM) and Unmanned Aerial Vehicles (UAV) technologies in the construction industry in general. Moreover the paper considers the prospect of using BIM technology in conjunction with the use of UAV technology for efficient and accurate as-built data collection and illustration of the works progress during an

  20. A Good Image Model Eases Restoration

    DTIC Science & Technology

    2002-02-06

    algorithms, and various classical as well as unexpected new applications of the BV ( bounded variation ) image model, first introduced into image processing by Rudin, Osher, and Fatemi in 1992 Physica D, 60:259-268.

  1. Featured Image: Modeling Supernova Remnants

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-05-01

    This image shows a computer simulation of the hydrodynamics within a supernova remnant. The mixing between the outer layers (where color represents the log of density) is caused by turbulence from the Rayleigh-Taylor instability, an effect that arises when the expanding core gas of the supernova is accelerated into denser shell gas. The past standard for supernova-evolution simulations was to perform them in one dimension and then, in post-processing, manually smooth out regions that undergo Rayleigh-Taylor turbulence (an intrinsically multidimensional effect). But in a recent study, Paul Duffell (University of California, Berkeley) has explored how a 1D model could be used to reproduce the multidimensional dynamics that occur in turbulence from this instability. For more information, check out the paper below!CitationPaul C. Duffell 2016 ApJ 821 76. doi:10.3847/0004-637X/821/2/76

  2. Building population mapping with aerial imagery and GIS data

    NASA Astrophysics Data System (ADS)

    Ural, Serkan; Hussain, Ejaz; Shan, Jie

    2011-12-01

    Geospatial distribution of population at a scale of individual buildings is needed for analysis of people's interaction with their local socio-economic and physical environments. High resolution aerial images are capable of capturing urban complexities and considered as a potential source for mapping urban features at this fine scale. This paper studies population mapping for individual buildings by using aerial imagery and other geographic data. Building footprints and heights are first determined from aerial images, digital terrain and surface models. City zoning maps allow the classification of the buildings as residential and non-residential. The use of additional ancillary geographic data further filters residential utility buildings out of the residential area and identifies houses and apartments. In the final step, census block population, which is publicly available from the U.S. Census, is disaggregated and mapped to individual residential buildings. This paper proposes a modified building population mapping model that takes into account the effects of different types of residential buildings. Detailed steps are described that lead to the identification of residential buildings from imagery and other GIS data layers. Estimated building populations are evaluated per census block with reference to the known census records. This paper presents and evaluates the results of building population mapping in areas of West Lafayette, Lafayette, and Wea Township, all in the state of Indiana, USA.

  3. Converting aerial imagery to application maps

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the last couple of years in Agricultural Aviation and at the 2014 and 2015 NAAA conventions, we have written about and presented both single-camera and two-camera imaging systems for use on agricultural aircraft. Many aerial applicators have shown a great deal of interest in the imaging systems...

  4. Medical image segmentation by MDP model

    NASA Astrophysics Data System (ADS)

    Lu, Yisu; Chen, Wufan

    2011-11-01

    MDP (Dirichlet Process Mixtures) model is applied to segment medical images in this paper. Segmentation can been automatically done without initializing segmentation class numbers. The MDP model segmentation algorithm is used to segment natural images and MR (Magnetic Resonance) images in the paper. To demonstrate the accuracy of the MDP model segmentation algorithm, many compared experiments, such as EM (Expectation Maximization) image segmentation algorithm, K-means image segmentation algorithm and MRF (Markov Field) image segmentation algorithm, have been done to segment medical MR images. All the methods are also analyzed quantitatively by using DSC (Dice Similarity Coefficients). The experiments results show that DSC of MDP model segmentation algorithm of all slices exceed 90%, which show that the proposed method is robust and accurate.

  5. Looking for an old aerial photograph

    USGS Publications Warehouse

    ,

    1997-01-01

    Attempts to photograph the surface of the Earth date from the 1800's, when photographers attached cameras to balloons, kites, and even pigeons. Today, aerial photographs and satellite images are commonplace. The rate of acquiring aerial photographs and satellite images has increased rapidly in recent years. Views of the Earth obtained from aircraft or satellites have become valuable tools to Government resource planners and managers, land-use experts, environmentalists, engineers, scientists, and a wide variety of other users. Many people want historical aerial photographs for business or personal reasons. They may want to locate the boundaries of an old farm or a piece of family property. Or they may want a photograph as a record of changes in their neighborhood, or as a gift. The U.S. Geological Survey (USGS) maintains the Earth Science Information Centers (ESIC?s) to sell aerial photographs, remotely sensed images from satellites, a wide array of digital geographic and cartographic data, as well as the Bureau?s wellknown maps. Declassified photographs from early spy satellites were recently added to the ESIC offerings of historical images. Using the Aerial Photography Summary Record System database, ESIC researchers can help customers find imagery in the collections of other Federal agencies and, in some cases, those of private companies that specialize in esoteric products.

  6. Thermal Modeling and Analysis of the Hurricane Imaging Radiometer (HIRad)

    NASA Technical Reports Server (NTRS)

    Mauro, Stephanie

    2013-01-01

    The Hurricane Imaging Radiometer (HIRad) is a payload carried by an unmanned aerial vehicle (UAV) at altitudes up to 60,000 ft with the purpose of measuring ocean surface wind speeds and near ocean surface rain rates in hurricanes. The payload includes several components that must maintain steady temperatures throughout the flight. Minimizing the temperature drift of these components allows for accurate data collection and conclusions to be drawn concerning the behavior of hurricanes. HIRad has flown on several different UAVs over the past two years during the fall hurricane season. Based on the data from the 2011 flight, a Thermal Desktop model was created to simulate the payload and reproduce the temperatures. Using this model, recommendations were made to reduce the temperature drift through the use of heaters controlled by resistance temperature detector (RTD) sensors. The suggestions made were implemented for the 2012 hurricane season and further data was collected. The implementation of the heaters reduced the temperature drift for a portion of the flight, but after a period of time, the temperatures rose. With this new flight data, the thermal model was updated and correlated. Detailed analysis was conducted to determine a more effective way to reduce the temperature drift. The final recommendations made were to adjust the set temperatures of the heaters for 2013 flights and implement hardware changes for flights beyond 2013.

  7. Modeling and Analysis of the Hurricane Imaging Radiometer (HIRAD)

    NASA Technical Reports Server (NTRS)

    Mauro, Stephanie

    2013-01-01

    The Hurricane Imaging Radiometer (HIRad) is a payload carried by an unmanned aerial vehicle (UAV) at altitudes up to 60,000 ft with the purpose of measuring ocean surface wind speeds and near ocean surface rain rates in hurricanes. The payload includes several components that must maintain steady temperatures throughout the flight. Minimizing the temperature drift of these components allows for accurate data collection and conclusions to be drawn concerning the behavior of hurricanes. HIRad has flown on several different UAVs over the past two years during the fall hurricane season. Based on the data from the 2011 flight, a Thermal Desktop model was created to simulate the payload and reproduce the temperatures. Using this model, recommendations were made to reduce the temperature drift through the use of heaters controlled by resistance temperature detector (RTD) sensors. The suggestions made were implemented for the 2012 hurricane season and further data was collected. The implementation of the heaters reduced the temperature drift for a portion of the flight, but after a period of time, the temperatures rose. With this new flight data, the thermal model was updated and correlated. Detailed analysis was conducted to determine a more effective way to reduce the temperature drift. The final recommendations made were to adjust the set temperatures of the heaters for 2013 flights and implement hardware changes for flights beyond 2013.

  8. Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) from an Unmanned Aerial Vehicle (UAV): Results from the 2014 AROMAT campaign

    NASA Astrophysics Data System (ADS)

    Merlaud, Alexis; Tack, Frederik; Constantin, Daniel; Fayt, Caroline; Maes, Jeroen; Mingireanu, Florin; Mocanu, Ionut; Georgescu, Lucian; Van Roozendael, Michel

    2015-04-01

    The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is an instrument dedicated to atmospheric trace gas retrieval from an Unmanned Aerial Vehicle (UAV). The payload is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27x12x12 cm3, and 6 W. The custom-built 2.5 m flying wing UAV is electrically powered, has a typical airspeed of 100 km/h, and can operate at a maximum altitude of 3 km. Both the payload and the UAV were developed in the framework of a collaboration between the Belgian Institute for Space Aeronomy (BIRA-IASB) and the Dunarea de Jos University of Galati, Romania. We present here SWING-UAV test flights dedicated to NO2 measurements and performed in Romania on 10 and 11 September 2014, during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign. The UAV performed 5 flights in the vicinity of the large thermal power station of Turceni (44.67° N, 23.4° E). The UAV was operated in visual range during the campaign, up to 900 m AGL , downwind of the plant and crossing its exhaust plume. The spectra recorded on flight are analyzed with the Differential Optical Absorption Spectroscopy (DOAS) method. The retrieved NO2 Differential Slant Column Densities (DSCDs) are up to 1.5e17 molec/cm2 and reveal the horizontal gradients around the plant. The DSCDs are converted to vertical columns and compared with coincident car-based DOAS measurements. We also present the near-future perspective of the SWING-UAV observation system, which includes flights in 2015 above the Black Sea to quantify ship emissions, the addition of SO2 as a target species, and autopilot flights at higher altitudes to cover a typical satellite pixel extent (10x10 km2).

  9. Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) from an Unmanned Aerial Vehicle (UAV): status and perspectives

    NASA Astrophysics Data System (ADS)

    Merlaud, Alexis; Tack, Frederik; Constantin, Daniel-Eduard; Fayt, Caroline; Maes, Jeroen; Mingireanu, Florin; Mocanu, Ionut; Georgescu, Lucian; Van Roozendael, Michel

    2014-05-01

    The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is a recently developed instrument dedicated to trace gas measurements from Unmanned Aerial Vehicles (UAVs). The payload is based on a compact ultra-violet visible spectrometer and a scanning mirror. Its weight, size, and power consumption are respectively 920 g, 27x12x12 cm3, and 6 W. The custom-built UAV is an electrically powered flying wing and can reach an altitude of 3 km at a mean airspeed of 100 km/h. The whole flight can be preprogrammed and controlled by an autopilot. The spectra are analyzed using Differential Optical Absorption Spectroscopy (DOAS). One major objective is the mapping of NO2 columns at high spatial resolution allowing to subsample satellite measurements within the extent of a typical ground pixel. We present the preliminary results of two test flights of the SWING-UAV observation system in the vicinity of Galati, Romania (45.45°N, 28.05°E), performed on 11 May 2013 and 20 September 2013. Several atmospheric species are identified in the spectral range covered by the spectrometer (300-600 nm): NO2, water vapor, O4, and O3. From the measurements, the detection limit for NO2 is estimated to lie around 2 ppb. We investigate: (1) the georeferencing issues and the effective spatial resolution achievable with SWING-UAV from the instantaneous field of view and the plane dynamics (2) the main parameters influencing the air mass factors, and (3) the reproducibility of NO2 measurements over the same area during the second flight which included repeated transects. We also present the near-future (2014-2015) campaigns planned for the SWING-UAV observation system.

  10. A model for growth of a single fungal hypha based on well-mixed tanks in series: simulation of nutrient and vesicle transport in aerial reproductive hyphae.

    PubMed

    Balmant, Wellington; Sugai-Guérios, Maura Harumi; Coradin, Juliana Hey; Krieger, Nadia; Furigo Junior, Agenor; Mitchell, David Alexander

    2015-01-01

    Current models that describe the extension of fungal hyphae and development of a mycelium either do not describe the role of vesicles in hyphal extension or do not correctly describe the experimentally observed profile for distribution of vesicles along the hypha. The present work uses the n-tanks-in-series approach to develop a model for hyphal extension that describes the intracellular transport of nutrient to a sub-apical zone where vesicles are formed and then transported to the tip, where tip extension occurs. The model was calibrated using experimental data from the literature for the extension of reproductive aerial hyphae of three different fungi, and was able to describe different profiles involving acceleration and deceleration of the extension rate. A sensitivity analysis showed that the supply of nutrient to the sub-apical vesicle-producing zone is a key factor influencing the rate of extension of the hypha. Although this model was used to describe the extension of a single reproductive aerial hypha, the use of the n-tanks-in-series approach to representing the hypha means that the model has the flexibility to be extended to describe the growth of other types of hyphae and the branching of hyphae to form a complete mycelium.

  11. Automatic registration of aerial photographs and digitized maps

    NASA Astrophysics Data System (ADS)

    Li, S. Z.; Kittler, Josef; Petrou, Maria

    1993-06-01

    We have developed a method of matching and recognizing aerial road network images based on road network models. The input is a list of line segments of an image obtained from a preprocessing stage, which is usually fragmentary and contains extraneous noisy segments. The output is the correspondences between the image line segments and model line segments. We use attributed relational graphs (ARG) to describe images and models. An ARG consists of a set of nodes, each node representing a line segment, and attributed relations between nodes. The task of matching is to find the best correspondences between the image ARG and the model ARG. The correspondences are found using a relaxation labeling algorithm, which optimizes a criterion of similarity. The algorithm is capable of subgraph matching of an image road structure to a map road model covering an area 10 times larger than the area imaged by the sensor, provided that the image distortion due to perspective imaging geometry has been corrected during preprocessing stages. We present matching experiments and demonstrate the stability of the matching method to extraneous line segments, missing line segments, and errors in scaling.

  12. Model observers in medical imaging research.

    PubMed

    He, Xin; Park, Subok

    2013-10-04

    Model observers play an important role in the optimization and assessment of imaging devices. In this review paper, we first discuss the basic concepts of model observers, which include the mathematical foundations and psychophysical considerations in designing both optimal observers for optimizing imaging systems and anthropomorphic observers for modeling human observers. Second, we survey a few state-of-the-art computational techniques for estimating model observers and the principles of implementing these techniques. Finally, we review a few applications of model observers in medical imaging research.

  13. Monitoring and Assuring the Quality of Digital Aerial Data

    NASA Technical Reports Server (NTRS)

    Christopherson, Jon

    2007-01-01

    This viewgraph presentation explains the USGS plan for monitoring and assuring the quality of digital aerial data. The contents include: 1) History of USGS Aerial Imaging Involvement; 2) USGS Research and Results; 3) Outline of USGS Quality Assurance Plan; 4) Other areas of Interest; and 5) Summary

  14. Kite Aerial Photography (KAP) as a Tool for Field Teaching

    ERIC Educational Resources Information Center

    Sander, Lasse

    2014-01-01

    Kite aerial photography (KAP) is proposed as a creative tool for geography field teaching and as a medium to approach the complexity of readily available geodata. The method can be integrated as field experiment, surveying technique or group activity. The acquired aerial images can instantaneously be integrated in geographic information systems…

  15. CFD Simulation of Aerial Crop Spraying

    NASA Astrophysics Data System (ADS)

    Omar, Zamri; Qiang, Kua Yong; Mohd, Sofian; Rosly, Nurhayati

    2016-11-01

    Aerial crop spraying, also known as crop dusting, is made for aerial application of pesticides or fertilizer. An agricultural aircraft which is converted from an aircraft has been built to combine with the aerial crop spraying for the purpose. In recent years, many studies on the aerial crop spraying were conducted because aerial application is the most economical, large and rapid treatment for the crops. The main objective of this research is to study the airflow of aerial crop spraying system using Computational Fluid Dynamics. This paper is focus on the effect of aircraft speed and nozzle orientation on the distribution of spray droplet at a certain height. Successful and accurate of CFD simulation will improve the quality of spray during the real situation and reduce the spray drift. The spray characteristics and efficiency are determined from the calculated results of CFD. Turbulence Model (k-ɛ Model) is used for the airflow in the fluid domain to achieve a more accurate simulation. Furthermore, spray simulation is done by setting the Flat-fan Atomizer Model of Discrete Phase Model (DPM) at the nozzle exit. The interaction of spray from each flat-fan atomizer can also be observed from the simulation. The evaluation of this study is validation and grid dependency study using field data from industry.

  16. Ultramap v3 - a Revolution in Aerial Photogrammetry

    NASA Astrophysics Data System (ADS)

    Reitinger, B.; Sormann, M.; Zebedin, L.; Schachinger, B.; Hoefler, M.; Tomasi, R.; Lamperter, M.; Gruber, B.; Schiester, G.; Kobald, M.; Unger, M.; Klaus, A.; Bernoegger, S.; Karner, K.; Wiechert, A.; Ponticelli, M.; Gruber, M.

    2012-07-01

    In the last years, Microsoft has driven innovation in the aerial photogrammetry community. Besides the market leading camera technology, UltraMap has grown to an outstanding photogrammetric workflow system which enables users to effectively work with large digital aerial image blocks in a highly automated way. Best example is the project-based color balancing approach which automatically balances images to a homogeneous block. UltraMap V3 continues innovation, and offers a revolution in terms of ortho processing. A fully automated dense matching module strives for high precision digital surface models (DSMs) which are calculated either on CPUs or on GPUs using a distributed processing framework. By applying constrained filtering algorithms, a digital terrain model can be derived which in turn can be used for fully automated traditional ortho texturing. By having the knowledge about the underlying geometry, seamlines can be generated automatically by applying cost functions in order to minimize visual disturbing artifacts. By exploiting the generated DSM information, a DSMOrtho is created using the balanced input images. Again, seamlines are detected automatically resulting in an automatically balanced ortho mosaic. Interactive block-based radiometric adjustments lead to a high quality ortho product based on UltraCam imagery. UltraMap v3 is the first fully integrated and interactive solution for supporting UltraCam images at best in order to deliver DSM and ortho imagery.

  17. Image Reconstruction Using Analysis Model Prior

    PubMed Central

    Han, Yu; Du, Huiqian; Lam, Fan; Mei, Wenbo; Fang, Liping

    2016-01-01

    The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims. PMID:27379171

  18. Nonlocal Markovian models for image denoising

    NASA Astrophysics Data System (ADS)

    Salvadeo, Denis H. P.; Mascarenhas, Nelson D. A.; Levada, Alexandre L. M.

    2016-01-01

    Currently, the state-of-the art methods for image denoising are patch-based approaches. Redundant information present in nonlocal regions (patches) of the image is considered for better image modeling, resulting in an improved quality of filtering. In this respect, nonlocal Markov random field (MRF) models are proposed by redefining the energy functions of classical MRF models to adopt a nonlocal approach. With the new energy functions, the pairwise pixel interaction is weighted according to the similarities between the patches corresponding to each pair. Also, a maximum pseudolikelihood estimation of the spatial dependency parameter (β) for these models is presented here. For evaluating this proposal, these models are used as an a priori model in a maximum a posteriori estimation to denoise additive white Gaussian noise in images. Finally, results display a notable improvement in both quantitative and qualitative terms in comparison with the local MRFs.

  19. On Two-Dimensional ARMA Models for Image Analysis.

    DTIC Science & Technology

    1980-03-24

    2-D ARMA models for image analysis . Particular emphasis is placed on restoration of noisy images using 2-D ARMA models. Computer results are...is concluded that the models are very effective linear models for image analysis . (Author)

  20. Image Modeling and Enhancement via Structured Sparse Model Selection

    DTIC Science & Technology

    2010-01-01

    signal estimation is then calculated with the selected model. The model selection leads to a guaranteed near optimal denoising estimator. The degree...are adapted to the image of interest and are computed with a simple and fast procedure. State-of-the-art results are shown in image denoising ...deblurring, and inpainting. Index Terms— Model selection, structured sparsity, best basis, denoising , deblurring, inpainting 1. INTRODUCTION Image enhancement

  1. Image segmentation with a unified graphical model.

    PubMed

    Zhang, Lei; Ji, Qiang

    2010-08-01

    We propose a unified graphical model that can represent both the causal and noncausal relationships among random variables and apply it to the image segmentation problem. Specifically, we first propose to employ Conditional Random Field (CRF) to model the spatial relationships among image superpixel regions and their measurements. We then introduce a multilayer Bayesian Network (BN) to model the causal dependencies that naturally exist among different image entities, including image regions, edges, and vertices. The CRF model and the BN model are then systematically and seamlessly combined through the theories of Factor Graph to form a unified probabilistic graphical model that captures the complex relationships among different image entities. Using the unified graphical model, image segmentation can be performed through a principled probabilistic inference. Experimental results on the Weizmann horse data set, on the VOC2006 cow data set, and on the MSRC2 multiclass data set demonstrate that our approach achieves favorable results compared to state-of-the-art approaches as well as those that use either the BN model or CRF model alone.

  2. Robust image modeling technique with a bioluminescence image segmentation application

    NASA Astrophysics Data System (ADS)

    Zhong, Jianghong; Wang, Ruiping; Tian, Jie

    2009-02-01

    A robust pattern classifier algorithm for the variable symmetric plane model, where the driving noise is a mixture of a Gaussian and an outlier process, is developed. The veracity and high-speed performance of the pattern recognition algorithm is proved. Bioluminescence tomography (BLT) has recently gained wide acceptance in the field of in vivo small animal molecular imaging. So that it is very important for BLT to how to acquire the highprecision region of interest in a bioluminescence image (BLI) in order to decrease loss of the customers because of inaccuracy in quantitative analysis. An algorithm in the mode is developed to improve operation speed, which estimates parameters and original image intensity simultaneously from the noise corrupted image derived from the BLT optical hardware system. The focus pixel value is obtained from the symmetric plane according to a more realistic assumption for the noise sequence in the restored image. The size of neighborhood is adaptive and small. What's more, the classifier function is base on the statistic features. If the qualifications for the classifier are satisfied, the focus pixel intensity is setup as the largest value in the neighborhood.Otherwise, it will be zeros.Finally,pseudo-color is added up to the result of the bioluminescence segmented image. The whole process has been implemented in our 2D BLT optical system platform and the model is proved.

  3. Experience With Bayesian Image Based Surface Modeling

    NASA Technical Reports Server (NTRS)

    Stutz, John C.

    2005-01-01

    Bayesian surface modeling from images requires modeling both the surface and the image generation process, in order to optimize the models by comparing actual and generated images. Thus it differs greatly, both conceptually and in computational difficulty, from conventional stereo surface recovery techniques. But it offers the possibility of using any number of images, taken under quite different conditions, and by different instruments that provide independent and often complementary information, to generate a single surface model that fuses all available information. I describe an implemented system, with a brief introduction to the underlying mathematical models and the compromises made for computational efficiency. I describe successes and failures achieved on actual imagery, where we went wrong and what we did right, and how our approach could be improved. Lastly I discuss how the same approach can be extended to distinct types of instruments, to achieve true sensor fusion.

  4. Local histograms and image occlusion models

    PubMed Central

    Massar, Melody L.; Bhagavatula, Ramamurthy; Fickus, Matthew; Kovačević, Jelena

    2012-01-01

    The local histogram transform of an image is a data cube that consists of the histograms of the pixel values that lie within a fixed neighborhood of any given pixel location. Such transforms are useful in image processing applications such as classification and segmentation, especially when dealing with textures that can be distinguished by the distributions of their pixel intensities and colors. We, in particular, use them to identify and delineate biological tissues found in histology images obtained via digital microscopy. In this paper, we introduce a mathematical formalism that rigorously justifies the use of local histograms for such purposes. We begin by discussing how local histograms can be computed as systems of convolutions. We then introduce probabilistic image models that can emulate textures one routinely encounters in histology images. These models are rooted in the concept of image occlusion. A simple model may, for example, generate textures by randomly speckling opaque blobs of one color on top of blobs of another. Under certain conditions, we show that, on average, the local histograms of such model-generated-textures are convex combinations of more basic distributions. We further provide several methods for creating models that meet these conditions; the textures generated by some of these models resemble those found in histology images. Taken together, these results suggest that histology textures can be analyzed by decomposing their local histograms into more basic components. We conclude with a proof-of-concept segmentation-and-classification algorithm based on these ideas, supported by numerical experimentation. PMID:23543920

  5. Aerial Scene Recognition using Efficient Sparse Representation

    SciTech Connect

    Cheriyadat, Anil M

    2012-01-01

    Advanced scene recognition systems for processing large volumes of high-resolution aerial image data are in great demand today. However, automated scene recognition remains a challenging problem. Efficient encoding and representation of spatial and structural patterns in the imagery are key in developing automated scene recognition algorithms. We describe an image representation approach that uses simple and computationally efficient sparse code computation to generate accurate features capable of producing excellent classification performance using linear SVM kernels. Our method exploits unlabeled low-level image feature measurements to learn a set of basis vectors. We project the low-level features onto the basis vectors and use simple soft threshold activation function to derive the sparse features. The proposed technique generates sparse features at a significantly lower computational cost than other methods~\\cite{Yang10, newsam11}, yet it produces comparable or better classification accuracy. We apply our technique to high-resolution aerial image datasets to quantify the aerial scene classification performance. We demonstrate that the dense feature extraction and representation methods are highly effective for automatic large-facility detection on wide area high-resolution aerial imagery.

  6. "A" Is for Aerial Maps and Art

    ERIC Educational Resources Information Center

    Todd, Reese H.; Delahunty, Tina

    2007-01-01

    The technology of satellite imagery and remote sensing adds a new dimension to teaching and learning about maps with elementary school children. Just a click of the mouse brings into view some images of the world that could only be imagined a generation ago. Close-up aerial pictures of the school and neighborhood quickly catch the interest of…

  7. AERIAL METHODS OF EXPLORATION

    DTIC Science & Technology

    The development of photointerpretation techniques for identifying kimberlite pipes on aerial photographs is discussed. The geographic area considered is the Daldyn region, which lies in the zone of Northern Taiga of Yakutiya.

  8. RBA: Reduced Bundle Adjustment for oblique aerial photogrammetry

    NASA Astrophysics Data System (ADS)

    Sun, Yanbiao; Sun, Huabo; Yan, Lei; Fan, Shiyue; Chen, Rui

    2016-11-01

    This study proposes an efficient Bundle Adjustment (BA) model for oblique aerial photogrammetry to reduce the number of unknown parameters and the dimensions of a non-linear optimization problem. Instead of serving as independent exterior orientations, oblique camera poses are parameterized with nadir camera poses and constant relative poses between oblique and nadir cameras. New observation functions are created with image points as a function of the nadir pose and the relative pose parameters. With these observation functions, the problem of BA is defined as finding optimal unknown parameters by minimizing the total difference between estimated and observed image points. A Gauss-Newton optimization method is utilized to provide a solution for this least-square problem with a reduced normal equation, which plays a very critical role in the convergence and efficiency of BA. Compared with traditional BA methods, the number of unknown parameters and the dimension of the normal equations decrease, this approach dramatically reduces the computational complexity and memory cost especially for large-scale scenarios with a number of oblique images. Four synthetic datasets and a real dataset were used to check the validation and the accuracy of the proposed method. The accuracy of the proposed method is very close to that of the traditional BA method, but the efficiency can be significantly improved by the proposed method. For very large-scale scenarios, the proposed method can still address the limitation of memory and orientate all images captured by an oblique aerial multi-camera system.

  9. Modeling gated neutron images of THD capsules

    SciTech Connect

    Wilson, Douglas Carl; Grim, Gary P; Tregillis, Ian L; Wilke, Mark D; Morgan, George L; Loomis, Eric N; Wilde, Carl H; Oertel, John A; Fatherley, Valerie E; Clark, David D; Schmitt, Mark J; Merrill, Frank E; Wang, Tai - Sen F; Danly, Christopher R; Batha, Steven H; Patel, M; Sepke, S; Hatarik, R; Fittinghoff, D; Bower, D; Marinak, M; Munro, D; Moran, M; Hilko, R; Frank, M; Buckles, R

    2010-01-01

    Time gating a neutron detector 28m from a NIF implosion can produce images at different energies. The brighter image near 14 MeV reflects the size and symmetry of the capsule 'hot spot'. Scattered neutrons, {approx}9.5-13 MeV, reflect the size and symmetry of colder, denser fuel, but with only {approx}1-7% of the neutrons. The gated detector records both the scattered neutron image, and, to a good approximation, an attenuated copy of the primary image left by scintillator decay. By modeling the imaging system the energy band for the scattered neutron image (10-12 MeV) can be chosen, trading off the decayed primary image and the decrease of scattered image brightness with energy. Modeling light decay from EJ399, BC422, BCF99-55, Xylene, DPAC-30, and Liquid A leads to a preference from BCF99-55 for the first NIF detector, but DPAC 30 and Liquid A would be preferred if incorporated into a system. Measurement of the delayed light from the NIF scintillator using implosions at the Omega laser shows BCF99-55 to be a good choice for down-scattered imaging at 28m.

  10. 1. NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    1. NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA PATCH ISLAND. REMAINS OF SEA WALL VISIBLE IN FOREGROUND AND RIGHT OF IMAGE. - Fort Delaware, Sea Wall, Pea Patch Island, Delaware City, New Castle County, DE

  11. NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA PATCH ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA PATCH ISLAND. REMAINS OF SEA WALL VISIBLE IN FOREGROUND AND RIGHT OF IMAGE - Fort Delaware, Pea Patch Island, Delaware City, New Castle County, DE

  12. Combined aerial and ground technique for assessing structural heat loss

    NASA Astrophysics Data System (ADS)

    Snyder, William C.; Schott, John R.

    1994-03-01

    The results of a combined aerial and ground-based structural heat loss survey are presented. The aerial imagery was collected by a thermal IR line scanner. Enhanced quantitative analysis of the imagery gives the roof heat flow and insulation level. The ground images were collected by a video van and converted to still frames stored on a video disk. A computer based presentation system retrieves the images and other information indexed by street address for screening and dissemination to owners. We conclude that the combined aerial and ground survey effectively discriminates between well insulated and poorly insulated structures, and that such a survey is a cost-effective alternative to site audits.

  13. Observing snow cover using unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Spallek, Waldemar; Witek, Matylda; Niedzielski, Tomasz

    2016-04-01

    Snow cover is a key environmental variable that influences high flow events driven by snow-melt episodes. Estimates of snow extent (SE), snow depth (SD) and snow water equivalent (SWE) allow to approximate runoff caused by snow-melt episodes. These variables are purely spatial characteristics, and hence their pointwise measurements using terrestrial monitoring systems do not offer the comprehensive and fully-spatial information on water storage in snow. Existing satellite observations of snow reveal moderate spatial resolution which, not uncommonly, is not fine enough to estimate the above-mentioned snow-related variables for small catchments. High-resolution aerial photographs and the resulting orthophotomaps and digital surface models (DSMs), obtained using unmanned aerial vehicles (UAVs), may offer spatial resolution of 3 cm/px. The UAV-based observation of snow cover may be done using the near-infrared (NIR) cameras and visible-light cameras. Since the beginning of 2015, in frame of the research project no. LIDER/012/223/L-5/13/NCBR/2014 financed by the National Centre for Research and Development of Poland, we have performed a series of the UAV flights targeted at four sites in the Kwisa catchment in the Izerskie Mts. (part of the Sudetes, SW Poland). Observations are carried out with the ultralight UAV swinglet CAM (produced by senseFly, lightweight 0.5 kg, wingspan 80 cm) which enables on-demand sampling at low costs. The aim of the field work is to acquire aerial photographs taken using the visible-light and NIR cameras for a purpose of producing time series of DSMs and orthophotomaps with snow cover for all sites. The DSMs are used to calculate SD as difference between observational (with snow) and reference (without snow) models. In order to verify such an approach to compute SD we apply several procedures, one of which is the estimation of SE using the corresponding orthophotomaps generated on a basis of visual-light and NIR images. The objective of this

  14. Semi-Automatic Building Models and FAÇADE Texture Mapping from Mobile Phone Images

    NASA Astrophysics Data System (ADS)

    Jeong, J.; Kim, T.

    2016-06-01

    Research on 3D urban modelling has been actively carried out for a long time. Recently the need of 3D urban modelling research is increased rapidly due to improved geo-web services and popularized smart devices. Nowadays 3D urban models provided by, for example, Google Earth use aerial photos for 3D urban modelling but there are some limitations: immediate update for the change of building models is difficult, many buildings are without 3D model and texture, and large resources for maintaining and updating are inevitable. To resolve the limitations mentioned above, we propose a method for semi-automatic building modelling and façade texture mapping from mobile phone images and analyze the result of modelling with actual measurements. Our method consists of camera geometry estimation step, image matching step, and façade mapping step. Models generated from this method were compared with actual measurement value of real buildings. Ratios of edge length of models and measurements were compared. Result showed 5.8% average error of length ratio. Through this method, we could generate a simple building model with fine façade textures without expensive dedicated tools and dataset.

  15. The combined use of Building Information Modelling (BIM) and Unmanned Aerial Vehicle (UAV) technologies for the 3D illustration of the progress of works in infrastructure construction projects

    NASA Astrophysics Data System (ADS)

    Vacanas, Yiannis; Themistocleous, Kyriacos; Agapiou, Athos; Hadjimitsis, Diofantos

    2016-08-01

    Building Information Modelling (BIM) technology is already part of the construction industry and is considered by professionals as a very useful tool for all phases of a construction project. BIM technology, with the particularly useful 3D illustrations which it provides, can be used to illustrate and monitor the progress of works effectively through the entire lifetime of the project. Unmanned Aerial Vehicles (UAVs) have undergone significant advances in equipment capabilities and now have the capacity to acquire high resolution imagery from different angles in a cost effective and efficient manner. By using photogrammetry, characteristics such as distances, areas, volumes, elevations, object sizes, and object shape can be determined within overlapping areas. This paper explores the combined use of BIM and UAV technologies in order to achieve efficient and accurate as-built data collection and 3D illustrations of the works progress during an infrastructure construction project.

  16. Aerial Photography Summary Record System

    USGS Publications Warehouse

    ,

    1998-01-01

    The Aerial Photography Summary Record System (APSRS) describes aerial photography projects that meet specified criteria over a given geographic area of the United States and its territories. Aerial photographs are an important tool in cartography and a number of other professions. Land use planners, real estate developers, lawyers, environmental specialists, and many other professionals rely on detailed and timely aerial photographs. Until 1975, there was no systematic approach to locate an aerial photograph, or series of photographs, quickly and easily. In that year, the U.S. Geological Survey (USGS) inaugurated the APSRS, which has become a standard reference for users of aerial photographs.

  17. Efficiency of a model human image code

    NASA Technical Reports Server (NTRS)

    Watson, Andrew B.

    1987-01-01

    Hypothetical schemes for neural representation of visual information can be expressed as explicit image codes. Here, a code modeled on the simple cells of the primate striate cortex is explored. The Cortex transform maps a digital image into a set of subimages (layers) that are bandpass in spatial frequency and orientation. The layers are sampled so as to minimize the number of samples and still avoid aliasing. Samples are quantized in a manner that exploits the bandpass contrast-masking properties of human vision. The entropy of the samples is computed to provide a lower bound on the code size. Finally, the image is reconstructed from the code. Psychophysical methods are derived for comparing the original and reconstructed images to evaluate the sufficiency of the code. When each resolution is coded at the threshold for detection artifacts, the image-code size is about 1 bit/pixel.

  18. A Deep Generative Deconvolutional Image Model

    SciTech Connect

    Pu, Yunchen; Yuan, Xin; Stevens, Andrew J.; Li, Chunyuan; Carin, Lawrence

    2016-05-09

    A deep generative model is developed for representation and analysis of images, based on a hierarchical convolutional dictionary-learning framework. Stochastic unpooling is employed to link consecutive layers in the model, yielding top-down image generation. A Bayesian support vector machine is linked to the top-layer features, yielding max-margin discrimination. Deep deconvolutional inference is employed when testing, to infer the latent features, and the top-layer features are connected with the max-margin classifier for discrimination tasks. The model is efficiently trained using a Monte Carlo expectation-maximization (MCEM) algorithm; the algorithm is implemented on graphical processor units (GPU) to enable large-scale learning, and fast testing. Excellent results are obtained on several benchmark datasets, including ImageNet, demonstrating that the proposed model achieves results that are highly competitive with similarly sized convolutional neural networks.

  19. Multicopter-based small format aerial photography using free and open source photogrammetry

    NASA Astrophysics Data System (ADS)

    Davis, Robert Matthew

    A process is described to convert aerial photographs from flat images to 3D point clouds and then convert into height maps to be used as pseudo digital elevation models for surface modeling. All software used in the process is either free or open source. The process uses a DJI Phanton multicoper and two Canon Point and Shoot digital cameras. One camera is unaltered, and a second camera is modified to produce infrared images. A DJI Phantom FC-40 multicopter is used as the aerial platform to carry the cameras. Multiple paths are described to convert from still images (or video to still images) to N-view matches, followed by sparse point clouds then dense point clouds. Point clouds are distinct 3D points charted in an XYZ coordinate system. The dense point clouds can be converted into 3D models for viewing and analysis. A height map is extracted from the point cloud and surface images (in raster format) are created and then used in QGIS or ArcMap as pseudo digital elevation models for surface modeling. Finally, the digital elevation models are evaluated in comparison to similar LIDAR images. Keywords: Passive Remote Sensing; LIDAR; Spatial Resolution.

  20. Noise Modeling of SDO AIA Images

    NASA Astrophysics Data System (ADS)

    Kirk, M. S.; Young, C. A.

    2014-12-01

    All digital images are corrupted by noise. In most solar imaging, we have the luxury of high photon counts and low background contamination, which when combined with carful calibration, minimize much of the impact noise has on the measurement. Outside high-intensity regions, such as in coronal holes, the noise component can become significant and complicate feature recognition and segmentation. We create a practical estimate of noise in the AIA images across the detector CCD. A Poisson-Gaussian model of noise is well suited in the digital imaging environment due to the statistical distributions of photons and the characteristics of the CCD. Using the dark and flat field calibration images, the level-1 AIA images, and readout noise measurements, we construct a maximum-a-posteriori estimation of the expected error in the AIA images. These estimations of noise not only provide a clearer view of solar features in AIA, but they are also relevant to error characterizations of other solar images.

  1. Digital image watermarking using visual models

    NASA Astrophysics Data System (ADS)

    Podilchuk, Christine I.; Zeng, Wenjun

    1997-06-01

    The huge success of the Internet permits the transmission and wide distribution and access of electronic data in an effortless manner. Content providers are faced with the challenge of how to protect their electronic data. This problem has generated a flurry of recent research activity in the area of digital watermarking of electronic content for copyright protection. Unlike the traditional visible watermark found on paper, the challenge here is to introduce a digital watermark that does not alter the perceived quality of the electronic content while being extremely robust to attack. For instance, in the case of image data, editing the picture or illegal tampering should not destroy or alter the watermark. Equally important, the watermark should not alter the perceived visual quality of the image. From a signal processing viewpoint, the two basic requirements for an effective watermarking scheme, robustness and transparency, conflict with each other. We propose a watermarking technique for digital images that is based on utilizing visual models which have been developed in the context of image compression. Specifically, we propose a watermarking scheme where visual models are used to determine image dependent modulation masks for watermark insertion. In other words, for each image we can determine the maximum amount of watermark signal that each portion of the image can tolerate without affecting the visual quality of the image. This allow us to provide the maximum strength watermark which in turn, is extremely robust to common image processing and editing such as JPEG compression, rescaling, and cropping. We have watermarking results in a DCT framework as well as a wavelet framework. The DCT framework allows the direct insertion of watermarks to JPEG -- compressed data whereas the wavelet based scheme provides a framework where we can take advantage of both a local and global approach. Our scheme is shown to provide dramatic improvement over the current state

  2. Latent Dirichlet allocation models for image classification.

    PubMed

    Rasiwasia, Nikhil; Vasconcelos, Nuno

    2013-11-01

    Two new extensions of latent Dirichlet allocation (LDA), denoted topic-supervised LDA (ts-LDA) and class-specific-simplex LDA (css-LDA), are proposed for image classification. An analysis of the supervised LDA models currently used for this task shows that the impact of class information on the topics discovered by these models is very weak in general. This implies that the discovered topics are driven by general image regularities, rather than the semantic regularities of interest for classification. To address this, ts-LDA models are introduced which replace the automated topic discovery of LDA with specified topics, identical to the classes of interest for classification. While this results in improvements in classification accuracy over existing LDA models, it compromises the ability of LDA to discover unanticipated structure of interest. This limitation is addressed by the introduction of css-LDA, an LDA model with class supervision at the level of image features. In css-LDA topics are discovered per class, i.e., a single set of topics shared across classes is replaced by multiple class-specific topic sets. The css-LDA model is shown to combine the labeling strength of topic-supervision with the flexibility of topic-discovery. Its effectiveness is demonstrated through an extensive experimental evaluation, involving multiple benchmark datasets, where it is shown to outperform existing LDA-based image classification approaches.

  3. Inversion of the PROSAIL model to estimate leaf area index of maize, potato, and sunflower fields from unmanned aerial vehicle hyperspectral data

    NASA Astrophysics Data System (ADS)

    Duan, Si-Bo; Li, Zhao-Liang; Wu, Hua; Tang, Bo-Hui; Ma, Lingling; Zhao, Enyu; Li, Chuanrong

    2014-02-01

    Leaf area index (LAI) is a key variable for modeling energy and mass exchange between the land surface and the atmosphere. Inversion of physically based radiative transfer models is the most established technique for estimating LAI from remotely sensed data. This study aims to evaluate the suitability of the PROSAIL model for LAI estimation of three typical row crops (maize, potato, and sunflower) from unmanned aerial vehicle (UAV) hyperspectral data. LAI was estimated using a look-up table (LUT) based on the inversion of the PROSAIL model. The estimated LAI was evaluated against in situ LAI measurements. The results indicated that the LUT-based inversion of the PROSAIL model was suitable for LAI estimation of these three crops, with a root mean square error (RMSE) of approximately 0.62 m2 m-2, and a relative RMSE (RRMSE) of approximately 15.5%. Dual-angle observations were also used to estimate LAI and proved to be more accurate than single-angle observations, with an RMSE of approximately 0.55 m2 m-2 and an RRMSE of approximately 13.6%. The results demonstrate that additional directional information improves the performance of LAI estimation.

  4. Image based modeling of tumor growth.

    PubMed

    Meghdadi, N; Soltani, M; Niroomand-Oscuii, H; Ghalichi, F

    2016-09-01

    Tumors are a main cause of morbidity and mortality worldwide. Despite the efforts of the clinical and research communities, little has been achieved in the past decades in terms of improving the treatment of aggressive tumors. Understanding the underlying mechanism of tumor growth and evaluating the effects of different therapies are valuable steps in predicting the survival time and improving the patients' quality of life. Several studies have been devoted to tumor growth modeling at different levels to improve the clinical outcome by predicting the results of specific treatments. Recent studies have proposed patient-specific models using clinical data usually obtained from clinical images and evaluating the effects of various therapies. The aim of this review is to highlight the imaging role in tumor growth modeling and provide a worthwhile reference for biomedical and mathematical researchers with respect to tumor modeling using the clinical data to develop personalized models of tumor growth and evaluating the effect of different therapies.

  5. Aerial Explorers and Robotic Ecosystems

    NASA Technical Reports Server (NTRS)

    Young, Larry A.; Pisanich, Greg

    2004-01-01

    A unique bio-inspired approach to autonomous aerial vehicle, a.k.a. aerial explorer technology is discussed. The work is focused on defining and studying aerial explorer mission concepts, both as an individual robotic system and as a member of a small robotic "ecosystem." Members of this robotic ecosystem include the aerial explorer, air-deployed sensors and robotic symbiotes, and other assets such as rovers, landers, and orbiters.

  6. A new approach towards image based virtual 3D city modeling by using close range photogrammetry

    NASA Astrophysics Data System (ADS)

    Singh, S. P.; Jain, K.; Mandla, V. R.

    2014-05-01

    3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing day to day for various engineering and non-engineering applications. Generally three main image based approaches are using for virtual 3D city models generation. In first approach, researchers used Sketch based modeling, second method is Procedural grammar based modeling and third approach is Close range photogrammetry based modeling. Literature study shows that till date, there is no complete solution available to create complete 3D city model by using images. These image based methods also have limitations This paper gives a new approach towards image based virtual 3D city modeling by using close range photogrammetry. This approach is divided into three sections. First, data acquisition process, second is 3D data processing, and third is data combination process. In data acquisition process, a multi-camera setup developed and used for video recording of an area. Image frames created from video data. Minimum required and suitable video image frame selected for 3D processing. In second section, based on close range photogrammetric principles and computer vision techniques, 3D model of area created. In third section, this 3D model exported to adding and merging of other pieces of large area. Scaling and alignment of 3D model was done. After applying the texturing and rendering on this model, a final photo-realistic textured 3D model created. This 3D model transferred into walk-through model or in movie form. Most of the processing steps are automatic. So this method is cost effective and less laborious. Accuracy of this model is good. For this research work, study area is the campus of department of civil engineering, Indian Institute of Technology, Roorkee. This campus acts as a prototype for city. Aerial photography is restricted in many country

  7. Multilayer Markov Random Field models for change detection in optical remote sensing images

    NASA Astrophysics Data System (ADS)

    Benedek, Csaba; Shadaydeh, Maha; Kato, Zoltan; Szirányi, Tamás; Zerubia, Josiane

    2015-09-01

    In this paper, we give a comparative study on three Multilayer Markov Random Field (MRF) based solutions proposed for change detection in optical remote sensing images, called Multicue MRF, Conditional Mixed Markov model, and Fusion MRF. Our purposes are twofold. On one hand, we highlight the significance of the focused model family and we set them against various state-of-the-art approaches through a thematic analysis and quantitative tests. We discuss the advantages and drawbacks of class comparison vs. direct approaches, usage of training data, various targeted application fields and different ways of Ground Truth generation, meantime informing the Reader in which roles the Multilayer MRFs can be efficiently applied. On the other hand we also emphasize the differences between the three focused models at various levels, considering the model structures, feature extraction, layer interpretation, change concept definition, parameter tuning and performance. We provide qualitative and quantitative comparison results using principally a publicly available change detection database which contains aerial image pairs and Ground Truth change masks. We conclude that the discussed models are competitive against alternative state-of-the-art solutions, if one uses them as pre-processing filters in multitemporal optical image analysis. In addition, they cover together a large range of applications, considering the different usage options of the three approaches.

  8. Unmanned aerial survey of elephants.

    PubMed

    Vermeulen, Cédric; Lejeune, Philippe; Lisein, Jonathan; Sawadogo, Prosper; Bouché, Philippe

    2013-01-01

    The use of a UAS (Unmanned Aircraft System) was tested to survey large mammals in the Nazinga Game Ranch in the south of Burkina Faso. The Gatewing ×100™ equipped with a Ricoh GR III camera was used to test animal reaction as the UAS passed, and visibility on the images. No reaction was recorded as the UAS passed at a height of 100 m. Observations, made on a set of more than 7000 images, revealed that only elephants (Loxodonta africana) were easily visible while medium and small sized mammals were not. The easy observation of elephants allows experts to enumerate them on images acquired at a height of 100 m. We, therefore, implemented an aerial strip sample count along transects used for the annual wildlife foot count. A total of 34 elephants were recorded on 4 transects, each overflown twice. The elephant density was estimated at 2.47 elephants/km(2) with a coefficient of variation (CV%) of 36.10%. The main drawback of our UAS was its low autonomy (45 min). Increased endurance of small UAS is required to replace manned aircraft survey of large areas (about 1000 km of transect per day vs 40 km for our UAS). The monitoring strategy should be adapted according to the sampling plan. Also, the UAS is as expensive as a second-hand light aircraft. However the logistic and flight implementation are easier, the running costs are lower and its use is safer. Technological evolution will make civil UAS more efficient, allowing them to compete with light aircraft for aerial wildlife surveys.

  9. Unmanned Aerial Survey of Elephants

    PubMed Central

    Vermeulen, Cédric; Lejeune, Philippe; Lisein, Jonathan; Sawadogo, Prosper; Bouché, Philippe

    2013-01-01

    The use of a UAS (Unmanned Aircraft System) was tested to survey large mammals in the Nazinga Game Ranch in the south of Burkina Faso. The Gatewing ×100™ equipped with a Ricoh GR III camera was used to test animal reaction as the UAS passed, and visibility on the images. No reaction was recorded as the UAS passed at a height of 100 m. Observations, made on a set of more than 7000 images, revealed that only elephants (Loxodonta africana) were easily visible while medium and small sized mammals were not. The easy observation of elephants allows experts to enumerate them on images acquired at a height of 100 m. We, therefore, implemented an aerial strip sample count along transects used for the annual wildlife foot count. A total of 34 elephants were recorded on 4 transects, each overflown twice. The elephant density was estimated at 2.47 elephants/km2 with a coefficient of variation (CV%) of 36.10%. The main drawback of our UAS was its low autonomy (45 min). Increased endurance of small UAS is required to replace manned aircraft survey of large areas (about 1000 km of transect per day vs 40 km for our UAS). The monitoring strategy should be adapted according to the sampling plan. Also, the UAS is as expensive as a second-hand light aircraft. However the logistic and flight implementation are easier, the running costs are lower and its use is safer. Technological evolution will make civil UAS more efficient, allowing them to compete with light aircraft for aerial wildlife surveys. PMID:23405088

  10. Comparison of point clouds derived from aerial image matching with data from airborne laser scanning. (Polish Title: Porównanie wóaściwości chmury punktów wygenerowanej metodą dopasowania obrazów zdjęć lotniczych z danymi z lotniczego skanowania)

    NASA Astrophysics Data System (ADS)

    Dominik, W.

    2014-12-01

    The aim of this study was to investigate the properties of point clouds derived from aerial image matching and to compare them with point clouds from airborne laser scanning. A set of aerial images acquired in years 2010-2013 over the city of Elblag were used for the analysis. Images were acquired with the use of three digital cameras: DMC II 230, DMC I and DigiCAM60 with a GSD varying from 4.5 cm to 15 cm. Eight sets of images that were used in the study were acquired at different stages of the growing season - from March to December. Two LiDAR point clouds were used for the comparison - one with a density of 1.3 p/m2 and a second with a density of 10 p/m2. Based on the input images point clouds were created with the use of the semi-global matching method. The properties of the obtained point clouds were analyzed in three ways: - by the comparison of the vertical accuracy of point clouds with reference to a terrain profile surveyed on bare ground with GPS-RTK method - by visual assessment of point cloud profiles generated both from SGM and LiDAR point clouds - by visual assessment of a digital surface model generated from a SGM point cloud with reference to a digital surface model generated from a LiDAR point cloud. The conducted studies allowed a number of observations about the quality of SGM point clouds to be formulated with respect to different factors. The main factors having influence on the quality of SGM point clouds are GSD and base/height ratio. The essential problem related to SGM point clouds are areas covered with vegetation where SGM point clouds are visibly worse in terms of both accuracy and the representation of terrain surface. It is difficult to expect that in these areas SGM point clouds could replace LiDAR point clouds. This leads to a general conclusion that SGM point clouds are less reliable, more unpredictable and are dependent on more factors than LiDAR point clouds. Nevertheless, SGM point clouds generated with appropriate parameters can

  11. Processing of Uav Based Range Imaging Data to Generate Detailed Elevation Models of Complex Natural Structures

    NASA Astrophysics Data System (ADS)

    Kohoutek, T. K.; Eisenbeiss, H.

    2012-07-01

    Unmanned Aerial Vehicles (UAVs) are more and more used in civil areas like geomatics. Autonomous navigated platforms have a great flexibility in flying and manoeuvring in complex environments to collect remote sensing data. In contrast to standard technologies such as aerial manned platforms (airplanes and helicopters) UAVs are able to fly closer to the object and in small-scale areas of high-risk situations such as landslides, volcano and earthquake areas and floodplains. Thus, UAVs are sometimes the only practical alternative in areas where access is difficult and where no manned aircraft is available or even no flight permission is given. Furthermore, compared to terrestrial platforms, UAVs are not limited to specific view directions and could overcome occlusions from trees, houses and terrain structures. Equipped with image sensors and/or laser scanners they are able to provide elevation models, rectified images, textured 3D-models and maps. In this paper we will describe a UAV platform, which can carry a range imaging (RIM) camera including power supply and data storage for the detailed mapping and monitoring of complex structures, such as alpine riverbed areas. The UAV platform NEO from Swiss UAV was equipped with the RIM camera CamCube 2.0 by PMD Technologies GmbH to capture the surface structures. Its navigation system includes an autopilot. To validate the UAV-trajectory a 360° prism was installed and tracked by a total station. Within the paper a workflow for the processing of UAV-RIM data is proposed, which is based on the processing of differential GNSS data in combination with the acquired range images. Subsequently, the obtained results for the trajectory are compared and verified with a track of a UAV (Falcon 8, Ascending Technologies) carried out with a total station simultaneously to the GNSS data acquisition. The results showed that the UAV's position using differential GNSS could be determined in the centimetre to the decimetre level. The RIM

  12. A Spherical Aerial Terrestrial Robot

    NASA Astrophysics Data System (ADS)

    Dudley, Christopher J.

    This thesis focuses on the design of a novel, ultra-lightweight spherical aerial terrestrial robot (ATR). The ATR has the ability to fly through the air or roll on the ground, for applications that include search and rescue, mapping, surveillance, environmental sensing, and entertainment. The design centers around a micro-quadcopter encased in a lightweight spherical exoskeleton that can rotate about the quadcopter. The spherical exoskeleton offers agile ground locomotion while maintaining characteristics of a basic aerial robot in flying mode. A model of the system dynamics for both modes of locomotion is presented and utilized in simulations to generate potential trajectories for aerial and terrestrial locomotion. Details of the quadcopter and exoskeleton design and fabrication are discussed, including the robot's turning characteristic over ground and the spring-steel exoskeleton with carbon fiber axle. The capabilities of the ATR are experimentally tested and are in good agreement with model-simulated performance. An energy analysis is presented to validate the overall efficiency of the robot in both modes of locomotion. Experimentally-supported estimates show that the ATR can roll along the ground for over 12 minutes and cover the distance of 1.7 km, or it can fly for 4.82 minutes and travel 469 m, on a single 350 mAh battery. Compared to a traditional flying-only robot, the ATR traveling over the same distance in rolling mode is 2.63-times more efficient, and in flying mode the system is only 39 percent less efficient. Experimental results also demonstrate the ATR's transition from rolling to flying mode.

  13. Low Cost Surveying Using AN Unmanned Aerial Vehicle

    NASA Astrophysics Data System (ADS)

    Pérez, M.; Agüera, F.; Carvajal, F.

    2013-08-01

    Traditional manned airborne surveys are usually expensive and the resolution of the acquired images is often limited. The main advantage of Unmanned Aerial Vehicle (UAV) system acting as a photogrammetric sensor platform over more traditional manned airborne system is the high flexibility that allows image acquisition from unconventional viewpoints, the low cost in comparison with classical aerial photogrammetry and the high resolution images obtained. Nowadays there is a necessity for surveying small areas and in these cases, it is not economical the use of normal large format aerial or metric cameras to acquire aerial photos, therefore, the use of UAV platforms can be very suitable. Also the large availability of digital cameras has strongly enhanced the capabilities of UAVs. The use of digital non metric cameras together with the UAV could be used for multiple applications such as aerial surveys, GIS, wildfire mapping, stability of landslides, crop monitoring, etc. The aim of this work was to develop a low cost and accurate methodology in the production of orthophotos and Digital Elevation Models (DEM). The study was conducted in the province of Almeria, south of Spain. The photogrammetric flight had an altitude of 50 m over ground, covering an area of 5.000 m2 approximately. The UAV used in this work was the md4-200, which is an electronic battery powered quadrocopter UAV developed by Microdrones GmbH, Germany. It had on-board a Pextax Optio A40 digital non metric camera with 12 Megapixels. It features a 3x optical zoom lens with a focal range covering angles of view equivalent to those of 37-111 mm lens in 35 mm format. The quadrocopter can be programmed to follow a route defined by several waypoints and actions and it has the ability for vertical take off and landing. Proper flight geometry during image acquisition is essential in order to minimize the number of photographs, avoid areas without a good coverage and make the overlaps homogeneous. The flight

  14. Multiresolution ARMA modeling of facial color images

    NASA Astrophysics Data System (ADS)

    Celenk, Mehmet; Al-Jarrah, Inad

    2002-05-01

    Human face perception is the key to identify confirmation in security systems, video teleconference, picture telephony, and web navigation. Modeling of human faces and facial expressions for different persons can be dealt with by building a point distribution model (PDM) based on spatial (shape) information or a gray-level model (GLM) based on spectral (intensity) information. To avoid short-comings of the local modeling of PDM and GLM, we propose a new approach for recognizing human faces and discriminating expressions associated with them in color images. It is based on the Laplacian of Gaussian (LoG) edge detection, KL transformation, and auto-regressive moving average (ARMA) filtering. First, the KL transform is applied to the R, G, and B dimensions, and a facial image is described by its principal component. A LoG edge-detector is then used for line drawing schematic of a face. The resultant face silhouette is divided into 5 X 5 non-overlapping blocks, each of which is represented by the auto-regressive (AR) parameter vector a. The ensample average of a over the whole image is taken as the feature vector for the description of a facial pattern. Each face class is represented by such ensample average vector a. Efficacy of the ARMA model is evaluated by the non-metric similarity measure S equals a.b/a.b for two facial images whose feature vectors, and a and b, are the ensample average of their ARMA parameters. Our measurements show that the ARMA modeling is effective for discriminating facial features in color images, and has the potential of distinguishing the corresponding facial expressions.

  15. Aerial of the VAB

    NASA Technical Reports Server (NTRS)

    2000-01-01

    Even in this aerial view at KSC, the Vehicle Assembly Building is imposing. In front of it is the Launch Control Center. In the background is the Rotation/Processing Facility, next to the Banana Creek. In the foreground is the Saturn Causeway that leads to Launch Pads 39A and 39B.

  16. Aerial photographic reproductions

    USGS Publications Warehouse

    ,

    1971-01-01

    Geological Survey vertical aerial photography is obtained primarily for topographic and geologic mapping. Reproductions from this photography are usually satisfactory for general use. Because reproductions are not stocked, but are custom processed for each order, they cannot be returned for credit or refund.

  17. The Radar Image Generation (RIG) model

    NASA Technical Reports Server (NTRS)

    Stenger, Anthony J.

    1993-01-01

    RIG is a modeling system which creates synthetic aperture radar (SAR) and inverse SAR images from 3-D faceted data bases. RIG is based on a physical optics model and includes the effects of multiple reflections. Both conducting and dielectric surfaces can be modeled; each surface is labeled with a material code which is an index into a data base of electromagnetic properties. The inputs to the program include the radar processing parameters, the target orientation, the sensor velocity, and (for inverse SAR) the target angle rates. The current version of RIG can be run on any workstation, however, it is not a real-time model. We are considering several approaches to enable the program to generate realtime radar imagery. In addition to its image generation function, RIG can also generate radar cross-section (RCS) plots as well as range and doppler radar return profiles.

  18. Model of Image Artifacts from Dust Particles

    NASA Technical Reports Server (NTRS)

    Willson, Reg

    2008-01-01

    A mathematical model of image artifacts produced by dust particles on lenses has been derived. Machine-vision systems often have to work with camera lenses that become dusty during use. Dust particles on the front surface of a lens produce image artifacts that can potentially affect the performance of a machine-vision algorithm. The present model satisfies a need for a means of synthesizing dust image artifacts for testing machine-vision algorithms for robustness (or the lack thereof) in the presence of dust on lenses. A dust particle can absorb light or scatter light out of some pixels, thereby giving rise to a dark dust artifact. It can also scatter light into other pixels, thereby giving rise to a bright dust artifact. For the sake of simplicity, this model deals only with dark dust artifacts. The model effectively represents dark dust artifacts as an attenuation image consisting of an array of diffuse darkened spots centered at image locations corresponding to the locations of dust particles. The dust artifacts are computationally incorporated into a given test image by simply multiplying the brightness value of each pixel by a transmission factor that incorporates the factor of attenuation, by dust particles, of the light incident on that pixel. With respect to computation of the attenuation and transmission factors, the model is based on a first-order geometric (ray)-optics treatment of the shadows cast by dust particles on the image detector. In this model, the light collected by a pixel is deemed to be confined to a pair of cones defined by the location of the pixel s image in object space, the entrance pupil of the lens, and the location of the pixel in the image plane (see Figure 1). For simplicity, it is assumed that the size of a dust particle is somewhat less than the diameter, at the front surface of the lens, of any collection cone containing all or part of that dust particle. Under this assumption, the shape of any individual dust particle artifact

  19. Deep Reconstruction Models for Image Set Classification.

    PubMed

    Hayat, Munawar; Bennamoun, Mohammed; An, Senjian

    2015-04-01

    Image set classification finds its applications in a number of real-life scenarios such as classification from surveillance videos, multi-view camera networks and personal albums. Compared with single image based classification, it offers more promises and has therefore attracted significant research attention in recent years. Unlike many existing methods which assume images of a set to lie on a certain geometric surface, this paper introduces a deep learning framework which makes no such prior assumptions and can automatically discover the underlying geometric structure. Specifically, a Template Deep Reconstruction Model (TDRM) is defined whose parameters are initialized by performing unsupervised pre-training in a layer-wise fashion using Gaussian Restricted Boltzmann Machines (GRBMs). The initialized TDRM is then separately trained for images of each class and class-specific DRMs are learnt. Based on the minimum reconstruction errors from the learnt class-specific models, three different voting strategies are devised for classification. Extensive experiments are performed to demonstrate the efficacy of the proposed framework for the tasks of face and object recognition from image sets. Experimental results show that the proposed method consistently outperforms the existing state of the art methods.

  20. COCOA: tracking in aerial imagery

    NASA Astrophysics Data System (ADS)

    Ali, Saad; Shah, Mubarak

    2006-05-01

    Unmanned Aerial Vehicles (UAVs) are becoming a core intelligence asset for reconnaissance, surveillance and target tracking in urban and battlefield settings. In order to achieve the goal of automated tracking of objects in UAV videos we have developed a system called COCOA. It processes the video stream through number of stages. At first stage platform motion compensation is performed. Moving object detection is performed to detect the regions of interest from which object contours are extracted by performing a level set based segmentation. Finally blob based tracking is performed for each detected object. Global tracks are generated which are used for higher level processing. COCOA is customizable to different sensor resolutions and is capable of tracking targets as small as 100 pixels. It works seamlessly for both visible and thermal imaging modes. The system is implemented in Matlab and works in a batch mode.

  1. A study to analyze six band multispectral images and fabricate a Fourier transform detector. [optical data processing - aerial photography/forests

    NASA Technical Reports Server (NTRS)

    Shackelford, R. G.; Walsh, J. R., Jr.

    1975-01-01

    An automatic Fourier transform diffraction pattern sampling system, used to investigate techniques for forestry classification of six band multispectral aerial photography is presented. Photographs and diagrams of the design, development and fabrication of a hybrid optical-digital Fourier transform detector are shown. The detector was designed around a concentric ring fiber optic array. This array was formed from many optical fibers which were sorted into concentric rings about a single fiber. All the fibers in each ring were collected into a bundle and terminated into a single photodetector. An optical/digital interface unit consisting of a high level multiplexer, and an analog-to-digital amplifier was also constructed and is described.

  2. Image-based modelling of organogenesis.

    PubMed

    Iber, Dagmar; Karimaddini, Zahra; Ünal, Erkan

    2016-07-01

    One of the major challenges in biology concerns the integration of data across length and time scales into a consistent framework: how do macroscopic properties and functionalities arise from the molecular regulatory networks-and how can they change as a result of mutations? Morphogenesis provides an excellent model system to study how simple molecular networks robustly control complex processes on the macroscopic scale despite molecular noise, and how important functional variants can emerge from small genetic changes. Recent advancements in three-dimensional imaging technologies, computer algorithms and computer power now allow us to develop and analyse increasingly realistic models of biological control. Here, we present our pipeline for image-based modelling that includes the segmentation of images, the determination of displacement fields and the solution of systems of partial differential equations on the growing, embryonic domains. The development of suitable mathematical models, the data-based inference of parameter sets and the evaluation of competing models are still challenging, and current approaches are discussed.

  3. Kinetic modeling and optimization of maceration and ultrasound-extraction of resinoid from the aerial parts of white lady's bedstraw (Galium mollugo L.).

    PubMed

    Milić, Petar S; Rajković, Katarina M; Stamenković, Olivera S; Veljković, Vlada B

    2013-01-01

    In this paper, extraction of resinoid from the aerial parts of white lady's bedstraw (Galium mollugo L.) using an aqueous ethanol solution (50% by volume) was studied at different temperatures in the absence and the presence of ultrasound. This study indicated that ultrasound-assisted extraction was effective for extracting the resinoid and gave better resinoid yields at lower extraction temperature and in much shorter time than the maceration. A phenomenological model was developed for modeling the kinetics of the extraction process. The model successfully describes the two-step extraction consisting of washing followed by diffusion of extractable substances and shows that ultrasound influences only the first step. The extraction process was optimized using response surface methodology (RMS) and artificial neural network (ANN) models. For the former modeling, the second-order polynomial equation was applied, while the second one was performed by an ANN-GA combination. The high coefficient of determination and the low MRPD between the ANN prediction and the corresponding experimental data proved that modeling the extraction process in the absence and the presence of ultrasound using ANN was more accurate than RSM modeling. The optimum extraction temperature was determined to be 80 and 40 °C, respectively for the maceration and the ultrasound-assisted extraction, ensuring the highest resinoid yield of 22.0 g/100g in 4h and 25.1g/100g in 30 min, which agreed with the yields obtained experimentally for the same time (21.7 and 25.3g/100g, respectively).

  4. Detecting blind building façades from highly overlapping wide angle aerial imagery

    NASA Astrophysics Data System (ADS)

    Burochin, Jean-Pascal; Vallet, Bruno; Brédif, Mathieu; Mallet, Clément; Brosset, Thomas; Paparoditis, Nicolas

    2014-10-01

    This paper deals with the identification of blind building façades, i.e. façades which have no openings, in wide angle aerial images with a decimeter pixel size, acquired by nadir looking cameras. This blindness characterization is in general crucial for real estate estimation and has, at least in France, a particular importance on the evaluation of legal permission of constructing on a parcel due to local urban planning schemes. We assume that we have at our disposal an aerial survey with a relatively high stereo overlap along-track and across-track and a 3D city model of LoD 1, that can have been generated with the input images. The 3D model is textured with the aerial imagery by taking into account the 3D occlusions and by selecting for each façade the best available resolution texture seeing the whole façade. We then parse all 3D façades textures by looking for evidence of openings (windows or doors). This evidence is characterized by a comprehensive set of basic radiometric and geometrical features. The blindness prognostic is then elaborated through an (SVM) supervised classification. Despite the relatively low resolution of the images, we reach a classification accuracy of around 85% on decimeter resolution imagery with 60 × 40 % stereo overlap. On the one hand, we show that the results are very sensitive to the texturing resampling process and to vegetation presence on façade textures. On the other hand, the most relevant features for our classification framework are related to texture uniformity and horizontal aspect and to the maximal contrast of the opening detections. We conclude that standard aerial imagery used to build 3D city models can also be exploited to some extent and at no additional cost for facade blindness characterisation.

  5. BOREAS TE-17 Production Efficiency Model Images

    NASA Technical Reports Server (NTRS)

    Hall, Forrest G.; Papagno, Andrea (Editor); Goetz, Scott J.; Goward, Samual N.; Prince, Stephen D.; Czajkowski, Kevin; Dubayah, Ralph O.

    2000-01-01

    A Boreal Ecosystem-Atmospheric Study (BOREAS) version of the Global Production Efficiency Model (http://www.inform.umd.edu/glopem/) was developed by TE-17 (Terrestrial Ecology) to generate maps of gross and net primary production, autotrophic respiration, and light use efficiency for the BOREAS region. This document provides basic information on the model and how the maps were generated. The data generated by the model are stored in binary image-format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

  6. The application of GPS precise point positioning technology in aerial triangulation

    NASA Astrophysics Data System (ADS)

    Yuan, Xiuxiao; Fu, Jianhong; Sun, Hongxing; Toth, Charles

    In traditional GPS-supported aerotriangulation, differential GPS (DGPS) positioning technology is used to determine the 3-dimensional coordinates of the perspective centers at exposure time with an accuracy of centimeter to decimeter level. This method can significantly reduce the number of ground control points (GCPs). However, the establishment of GPS reference stations for DGPS positioning is not only labor-intensive and costly, but also increases the implementation difficulty of aerial photography. This paper proposes aerial triangulation supported with GPS precise point positioning (PPP) as a way to avoid the use of the GPS reference stations and simplify the work of aerial photography. Firstly, we present the algorithm for GPS PPP in aerial triangulation applications. Secondly, the error law of the coordinate of perspective centers determined using GPS PPP is analyzed. Thirdly, based on GPS PPP and aerial triangulation software self-developed by the authors, four sets of actual aerial images taken from surveying and mapping projects, different in both terrain and photographic scale, are given as experimental models. The four sets of actual data were taken over a flat region at a scale of 1:2500, a mountainous region at a scale of 1:3000, a high mountainous region at a scale of 1:32000 and an upland region at a scale of 1:60000 respectively. In these experiments, the GPS PPP results were compared with results obtained through DGPS positioning and traditional bundle block adjustment. In this way, the empirical positioning accuracy of GPS PPP in aerial triangulation can be estimated. Finally, the results of bundle block adjustment with airborne GPS controls from GPS PPP are analyzed in detail. The empirical results show that GPS PPP applied in aerial triangulation has a systematic error of half-meter level and a stochastic error within a few decimeters. However, if a suitable adjustment solution is adopted, the systematic error can be eliminated in GPS

  7. Sea Ice Mapping using Unmanned Aerial Systems

    NASA Astrophysics Data System (ADS)

    Solbø, S.; Storvold, R.

    2011-12-01

    Mapping of sea ice extent and sea ice features is an important task in climate research. Since the arctic coastal and oceanic areas have a high probability of cloud coverage, aerial platforms are superior to satellite measurements for high-resolution optical measurements. However, routine observations of sea ice conditions present a variety of problems using conventional piloted aircrafts. Specially, the availability of suitable aircrafts for lease does not cover the demand in major parts of the arctic. With the recent advances in unmanned aerial systems (UAS), there is a high possibility of establishing routine, cost effective aerial observations of sea ice conditions in the near future. Unmanned aerial systems can carry a wide variety of sensors useful for characterizing sea-ice features. For instance, the CryoWing UAS, a system initially designed for measurements of the cryosphere, can be equipped with digital cameras, surface thermometers and laser altimeters for measuring freeboard of ice flows. In this work we will present results from recent CryoWing sea ice flights on Svalbard, Norway. The emphasis will be on data processing for stitching together images acquired with the non-stabilized camera payload, to form high-resolution mosaics covering large spatial areas. These data are being employed to map ice conditions; including ice and lead features and melt ponds. These high-resolution mosaics are also well suited for sea-ice mechanics, classification studies and for validation of satellite sea-ice products.

  8. [Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

    PubMed

    Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

    2015-05-01

    This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

  9. Image Discrimination Models With Stochastic Channel Selection

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert J., Jr.; Beard, Bettina L.; Null, Cynthia H. (Technical Monitor)

    1995-01-01

    Many models of human image processing feature a large fixed number of channels representing cortical units varying in spatial position (visual field direction and eccentricity) and spatial frequency (radial frequency and orientation). The values of these parameters are usually sampled at fixed values selected to ensure adequate overlap considering the bandwidth and/or spread parameters, which are usually fixed. Even high levels of overlap does not always ensure that the performance of the model will vary smoothly with image translation or scale changes. Physiological measurements of bandwidth and/or spread parameters result in a broad distribution of estimated parameter values and the prediction of some psychophysical results are facilitated by the assumption that these parameters also take on a range of values. Selecting a sample of channels from a continuum of channels rather than using a fixed set can make model performance vary smoothly with changes in image position, scale, and orientation. It also facilitates the addition of spatial inhomogeneity, nonlinear feature channels, and focus of attention to channel models.

  10. Panoramic imaging perimeter sensor design and modeling

    SciTech Connect

    Pritchard, D.A.

    1993-12-31

    This paper describes the conceptual design and preliminary performance modeling of a 360-degree imaging sensor. This sensor combines automatic perimeter intrusion detection with immediate visual assessment and is intended to be used for fast deployment around fixed or temporary high-value assets. The sensor requirements, compiled from various government agencies, are summarized. The conceptual design includes longwave infrared and visible linear array technology. An auxiliary millimeter-wave sensing technology is also considered for use during periods of infrared and visible obscuration. The infrared detectors proposed for the sensor design are similar to the Standard Advanced Dewar Assembly Types Three A and B (SADA-IIIA/B). An overview of the sensor and processor is highlighted. The infrared performance of this sensor design has been predicted using existing thermal imaging system models and is described in the paper. Future plans for developing a prototype are also presented.

  11. Photogrammetric mapping using unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Graça, N.; Mitishita, E.; Gonçalves, J.

    2014-11-01

    Nowadays Unmanned Aerial Vehicle (UAV) technology has attracted attention for aerial photogrammetric mapping. The low cost and the feasibility to automatic flight along commanded waypoints can be considered as the main advantages of this technology in photogrammetric applications. Using GNSS/INS technologies the images are taken at the planned position of the exposure station and the exterior orientation parameters (position Xo, Yo, Zo and attitude ω, φ, χ) of images can be direct determined. However, common UAVs (off-the-shelf) do not replace the traditional aircraft platform. Overall, the main shortcomings are related to: difficulties to obtain the authorization to perform the flight in urban and rural areas, platform stability, safety flight, stability of the image block configuration, high number of the images and inaccuracies of the direct determination of the exterior orientation parameters of the images. In this paper are shown the obtained results from the project photogrammetric mapping using aerial images from the SIMEPAR UAV system. The PIPER J3 UAV Hydro aircraft was used. It has a micro pilot MP2128g. The system is fully integrated with 3-axis gyros/accelerometers, GPS, pressure altimeter, pressure airspeed sensors. A Sony Cyber-shot DSC-W300 was calibrated and used to get the image block. The flight height was close to 400 m, resulting GSD near to 0.10 m. The state of the art of the used technology, methodologies and the obtained results are shown and discussed. Finally advantages/shortcomings found in the study and main conclusions are presented

  12. Imaging black holes with sparse modeling

    NASA Astrophysics Data System (ADS)

    Honma, Mareki; Akiyama, Kazunori; Tazaki, Fumie; Kuramochi, Kazuki; Ikeda, Shiro; Hada, Kazuhiro; Uemura, Makoto

    2016-03-01

    We introduce a new imaging method for radio interferometry based on sparse- modeling. The direct observables in radio interferometry are visibilities, which are Fourier transformation of an astronomical image on the sky-plane, and incomplete sampling of visibilities in the spatial frequency domain results in an under-determined problem, which has been usually solved with 0 filling to un-sampled grids. In this paper we propose to directly solve this under-determined problem using sparse modeling without 0 filling, which realizes super resolution, i.e., resolution higher than the standard refraction limit. We show simulation results of sparse modeling for the Event Horizon Telescope (EHT) observations of super-massive black holes and demonstrate that our approach has significant merit in observations of black hole shadows expected to be realized in near future. We also present some results with the method applied to real data, and also discuss more advanced techniques for practical observations such as imaging with closure phase as well as treating the effect of interstellar scattering effect.

  13. Delineation of Nested Wetland Catchments and Modeling of Hydrologic Connectivity Using LiDAR Data and Aerial Imagery

    EPA Science Inventory

    In traditional watershed delineation and topographic modelling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In r...

  14. Unmanned aerial optical systems for spatial monitoring of Antarctic mosses

    NASA Astrophysics Data System (ADS)

    Lucieer, Arko; Turner, Darren; Veness, Tony; Malenovsky, Zbynek; Harwin, Stephen; Wallace, Luke; Kelcey, Josh; Robinson, Sharon

    2013-04-01

    The Antarctic continent has experienced major changes in temperature, wind speed and stratospheric ozone levels during the last 50 years. In a manner similar to tree rings, old growth shoots of Antarctic mosses, the only plants on the continent, also preserve a climate record of their surrounding environment. This makes them an ideal bio-indicator of the Antarctic climate change. Spatially extensive ground sampling of mosses is laborious and time limited due to the short Antarctic growing season. Obviously, there is a need for an efficient method to monitor spatially climate change induced stress of the Antarctic moss flora. Cloudy weather and high spatial fragmentation of the moss turfs makes satellite imagery unsuitable for this task. Unmanned aerial systems (UAS), flying at low altitudes and collecting image data even under a full overcast, can, however, overcome the insufficiency of satellite remote sensing. We, therefore, developed scientific UAS, consisting of a remote-controlled micro-copter carrying on-board different remote sensing optical sensors, tailored to perform fast and cost-effective mapping of Antarctic flora at ultra-high spatial resolution (1-10 cm depending on flight altitude). A single lens reflex (SLR) camera carried by UAS acquires multi-view aerial photography, which processed by the Structure from Motion computer vision algorithm provides an accurate three-dimensional digital surface model (DSM) at ultra-high spatial resolution. DSM is the key input parameter for modelling a local seasonal snowmelt run-off, which provides mosses with the vital water supply. A lightweight multispectral camera on-board of UVS is collecting images of six selected spectral wavebands with the full-width-half-maximum (FWHM) of 10 nm. The spectral bands can be used to compute various vegetation optical indices, e.g. Difference Vegetation Index (NDVI) or Photochemical Reflectance Index (PRI), assessing the actual physiological state of polar vegetation. Recently

  15. Personalized image retrieval with user's preference model

    NASA Astrophysics Data System (ADS)

    Kim, Yong-Hwan; Lee, K. E.; Choi, K. S.; Yoo, Ji-Beom; Rhee, Phill-Kyu; Park, Youngchoon

    1998-10-01

    Recently, available information resources in the form of various media have been increased with rapid speed. Many retrieval systems for multimedia information resources have been developed only focused on their efficiency and performance. Therefore, they cannot deal with user's preferences and interests well. In this paper, we present the framework design of a personalized image retrieval system (PIRS) which can reflect user's preferences and interests incrementally. The prototype of PIRS consists of two major parts: user's preference model (UPM) and retrieval module (RM). The UPM plays a role of refining user's query to meet with user's needs. The RM retrieves the proper images for refined query by computing the similarities between each image and refined query, and the retrieved images are ordered by these similarities. In this paper, we mainly discuss about UPM. The incremental machine learning technologies have been employed to provide the user adaptable and intelligent capability to the system. The UPM is implemented by decision tree based on incremental tree induction, and adaptive resonance theory network. User's feedbacks are returned to the UPM, and they modify internal structure of the UPM. User's iterative retrieval activities with PIRS cause the UPM to be revised for user's preferences and interests. Therefore, the PIRS can be adapted to user's preferences and interests. We have achieved encouraging results through experiments.

  16. Imaging and modeling new VETEM data

    USGS Publications Warehouse

    Wright, David L.; Smith, David V.; Abraham, Jared D.; Hutton, Raymond S.; Bond, E. Kent; Cui, Tie Jun; Aydiner, Alaeddin A.; Chew, Weng Cho

    2000-01-01

    In previously reported work (Wright and others, 2000) we found that the very early time electromagnetic (VETEM) prototype system produced data from which high resolution images of a buried former foundry site at the Denver Federal Center were made. The soil covering the site is about 30 mS/m conductivity, and is thus relatively unfavorable for ground penetrating radar (GPR) imaging. We have surveyed portions of this site again with new electric field dipole antennas and a new receiver designed for these antennas. Comparisons of the images produced using the loop antennas to those produced using the electric field dipole antennas illustrate that for this application the loop antennas produced more useful images. The larger man-made structures can be seen more clearly because they are not masked by dispersion and/or smaller scale variations as with the electric field dipole antennas. The VETEM system now contains an array of antennas with appropriate transmitters and receivers and can be operated as a low frequency time domain GPR or as a high frequency time domain electromagnetic (EM) system with several possible antenna spacings and polarizations. We plan to examine additional configurations. Numerical modeling of the perpendicular loop antenna configuration has been done and depth estimates produced. We conclude that, as with other GPR and time domain EM systems, the best choice of operating parameters depends on the application and the environment, but the inherent flexibility of the VETEM system allows a wide range of options.

  17. High Resolution Urban Land Cover Mapping Using NAIP Aerial Photography and Image Processing for the USEPA National Atlas of Sustainability and Ecosystem Services

    NASA Astrophysics Data System (ADS)

    Pilant, A. N.; Baynes, J.; Dannenberg, M.

    2012-12-01

    The US EPA National Atlas for Sustainability is a web-based, easy-to-use, mapping application that allows users to view and analyze multiple ecosystem services in a specific region. The Atlas provides users with a visual method for interpreting ecosystem services and understanding how they can be conserved and enhanced for a sustainable future. The Urban Atlas component of the National Atlas will provide fine-scale information linking human health and well-being to environmental conditions such as urban heat islands, near-road pollution, resource use, access to recreation, drinking water quality and other quality of life indicators. The National Land Cover Data (NLCD) derived from 30 m scale 2006 Landsat imagery provides the land cover base for the Atlas. However, urban features and phenomena occur at finer spatial scales, so higher spatial resolution and more current LC maps are required. We used 4 band USDA NAIP imagery (1 m pixel size) and various classification approaches to produce urban land cover maps with these classes: impervious surface, grass and herbaceous, trees and forest, soil and barren, and water. Here we present the remote sensing methods used and results from four pilot cities in this effort, highlighting the pros and cons of the approach, and the benefits to sustainability and ecosystem services analysis. Example of high resolution land cover map derived from USDA NAIP aerial photo. Compare 30 m and 1 m resolution land cover maps of downtown Durham, NC.

  18. Development of an aerial counting system in oil palm plantations

    NASA Astrophysics Data System (ADS)

    Zulyma Miserque Castillo, Jhany; Laverde Diaz, Rubbermaid; Rueda Guzmán, Claudia Leonor

    2016-07-01

    This paper proposes the development of a counting aerial system capable of capturing, process and analyzing images of an oil palm plantation to register the number of cultivated palms. It begins with a study of the available UAV technologies to define the most appropriate model according to the project needs. As result, a DJI Phantom 2 Vision+ is used to capture pictures that are processed by a photogrammetry software to create orthomosaics from the areas of interest, which are handled by the developed software to calculate the number of palms contained in them. The implemented algorithm uses a sliding window technique in image pyramids to generate candidate windows, an LBP descriptor to model the texture of the picture, a logistic regression model to classify the windows and a non-maximum suppression algorithm to refine the decision. The system was tested in different images than the ones used for training and for establishing the set point. As result, the system showed a 95.34% detection rate with a 97.83% precision in mature palms and a 79.26% detection rate with a 97.53% precision in young palms giving an FI score of 0.97 for mature palms and 0.87 for the small ones. The results are satisfactory getting the census and high-quality images from which is possible to get more information from the area of interest. All this, achieved through a low-cost system capable of work even in cloudy conditions.

  19. New variational image decomposition model for simultaneously denoising and segmenting optical coherence tomography images

    NASA Astrophysics Data System (ADS)

    Duan, Jinming; Tench, Christopher; Gottlob, Irene; Proudlock, Frank; Bai, Li

    2015-11-01

    Optical coherence tomography (OCT) imaging plays an important role in clinical diagnosis and monitoring of diseases of the human retina. Automated analysis of optical coherence tomography images is a challenging task as the images are inherently noisy. In this paper, a novel variational image decomposition model is proposed to decompose an OCT image into three components: the first component is the original image but with the noise completely removed; the second contains the set of edges representing the retinal layer boundaries present in the image; and the third is an image of noise, or in image decomposition terms, the texture, or oscillatory patterns of the original image. In addition, a fast Fourier transform based split Bregman algorithm is developed to improve computational efficiency of solving the proposed model. Extensive experiments are conducted on both synthesised and real OCT images to demonstrate that the proposed model outperforms the state-of-the-art speckle noise reduction methods and leads to accurate retinal layer segmentation.

  20. New variational image decomposition model for simultaneously denoising and segmenting optical coherence tomography images.

    PubMed

    Duan, Jinming; Tench, Christopher; Gottlob, Irene; Proudlock, Frank; Bai, Li

    2015-11-21

    Optical coherence tomography (OCT) imaging plays an important role in clinical diagnosis and monitoring of diseases of the human retina. Automated analysis of optical coherence tomography images is a challenging task as the images are inherently noisy. In this paper, a novel variational image decomposition model is proposed to decompose an OCT image into three components: the first component is the original image but with the noise completely removed; the second contains the set of edges representing the retinal layer boundaries present in the image; and the third is an image of noise, or in image decomposition terms, the texture, or oscillatory patterns of the original image. In addition, a fast Fourier transform based split Bregman algorithm is developed to improve computational efficiency of solving the proposed model. Extensive experiments are conducted on both synthesised and real OCT images to demonstrate that the proposed model outperforms the state-of-the-art speckle noise reduction methods and leads to accurate retinal layer segmentation.

  1. F/A-18 Automated Aerial Refueling (AAR) Phase 1

    NASA Video Gallery

    Engineers at NASA's Dryden Flight Research Center are evaluating the capability of an F/A-18A aircraft as an in-flight refueling tanker to develop analytical models for an automated aerial refuelin...

  2. Modeling and Imaging Flexural Plate Wave Devices

    SciTech Connect

    Adkins, D.R.; Butler, M.A.; Chu, A.S.; Schubert, W.K.

    1999-07-09

    Sandia National Laboratories is developing a new form of flexural plate wave device (FPW) for sensor applications. In this device, Lorentz forces cause out of plane vibrations in a silicon nitride membrane. Current induced in transducer lines on the membrane provides information about the amplitude and phase of these surface vibrations. By tracking the large amplitude vibrations that occur at resonant frequencies, it is possible to infer information about loading on the membrane. In fabricating FPWs, it is important to understand the impact that minor defects can have on operation. Through modeling and testing, they are developing resilient designs that provide large amplitude signals with a high tolerance to defects. A finite element model has been developed to perform design trade-off studies, and results from the model are being verified with a unique measurement system that can image Angstrom scale displacements at vibrational frequencies up to 800 kHz. Results from FPW modeling and imaging efforts are presented in this paper.

  3. Defense Science Board Study on Unmanned Aerial Vehicles and Uninhabited Combat Aerial Vehicles

    DTIC Science & Technology

    2004-02-01

    Defense Science Board Study on Unmanned Aerial Vehicles and Uninhabited Combat Aerial Vehicles February 2004 Office...COVERED - 4. TITLE AND SUBTITLE Defense Science Board Study on Unmanned Aerial Vehicles and Uninhabited Combat Aerial Vehicles 5a. CONTRACT...the Defense Science Board Task Force on Unmanned Aerial Vehicles and Uninhabited Combat Aerial Vehicles I am pleased to forward the final report of

  4. Aerial views of the San Andreas Fault

    USGS Publications Warehouse

    Moore, M.

    1988-01-01

    These aerial photographs of the San Andreas fault were taken in 1965 by Robert E. Wallace of the U.S Geological Survey. The pictures were taken with a Rolliflex camera on 20 format black and white flim; Wallace was aboard a light, fixed-wing aircraft, flying mostly at low altitudes. He photographed the fault from San Francisco near its north end where it enters by the Salton Sea. These images represent only a sampling of the more than 300 images prodcued during this project. All the photographs reside in the U.S Geological Survey Library in Menlo Park, California. 

  5. Locating buildings in aerial photos

    NASA Technical Reports Server (NTRS)

    Green, James S.

    1994-01-01

    Algorithms and techniques for use in the identification and location of large buildings in digitized copies of aerial photographs are developed and tested. The building data would be used in the simulation of objects located in the vicinity of an airport that may be detected by aircraft radar. Two distinct approaches are considered. Most building footprints are rectangular in form. The first approach studied is to search for right-angled corners that characterize rectangular objects and then to connect these corners to complete the building. This problem is difficult because many nonbuilding objects, such as street corners, parking lots, and ballparks often have well defined corners which are often difficult to distinguish from rooftops. Furthermore, rooftops come in a number of shapes, sizes, shadings, and textures which also limit the discrimination task. The strategy used linear sequences of different samples to detect straight edge segments at multiple angles and to determine when these segments meet at approximately right-angles with respect to each other. This technique is effective in locating corners. The test image used has a fairly rectangular block pattern oriented about thirty degrees clockwise from a vertical alignment, and the overall measurement data reflect this. However, this technique does not discriminate between buildings and other objects at an operationally suitable rate. In addition, since multiple paths are tested for each image pixel, this is a time consuming task. The process can be speeded up by preprocessing the image to locate the more optimal sampling paths. The second approach is to rely on a human operator to identify and select the building objects and then to have the computer determine the outline and location of the selected structures. When presented with a copy of a digitized aerial photograph, the operator uses a mouse and cursor to select a target building. After a button on the mouse is pressed, with the cursor fully within

  6. Aerial photography for sensing plant anomalies

    NASA Technical Reports Server (NTRS)

    Gausman, H. W.; Cardenas, R.; Hart, W. G.

    1970-01-01

    Changes in the red tonal response of Kodak Ektrachrome Infrared Aero 8443 film (EIR) are often incorrectly attributed solely to variations in infrared light reflectance of plant leaves, when the primary influence is a difference in visible light reflectance induced by varying chlorophyll contents. Comparisons are made among aerial photographic images of high- and low-chlorophyll foliage. New growth, foot rot, and boron and chloride nutrient toxicites produce low-chlorophyll foliage, and EIR transparency images of light red or white compared with dark-red images of high-chlorophyll foliage. Deposits of the sooty mold fungus that subsists on the honeydew produced by brown soft scale insects, obscure the citrus leaves' green color. Infected trees appear as black images on EIR film transparencies compared with red images of healthy trees.

  7. Ultrasonic measurement models for imaging with phased arrays

    NASA Astrophysics Data System (ADS)

    Schmerr, Lester W., Jr.; Engle, Brady J.; Sedov, Alexander; Li, Xiongbing

    2014-02-01

    Ultrasonic imaging measurement models (IMMs) are developed that generate images of flaws by inversion of ultrasonic measurement models. These IMMs are generalizations of the synthetic aperture focusing technique (SAFT) and the total focusing method (TFM). A special case when the flaw is small is shown to generalize physical optics far field inverse scattering (POFFIS) images. The ultrasonic IMMs provide a rational basis for generating and understanding the ultrasonic images produced by delay-and-sum imaging methods.

  8. Effective delineation of urban flooded areas based on aerial ortho-photo imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Ying; Guindon, Bert; Raymond, Don; Hong, Gang

    2016-10-01

    The combination of rapid global urban growth and climate change has resulted in increased occurrence of major urban flood events across the globe. The distribution of flooded area is one of the key information layers for applications of emergency planning and response management. While SAR systems and technologies have been widely used for flood area delineation, radar images suffer from range ambiguities arising from corner reflection effects and shadowing in dense urban settings. A new mapping framework is proposed for the extraction and quantification of flood extent based on aerial optical multi-spectral imagery and ancillary data. This involves first mapping of flood areas directly visible to the sensor. Subsequently, the complete area of submergence is estimated from this initial mapping and inference techniques based on baseline data such as land cover and GIS information such as available digital elevation models. The methodology has been tested and proven effective using aerial photography for the case of the 2013 flood in Calgary, Canada.

  9. A comparative study of four change detection methods for aerial photography applications

    NASA Astrophysics Data System (ADS)

    Abramovich, Gil; Brooksby, Glen; Bush, Stephen F.; Manickam, Swaminathan; Ozcanli, Ozge; Garrett, Benjamin D.

    2010-04-01

    We present four new change detection methods that create an automated change map from a probability map. In this case, the probability map was derived from a 3D model. The primary application of interest is aerial photographic applications, where the appearance, disappearance or change in position of small objects of a selectable class (e.g., cars) must be detected at a high success rate in spite of variations in magnification, lighting and background across the image. The methods rely on an earlier derivation of a probability map. We describe the theory of the four methods, namely Bernoulli variables, Markov Random Fields, connected change, and relaxation-based segmentation, evaluate and compare their performance experimentally on a set probability maps derived from aerial photographs.

  10. 2. AERIAL VIEW OF MINUTEMAN SILOS. Low oblique aerial view ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    2. AERIAL VIEW OF MINUTEMAN SILOS. Low oblique aerial view (original in color) of the two launch silos, covered. - Edwards Air Force Base, Air Force Rocket Propulsion Laboratory, Missile Silo Type, Test Area 1-100, northeast end of Test Area 1-100 Road, Boron, Kern County, CA

  11. Using aerial video to train the supervised classification of Landsat TM imagery for coral reef habitats mapping.

    PubMed

    Bello-Pineda, J; Liceaga-Correa, M A; Hernández-Núñez, H; Ponce-Hernández, R

    2005-06-01

    Management of coral reef resources is a challenging task, in many cases, because of the scarcity or inexistence of accurate sources of information and maps. Remote sensing is a not intrusive, but powerful tool, which has been successfully used for the assessment and mapping of natural resources in coral reef areas. In this study we utilized GIS to combine Landsat TM imagery, aerial photography, aerial video and a digital bathymetric model, to assess and to map submerged habitats for Alacranes reef, Yucatán, México. Our main goal was testing the potential of aerial video as the source of data to produce training areas for the supervised classification of Landsat TM imagery. Submerged habitats were ecologically characterized by using a hierarchical classification of field data. Habitats were identified on an overlaid image, consisting of the three types of remote sensing products and the bathymetric model. Pixels representing those habitats were selected as training areas by using GIS tools. Training areas were used to classify the Landsat TM bands 1, 2 and 3 and the bathymetric model by using a maximum likelihood algorithm. The resulting thematic map was compared against field data classification to improve habitats definition. Contextual editing and reclassification were used to obtain the final thematic map with an overall accuracy of 77%. Analysis of aerial video by a specialist in coral reef ecology was found to be a suitable source of information to produce training areas for the supervised classification of Landsat TM imagery in coral reefs at a coarse scale.

  12. Automatic Sea Bird Detection from High Resolution Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Mader, S.; Grenzdörffer, G. J.

    2016-06-01

    Great efforts are presently taken in the scientific community to develop computerized and (fully) automated image processing methods allowing for an efficient and automatic monitoring of sea birds and marine mammals in ever-growing amounts of aerial imagery. Currently the major part of the processing, however, is still conducted by especially trained professionals, visually examining the images and detecting and classifying the requested subjects. This is a very tedious task, particularly when the rate of void images regularly exceeds the mark of 90%. In the content of this contribution we will present our work aiming to support the processing of aerial images by modern methods from the field of image processing. We will especially focus on the combination of local, region-based feature detection and piecewise global image segmentation for automatic detection of different sea bird species. Large image dimensions resulting from the use of medium and large-format digital cameras in aerial surveys inhibit the applicability of image processing methods based on global operations. In order to efficiently handle those image sizes and to nevertheless take advantage of globally operating segmentation algorithms, we will describe the combined usage of a simple performant feature detector based on local operations on the original image with a complex global segmentation algorithm operating on extracted sub-images. The resulting exact segmentation of possible candidates then serves as a basis for the determination of feature vectors for subsequent elimination of false candidates and for classification tasks.

  13. Biophotonic Modelling of Cardiac Optical Imaging.

    PubMed

    Bishop, Martin J; Plank, Gernot

    2015-01-01

    Computational models have been recently applied to simulate and better understand the nature of fluorescent photon scattering and optical signal distortion during cardiac optical imaging. The goal of such models is both to provide a useful post-processing tool to facilitate a more accurate and faithful comparison between computational simulations of electrical activity and experiments, as well as providing essential insight into the mechanisms underlying this distortion, suggesting ways in which it may be controlled or indeed utilised to maximise the information derived from the recorded fluorescent signal. Here, we present different modelling methodologies developed and used in the field to simulate both the explicit processes involved in optical signal synthesis and the resulting consequences of the effects of photon scattering within the myocardium upon the optically-detected signal. We focus our attentions to two main types of modelling approaches used to simulate light transport in cardiac tissue, specifically continuous (reaction-diffusion) and discrete stochastic (Monte Carlo) methods. For each method, we provide both a summary of the necessary methodological details of such models, in addition to brief reviews of relevant application studies which have sought to apply these methods to elucidate important information regarding experimentally-recorded optical signals under different circumstances.

  14. Improving Measurement of Forest Structural Parameters by Co-Registering of High Resolution Aerial Imagery and Low Density LiDAR Data.

    PubMed

    Huang, Huabing; Gong, Peng; Cheng, Xiao; Clinton, Nick; Li, Zengyuan

    2009-01-01

    Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to generate a DEM (Digital Elevation Model) and a CHM (Canopy Height Model) from LiDAR data. The LiDAR camera image is matched to the aerial image with an automated keypoints search algorithm. As a result, a high registration accuracy of 0.5 pixels was obtained. A local maximum filter, watershed segmentation, and object-oriented image segmentation are used to obtain tree height and crown width. Results indicate that the camera data collected by the integrated LiDAR system plays an important role in registration with aerial imagery. The synthesis with aerial imagery increases the accuracy of forest structural parameter extraction when compared to only using the low density LiDAR data.

  15. Aerial thermography in archaeological prospection: Applications & processing

    NASA Astrophysics Data System (ADS)

    Cool, Autumn Chrysantha

    Aerial thermography is one of the least utilized archaeological prospection methods, yet it has great potential for detecting anthropogenic anomalies. Thermal infrared radiation is absorbed and reemitted at varying rates by all objects on and within the ground depending upon their density, composition, and moisture content. If an area containing archaeological features is recorded at the moment when their thermal signatures most strongly contrast with that of the surrounding matrix, they can be visually identified in thermal images. Research conducted in the 1960s and 1970s established a few basic rules for conducting thermal survey, but the expense associated with the method deterred most archaeologists from using this technology. Subsequent research was infrequent and almost exclusively appeared in the form of case studies. However, as the current proliferation of unmanned aerial vehicles (UAVs) and compact thermal cameras draws renewed attention to aerial thermography as an attractive and exciting form of survey, it is appropriate and necessary to reevaluate our approach. In this thesis I have taken a two-pronged approach. First, I built upon the groundwork of earlier researchers and created an experiment to explore the impact that different environmental and climatic conditions have on the success or failure of thermal imaging. I constructed a test site designed to mimic a range of archaeological features and imaged it under a variety of conditions to compare and contrast the results. Second, I explored a new method for processing thermal data that I hope will lead to a means of reducing noise and increasing the clarity of thermal images. This step was done as part of a case study so that the effectiveness of the processing method could be evaluated by comparison with the results of other geophysical surveys.

  16. Estimating snow depth in real time using unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Niedzielski, Tomasz; Mizinski, Bartlomiej; Witek, Matylda; Spallek, Waldemar; Szymanowski, Mariusz

    2016-04-01

    In frame of the project no. LIDER/012/223/L-5/13/NCBR/2014, financed by the National Centre for Research and Development of Poland, we elaborated a fully automated approach for estimating snow depth in real time in the field. The procedure uses oblique aerial photographs taken by the unmanned aerial vehicle (UAV). The geotagged images of snow-covered terrain are processed by the Structure-from-Motion (SfM) method which is used to produce a non-georeferenced dense point cloud. The workflow includes the enhanced RunSFM procedure (keypoint detection using the scale-invariant feature transform known as SIFT, image matching, bundling using the Bundler, executing the multi-view stereo PMVS and CMVS2 software) which is preceded by multicore image resizing. The dense point cloud is subsequently automatically georeferenced using the GRASS software, and the ground control points are borrowed from positions of image centres acquired from the UAV-mounted GPS receiver. Finally, the digital surface model (DSM) is produced which - to improve the accuracy of georeferencing - is shifted using a vector obtained through precise geodetic GPS observation of a single ground control point (GCP) placed on the Laboratory for Unmanned Observations of Earth (mobile lab established at the University of Wroclaw, Poland). The DSM includes snow cover and its difference with the corresponding snow-free DSM or digital terrain model (DTM), following the concept of the digital elevation model of differences (DOD), produces a map of snow depth. Since the final result depends on the snow-free model, two experiments are carried out. Firstly, we show the performance of the entire procedure when the snow-free model reveals a very high resolution (3 cm/px) and is produced using the UAV-taken photographs and the precise GCPs measured by the geodetic GPS receiver. Secondly, we perform a similar exercise but the 1-metre resolution light detection and ranging (LIDAR) DSM or DTM serves as the snow-free model

  17. 1:500 Scale Aerial Triangulation Test with Unmanned Airship in Hubei Province

    NASA Astrophysics Data System (ADS)

    Feifei, Xie; Zongjian, Lin; Dezhu, Gui

    2014-03-01

    A new UAVS (Unmanned Aerial Vehicle System) for low altitude aerial photogrammetry is introduced for fine surveying and mapping, including the platform airship, sensor system four-combined wide-angle camera and photogrammetry software MAP-AT. It is demonstrated that this low-altitude aerial photogrammetric system meets the precision requirements of 1:500 scale aerial triangulation based on the test of this system in Hubei province, including the working condition of the airship, the quality of image data and the data processing report. This work provides a possibility for fine surveying and mapping.

  18. The DOE ARM Aerial Facility

    SciTech Connect

    Schmid, Beat; Tomlinson, Jason M.; Hubbe, John M.; Comstock, Jennifer M.; Mei, Fan; Chand, Duli; Pekour, Mikhail S.; Kluzek, Celine D.; Andrews, Elisabeth; Biraud, S.; McFarquhar, Greg

    2014-05-01

    The Department of Energy Atmospheric Radiation Measurement (ARM) Program is a climate research user facility operating stationary ground sites that provide long-term measurements of climate relevant properties, mobile ground- and ship-based facilities to conduct shorter field campaigns (6-12 months), and the ARM Aerial Facility (AAF). The airborne observations acquired by the AAF enhance the surface-based ARM measurements by providing high-resolution in-situ measurements for process understanding, retrieval-algorithm development, and model evaluation that are not possible using ground- or satellite-based techniques. Several ARM aerial efforts were consolidated into the AAF in 2006. With the exception of a small aircraft used for routine measurements of aerosols and carbon cycle gases, AAF at the time had no dedicated aircraft and only a small number of instruments at its disposal. In this "virtual hangar" mode, AAF successfully carried out several missions contracting with organizations and investigators who provided their research aircraft and instrumentation. In 2009, AAF started managing operations of the Battelle-owned Gulfstream I (G-1) large twin-turboprop research aircraft. Furthermore, the American Recovery and Reinvestment Act of 2009 provided funding for the procurement of over twenty new instruments to be used aboard the G-1 and other AAF virtual-hangar aircraft. AAF now executes missions in the virtual- and real-hangar mode producing freely available datasets for studying aerosol, cloud, and radiative processes in the atmosphere. AAF is also engaged in the maturation and testing of newly developed airborne sensors to help foster the next generation of airborne instruments.

  19. Research on infrared imaging illumination model based on materials

    NASA Astrophysics Data System (ADS)

    Hu, Hai-he; Feng, Chao-yin; Guo, Chang-geng; Zheng, Hai-jing; Han, Qiang; Hu, Hai-yan

    2013-09-01

    In order to effectively simulate infrared features of the scene and infrared high light phenomenon, Based on the visual light illumination model, according to the optical property of all material types in the scene, the infrared imaging illumination models are proposed to fulfill different materials: to the smooth material with specular characteristic, adopting the infrared imaging illumination model based on Blinn-Phone reflection model and introducing the self emission; to the ordinary material which is similar to black body without highlight feature, ignoring the computation of its high light reflection feature, calculating simply the material's self emission and its reflection to the surrounding as its infrared imaging illumination model, the radiation energy under zero range of visibility can be obtained according to the above two models. The OpenGl rendering technology is used to construct infrared scene simulation system which can also simulate infrared electro-optical imaging system, then gets the synthetic infrared images from any angle of view of the 3D scenes. To validate the infrared imaging illumination model, two typical 3D scenes are made, and their infrared images are calculated to compare and contrast with the real collected infrared images obtained by a long wave infrared band imaging camera. There are two major points in the paper according to the experiment results: firstly, the infrared imaging illumination models are capable of producing infrared images which are very similar to those received by thermal infrared camera; secondly, the infrared imaging illumination models can simulate the infrared specular feature of relative materials and common infrared features of general materials, which shows the validation of the infrared imaging illumination models. Quantitative analysis shows that the simulation images are similar to the collected images in the aspects of main features, but their histogram distribution does not match very well, the

  20. Image Discrimination Models Predict Object Detection in Natural Backgrounds

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert J., Jr.; Rohaly, A. M.; Watson, Andrew B.; Null, Cynthia H. (Technical Monitor)

    1994-01-01

    Object detection involves looking for one of a large set of object sub-images in a large set of background images. Image discrimination models only predict the probability that an observer will detect a difference between two images. In a recent study based on only six different images, we found that discrimination models can predict the relative detectability of objects in those images, suggesting that these simpler models may be useful in some object detection applications. Here we replicate this result using a new, larger set of images. Fifteen images of a vehicle in an other-wise natural setting were altered to remove the vehicle and mixed with the original image in a proportion chosen to make the target neither perfectly recognizable nor unrecognizable. The target was also rotated about a vertical axis through its center and mixed with the background. Sixteen observers rated these 30 target images and the 15 background-only images for the presence of a vehicle. The likelihoods of the observer responses were computed from a Thurstone scaling model with the assumption that the detectabilities are proportional to the predictions of an image discrimination model. Three image discrimination models were used: a cortex transform model, a single channel model with a contrast sensitivity function filter, and the Root-Mean-Square (RMS) difference of the digital target and background-only images. As in the previous study, the cortex transform model performed best; the RMS difference predictor was second best; and last, but still a reasonable predictor, was the single channel model. Image discrimination models can predict the relative detectabilities of objects in natural backgrounds.

  1. Modeling and Retrieving Images by Content.

    ERIC Educational Resources Information Center

    Gudivada, Venkat N.; Raghavan, Vijay V.

    1997-01-01

    Discusses content-based image retrieval systems that effectively utilize information from image databases, and provides a taxonomy for approaches to image retrieval. Highlights include image retrieval architecture that supports query operators; conceptual issues; and two application prototypes. (100 references) (Author/LRW)

  2. Multi-temporal image analysis of historical aerial photographs and recent satellite imagery reveals evolution of water body surface area and polygonal terrain morphology in Kobuk Valley National Park, Alaska

    NASA Astrophysics Data System (ADS)

    Necsoiu, Marius; Dinwiddie, Cynthia L.; Walter, Gary R.; Larsen, Amy; Stothoff, Stuart A.

    2013-06-01

    Multi-temporal image analysis of very-high-resolution historical aerial and recent satellite imagery of the Ahnewetut Wetlands in Kobuk Valley National Park, Alaska, revealed the nature of thaw lake and polygonal terrain evolution over a 54-year period of record comprising two 27-year intervals (1951-1978, 1978-2005). Using active-contouring-based change detection, high-precision orthorectification and co-registration and the normalized difference index, surface area expansion and contraction of 22 shallow water bodies, ranging in size from 0.09 to 179 ha, and the transition of ice-wedge polygons from a low- to a high-centered morphology were quantified. Total surface area decreased by only 0.4% during the first time interval, but decreased by 5.5% during the second time interval. Twelve water bodies (ten lakes and two ponds) were relatively stable with net surface area decreases of ≤10%, including four lakes that gained area during both time intervals, whereas ten water bodies (five lakes and five ponds) had surface area losses in excess of 10%, including two ponds that drained completely. Polygonal terrain remained relatively stable during the first time interval, but transformation of polygons from low- to high-centered was significant during the second time interval.

  3. Observation of a Large Landslide on La Reunion Island Using Differential Sar Interferometry (JERS and Radarsat) and Correlation of Optical (Spot5 and Aerial) Images.

    PubMed

    Delacourt, Christophe; Raucoules, Daniel; Le Mouélic, Stéphane; Carnec, Claudie; Feurer, Denis; Allemand, Pascal; Cruchet, Marc

    2009-01-01

    Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean) is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its specific geological context. We show that remote sensing techniques (Differential SAR Interferometry and correlation of optical images) provide complementary means to characterize landslides on a regional scale. The vegetation cover generally hampers the analysis of C-band interferograms. We used JERS-1 images to show that the L-band can be used to overcome the loss of coherence observed in Radarsat C-band interferograms. Image correlation was applied to optical airborne and SPOT 5 sensors images. The two techniques were applied to a landslide near the town of Hellbourg in order to assess their performance for detecting and quantifying the ground motion associated to this landslide. They allowed the mapping of the unstable areas. Ground displacement of about 0.5 m yr(-1) was measured.

  4. Observation of a Large Landslide on La Reunion Island Using Differential Sar Interferometry (JERS and Radarsat) and Correlation of Optical (Spot5 and Aerial) Images

    PubMed Central

    Delacourt, Christophe; Raucoules, Daniel; Le Mouélic, Stéphane; Carnec, Claudie; Feurer, Denis; Allemand, Pascal; Cruchet, Marc

    2009-01-01

    Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean) is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its specific geological context. We show that remote sensing techniques (Differential SAR Interferometry and correlation of optical images) provide complementary means to characterize landslides on a regional scale. The vegetation cover generally hampers the analysis of C–band interferograms. We used JERS-1 images to show that the L-band can be used to overcome the loss of coherence observed in Radarsat C-band interferograms. Image correlation was applied to optical airborne and SPOT 5 sensors images. The two techniques were applied to a landslide near the town of Hellbourg in order to assess their performance for detecting and quantifying the ground motion associated to this landslide. They allowed the mapping of the unstable areas. Ground displacement of about 0.5 m yr-1 was measured. PMID:22389620

  5. The Aeronautics Education, Research, and Industry Alliance (AERIAL) 2002 Report

    NASA Technical Reports Server (NTRS)

    Bowen, Brent D.; Fink, Mary M.; Nickerson, Jocelyn S.

    2002-01-01

    This report presents and overview of the Aeronautics Education, Research, and Industry Alliance (AERIAL). It covers the University of Nebraska's areas of research, and its outreach to students at Native American schools as part of AERIAL. The report contains three papers: "Airborne Remote Sensing (ARS) for Agricultural Research and Commercialization Application" (White Paper), "Validated Numerical Models for the Convective Extinction of Fuel Droplets (CEFD)", and "The Small Aircraft Transportation System (SATS): Research Collaborations with the NASA Langley Research Center".

  6. Observing river stages using unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Niedzielski, Tomasz; Witek, Matylda; Spallek, Waldemar

    2016-08-01

    We elaborated a new method for observing water surface areas and river stages using unmanned aerial vehicles (UAVs). It is based on processing multitemporal five orthophotomaps produced from the UAV-taken visible light images of nine sites of the river, acquired with a sufficient overlap in each part. Water surface areas are calculated in the first place, and subsequently expressed as fractions of total areas of water-covered terrain at a given site of the river recorded on five dates. The logarithms of the fractions are later calculated, producing five samples, each consisted of nine elements. In order to detect statistically significant increments of water surface areas between two orthophotomaps, we apply the asymptotic and bootstrapped versions of the Student's t test, preceded by other tests that aim to check model assumptions. The procedure is applied to five orthophotomaps covering nine sites of the Ścinawka river (south-western (SW) Poland). The data have been acquired during the experimental campaign, at which flight settings were kept unchanged over nearly 3 years (2012-2014). We have found that it is possible to detect transitions between water surface areas associated with all characteristic water levels (low, mean, intermediate and high stages). In addition, we infer that the identified transitions hold for characteristic river stages as well. In the experiment we detected all increments of water level: (1) from low stages to mean, intermediate and high stages; (2) from mean stages to intermediate and high stages; and (3) from intermediate stages to high stages. Potential applications of the elaborated method include verification of hydrodynamic models and the associated predictions of high flows as well as monitoring water levels of rivers in ungauged basins.

  7. A NASA F/A-18, participating in the Automated Aerial Refueling (AAR) project, flies over the Dryden

    NASA Technical Reports Server (NTRS)

    2002-01-01

    A NASA F/A-18 is participating in the Automated Aerial Refueling (AAR) project. The 300-gallon aerial refueling store seen on the belly of the aircraft carries fuel and a refueling drogue. This aircraft acts as a tanker in the study to develop an aerodynamic model for future automated aerial refueling, especially of unmanned vehicles.

  8. Robust crack detection for unmanned aerial vehicles inspection in an a-contrario decision framework

    NASA Astrophysics Data System (ADS)

    Aldea, Emanuel; Le Hégarat-Mascle, Sylvie

    2015-11-01

    We are interested in the performance of currently available algorithms for the detection of cracks in the specific context of aerial inspection, which is characterized by image quality degradation. We focus on two widely used families of algorithms based on minimal cost path analysis and on image percolation, and we highlight their limitations in this context. Furthermore, we propose an improved strategy based on a-contrario modeling which is able to withstand significant motion blur due to the absence of various thresholds which are usually required in order to cope with varying crack appearances and with varying levels of degradation. The experiments are performed on real image datasets to which we applied complex blur, and the results show that the proposed strategy is effective, while other methods which perform well on good quality data experience significant difficulties with degraded images.

  9. On the Performance of Stochastic Model-Based Image Segmentation

    NASA Astrophysics Data System (ADS)

    Lei, Tianhu; Sewchand, Wilfred

    1989-11-01

    A new stochastic model-based image segmentation technique for X-ray CT image has been developed and has been extended to the more general nondiffraction CT images which include MRI, SPELT, and certain type of ultrasound images [1,2]. The nondiffraction CT image is modeled by a Finite Normal Mixture. The technique utilizes the information theoretic criterion to detect the number of the region images, uses the Expectation-Maximization algorithm to estimate the parameters of the image, and uses the Bayesian classifier to segment the observed image. How does this technique over/under-estimate the number of the region images? What is the probability of errors in the segmentation of this technique? This paper addresses these two problems and is a continuation of [1,2].

  10. Aerial thermography for energy conservation

    NASA Technical Reports Server (NTRS)

    Jack, J. R.

    1978-01-01

    Thermal infrared scanning from an aircraft is a convenient and commercially available means for determining relative rates of energy loss from building roofs. The need to conserve energy as fuel costs makes the mass survey capability of aerial thermography an attractive adjunct to community energy awareness programs. Background information on principles of aerial thermography is presented. Thermal infrared scanning systems, flight and environmental requirements for data acquisition, preparation of thermographs for display, major users and suppliers of thermography, and suggested specifications for obtaining aerial scanning services were reviewed.

  11. Aerial Photogrammetric Analysis of a Scree Slope and Cliff

    NASA Astrophysics Data System (ADS)

    Saunders, Greg; Galland, Olivier; Mair, Karen

    2014-05-01

    Mapping the physical features of landslide tracks provides information about factors controlling landslide movement. The increasing availability of unmanned aerial vehicles (UAV) provides the opportunity to efficiently and cost effectively map terrain. The main goal of this field study is to create a streamlined work-flow from acquisition to interpretation for the photogrammetric analysis of landslide tracks. Here an open source software package MicMac is used for ortho-image and point-cloud creation. A series of two flights were conducted over a scree (rockfall) slope in Kolsas, Norway. The slope runs roughly 500 m north-south with a maximum width of 60 m. A cliff to the west is the source area for the scree. The cliff consists of conglomerate, basalt, and porphyry from bottom to top respectively. The grain size of boulders in the scree slope apparently varies due to lateral differences in the cliff composition. The flights were completed under cloud cover and consisted of multiple lengthwise passes over the scree field. There was a minimum of 75% overlap between images. During the first flight the altitude was roughly 100 m, the camera was positioned normal to the scree (60 degrees from horizontal), and the resolution was 2.7 cm per pixel. The second flight had an altitude of 200 m, the camera orientation was 30 degrees from horizontal, and the resolution was 4.0 cm per pixel. Using the Micmac engine, Ortho-photos and Digital Elevation Models (DEM) were created for both the scree and the cliff. This data will allow for analysis of grain-size, surface roughness, grain-shape, fracture plane orientation, as well as geological mapping. Further work will focus the quantitative assessment of the significance different camera altitudes and angles have on the results. The work-flow used in this study provides a repeatable method for aerial photogrammetric surveys of scree slopes.

  12. Best practices for radiometric modeling of imaging spectrometers

    NASA Astrophysics Data System (ADS)

    Zellinger, Lou; Silny, John F.

    2015-09-01

    This paper provides best practices for the radiometric performance modeling of imaging spectrometers. A set of standard terminology is proposed to use when modeling imaging spectrometers. The calculation of various radiometric sensitivity metrics and their contrast counterparts are outlined. Modeling approaches are described for both solar reflected and thermally emitted bands. Finally, this approach is applied to an example hyperspectral sensor.

  13. Modeling interaction for image-guided procedures

    NASA Astrophysics Data System (ADS)

    Trevisan, Daniela G.; Vanderdonckt, Jean; Macq, Benoit M. M.; Raftopoulos, Christian

    2003-05-01

    Compared to conventional interfaces, image guided surgery (IGS) interfaces contain a richer variety and more complex objects and interaction types. The main interactive characteristics emering from systems like this is the interaction focus shared between physical space, where the surgeon interacts with the patient using surgical tools, and with the digital world, where the surgeon interacts with the system. This limitation results in two different interfaces likely inconsistent, thereby the interaction discontinuities do break the natuarl workflow forcing the user to switch between the operation modes. Our work addresses these features by focusing on the model, interaction and ergonomic integrity analysis considering the Augmented Reality paradigm applied to IGS procedures and more specifically applied to the Neurosurgery study case. We followed a methodology according to the model-based approach, including new extensions in order to support interaction technologies and to sensure continuity interaction according to the IGS system requirements. As a result, designers may as soon as possible discover errors in the development process and may perform an efficient interface design coherently integrating constraints favoring continuity instead of discrete interaction with possible inconsistencies.

  14. Image-Based Modeling of Trabecular Bones

    NASA Astrophysics Data System (ADS)

    Rajapakse, Chamith; Gunaratne, Gemunu

    2004-10-01

    Osteoporosis is a major health problem in the U.S. today. The detection and treatment of osteoporosis is currently based on Bone Mineral Density (BMD) measurements. Recent evidence suggests that the low bone mass alone does not account for the entire risk of osteoporotic fractures. It is also been known that the trabecular regions of bones play a major role in the bone strength . Trabecular bone has a complex structure with substantial heterogeneity, anisotropy and asymmetry. Although these properties effect BMD, the role of architecture and tissue material remain uncertain. Computer modeling of trabecular bone can be used predict responses that cannot be obtained experimentally, and they can compute responses that cannot be measured in-vivo. Due to the complexity of the Trabecular Architecture (TA) a model system based on scanned digital images is introduced to get substantial insight of TA and to predict the failure behavior. It is assumed that the added insight provided by these studies will lead to improved diagnostics and treatments of patient-specific osteoporotic fractures.

  15. Robust model for segmenting images with/without intensity inhomogeneities.

    PubMed

    Li, Changyang; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Feng, David Dagan

    2013-08-01

    Intensity inhomogeneities and different types/levels of image noise are the two major obstacles to accurate image segmentation by region-based level set models. To provide a more general solution to these challenges, we propose a novel segmentation model that considers global and local image statistics to eliminate the influence of image noise and to compensate for intensity inhomogeneities. In our model, the global energy derived from a Gaussian model estimates the intensity distribution of the target object and background; the local energy derived from the mutual influences of neighboring pixels can eliminate the impact of image noise and intensity inhomogeneities. The robustness of our method is validated on segmenting synthetic images with/without intensity inhomogeneities, and with different types/levels of noise, including Gaussian noise, speckle noise, and salt and pepper noise, as well as images from different medical imaging modalities. Quantitative experimental comparisons demonstrate that our method is more robust and more accurate in segmenting the images with intensity inhomogeneities than the local binary fitting technique and its more recent systematic model. Our technique also outperformed the region-based Chan–Vese model when dealing with images without intensity inhomogeneities and produce better segmentation results than the graph-based algorithms including graph-cuts and random walker when segmenting noisy images.

  16. Challenges of Integrating Unmanned Aerial Vehicles In Civil Application

    NASA Astrophysics Data System (ADS)

    Eid, B. M.; Chebil, J.; Albatsh, F.; Faris, W. F.

    2013-12-01

    Unmanned Aerial Vehicle (UAV) has evolved rapidly over the past decade. There have been an increased number of studies aiming at improving UAV and in its use for different civil applications. This paper highlights the fundamentals of UAV system and examines the challenges related with the major components such as motors, drives, power systems, communication systems and image processing tools and equipment.

  17. Use of archive aerial photography for monitoring black mangrove populations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A study was conducted on the south Texas Gulf Coast to evaluate archive aerial color-infrared (CIR) photography combined with supervised image analysis techniques to quantify changes in black mangrove [Avicennia germinans (L.) L.] populations over a 26-year period. Archive CIR film from two study si...

  18. High throughput phenotyping using an unmanned aerial vehicle

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Field trials are expensive and labor-intensive to carry out. Strategies to maximize data collection from these trials will improve research efficiencies. We have purchased a small unmanned aerial vehicle (AEV) to collect digital images from field plots. The AEV is remote-controlled and can be guided...

  19. Aerial Refueling Clearance Process Guide

    DTIC Science & Technology

    2014-08-21

    08-2014 2. REPORT TYPE Guidance Document 3. DATES COVERED 2008-2014 4. TITLE AND SUBTITLE Aerial Refueling Clearance Process Guide Attachment: Aerial...ATP-3.3.4.2 covers general operational procedures for AR and national/organizational SRDs cover data and procedures specific to their AR platforms...Receptacle, Probe/Drogue, and BDA Kit. 3.1.3 The items for assessment consideration cover several areas of interface for both the tanker and the

  20. Velocity measurements and changes in position of Thwaites Glacier/iceberg tongue from aerial photography, Landsat images and NOAA AVHRR data

    USGS Publications Warehouse

    Ferrigno, Jane G.; Lucchitta, Baerbel K.; Mullinsallison, A. L.; Allen, Robert J.; Gould, W. G.

    1993-01-01

    The Thwaites Glacier/iceberg tongue complex has been a significant feature of the Antarctic coastline for at least 50 years. In 1986, major changes began to occur in this area. Fast ice melted and several icebergs calved from the base of the iceberg tongue and the terminus of Thwaites Glacier. The iceberg tongue rotated to an east-west orientation and drifted westward. Between 1986 and 1992, a total of 140 km of drift has occurred. Remote digital velocity measurements were made on Thwaites Glacier using sequential Landsat images to try to determine if changes in velocity had occurred in conjunction with the changes in ice position. Examination of the morphology of the glacier/iceberg tongue showed no evidence of surge activity.

  1. Object-Based Arctic Sea Ice Feature Extraction through High Spatial Resolution Aerial photos

    NASA Astrophysics Data System (ADS)

    Miao, X.; Xie, H.

    2015-12-01

    High resolution aerial photographs used to detect and classify sea ice features can provide accurate physical parameters to refine, validate, and improve climate models. However, manually delineating sea ice features, such as melt ponds, submerged ice, water, ice/snow, and pressure ridges, is time-consuming and labor-intensive. An object-based classification algorithm is developed to automatically extract sea ice features efficiently from aerial photographs taken during the Chinese National Arctic Research Expedition in summer 2010 (CHINARE 2010) in the MIZ near the Alaska coast. The algorithm includes four steps: (1) the image segmentation groups the neighboring pixels into objects based on the similarity of spectral and textural information; (2) the random forest classifier distinguishes four general classes: water, general submerged ice (GSI, including melt ponds and submerged ice), shadow, and ice/snow; (3) the polygon neighbor analysis separates melt ponds and submerged ice based on spatial relationship; and (4) pressure ridge features are extracted from shadow based on local illumination geometry. The producer's accuracy of 90.8% and user's accuracy of 91.8% are achieved for melt pond detection, and shadow shows a user's accuracy of 88.9% and producer's accuracies of 91.4%. Finally, pond density, pond fraction, ice floes, mean ice concentration, average ridge height, ridge profile, and ridge frequency are extracted from batch processing of aerial photos, and their uncertainties are estimated.

  2. Aeolic vibration of aerial electricity transmission cables

    NASA Astrophysics Data System (ADS)

    Avila, A.; Rodriguez-Vera, Ramon; Rayas, Juan A.; Barrientos, Bernardino

    2005-02-01

    A feasibility study for amplitude and frequency vibration measurement in aerial electricity transmission cable has been made. This study was carried out incorporating a fringe projection method for the experimental part and horizontal taut string model for theoretical one. However, this kind of model ignores some inherent properties such as cable sag and cable inclination. Then, this work reports advances on aeolic vibration considering real cables. Catenary and sag are considered in our theoretical model in such a way that an optical theodolite for measuring has been used. Preliminary measurements of the catenary as well as numerical simulation of a sagged cable vibration are given.

  3. Utilize the Remote Sensing Image to Establish the Digital Model of Geographical Information

    NASA Astrophysics Data System (ADS)

    Liu, Z.; Tsai, M.; Wen, J.; Chen, K.

    2008-12-01

    When the natural disaster occurs, it usually leads the change of the terrain, landscape and civil engineering structures. The complete description of the change of the land covers is helpful to the execution and promotion of the disaster rescue. Remote sensing uses the aerial platform carrying image sensors to acquire the remote sensing images from the region that the human can not reach in time. The major advantage of the remote sensing technology is that the environmental information can be obtained ready without contacting with the targets. This advantage lets the remote sensing technology provide a feasible and efficient way to investigate and identify the change of the land covers in the disaster area. In this study, we use the remote sensing technology for image interpretation and the land cover type identification. A mathematical method was developed to adjust the oblique photographs from the aerial photographs to the vertical ones. Then the supervised classification is utilized to identify the land cover types. The results show that our mathematical method provides a feasible approach to adjust the oblique photographs to the vertical ones. The total accuracy of the classification accuracy in the summer is more than 70 percentages, but less than 50 percentages in the winter. The aerial photography is demonstrated to be feasible for the identification of the land cover types in this study. Keywords:Remote sensing image, oblique photograph, vertical photograph, supervised classification.

  4. Aerial thermography for energy efficiency of buildings: the ChoT project

    NASA Astrophysics Data System (ADS)

    Mandanici, Emanuele; Conte, Paolo

    2016-10-01

    The ChoT project aims at analysing the potential of aerial thermal imagery to produce large scale datasets for energetic efficiency analyses and policies in urban environments. It is funded by the Italian Ministry of Education, University and Research (MIUR) in the framework of the SIR 2014 (Scientific Independence of young Researchers) programme. The city of Bologna (Italy) was chosen as the case study. The acquisition of thermal infrared images at different times by multiple aerial flights is one of the main tasks of the project. The present paper provides an overview of the ChoT project, but it delves into some specific aspects of the data processing chain: the computing of the radiometric quantities of the atmosphere, the estimation of surface emissivity (through an object-oriented classification applied on a very high resolution multispectral image, to distinguish among the major roofing materials) and sky-view factor (by means of a digital surface model). To collect ground truth data, the surface temperature of roofs and road pavings was measured at several locations at the same time as the aircraft acquired the thermal images. Furthermore, the emissivity of some roofing materials was estimated by means of a thermal camera and a contact probe. All the surveys were georeferenced by GPS. The results of the first surveying campaign demonstrate the high sensitivity of the model to the variability of the surface emissivity and the atmospheric parameters.

  5. Multiscale modeling for image analysis of brain tumor studies.

    PubMed

    Bauer, Stefan; May, Christian; Dionysiou, Dimitra; Stamatakos, Georgios; Büchler, Philippe; Reyes, Mauricio

    2012-01-01

    Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multiscale, multiphysics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlas-based segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

  6. Affine transformations from aerial photos to computer compatible tapes

    NASA Technical Reports Server (NTRS)

    Peet, F. G.; Mack, A. R.; Crosson, L. S.

    1974-01-01

    During the development of a project to estimate wheat production, it became necessary to pull data, corresponding to particular fields in a test site, off an ERTS computer compatible tape. Aerial photographs and topographic maps were on hand for the test site. A method was devised, using an affine transformation, to relate the aerial photographs or topographic maps to the tapes. One can thereby access data on the tape corresponding to regions covered by only a few pixels. The theory can be used for the registration of two tapes for the same area and for the geometric correction of images.

  7. Comparison of texture models for efficient ultrasound image retrieval

    NASA Astrophysics Data System (ADS)

    Bansal, Maggi; Sharma, Vipul; Singh, Sukhwinder

    2013-02-01

    Due to availability of inexpensive and easily available image capturing devices, the size of digital image collection is increasing rapidly. Thus, there is need to create efficient access methods or retrieval tools to search, browse and retrieve images from large multimedia repositories. More specifically, researchers have been engaged on different ways of retrieving images based on their actual content. In particular, Content Based Image Retrieval (CBIR) systems have attracted considerable research and commercial interest in the recent years. In CBIR, visual features characterizing the image content are color, shape and texture. Currently, texture is used to quantify the image content of medical images as it is the most prominent feature that contains information about the spatial distribution of gray levels and variations in brightness. Various texture models like Haralick's Spatial Gray Level Co-occurence Matrix (SGLCM), Gray Level Difference Statistics (GLDS), First-order Statistics (FoS), Statistical Feature Matrix (SFM), Law's Texture Energy Measures (TEM), Fractal features and Fourier Power Spectrum (FPS) features exists in literature. Each of these models visualizes texture in a different way. Retrieval performance depends upon the choice of texture algorithm. Unfortunately, there is no texture model known to work best for encoding texture properties of liver ultrasound images or retrieving most similar images. An experimental comparison of different texture models for Content Based Medical Image Retrieval (CBMIR) is presented in this paper. For the experiments, liver ultrasound image database is used and the retrieval performance of the various texture models is analyzed in detail. The paper concludes with recommendations which texture model performs better for liver ultrasound images. Interestingly, FPS and SGLCM based Haralick's features perform well for liver ultrasound retrieval and thus can be recommended as a simple baseline for such images.

  8. Optical Imaging and Radiometric Modeling and Simulation

    NASA Technical Reports Server (NTRS)

    Ha, Kong Q.; Fitzmaurice, Michael W.; Moiser, Gary E.; Howard, Joseph M.; Le, Chi M.

    2010-01-01

    OPTOOL software is a general-purpose optical systems analysis tool that was developed to offer a solution to problems associated with computational programs written for the James Webb Space Telescope optical system. It integrates existing routines into coherent processes, and provides a structure with reusable capabilities that allow additional processes to be quickly developed and integrated. It has an extensive graphical user interface, which makes the tool more intuitive and friendly. OPTOOL is implemented using MATLAB with a Fourier optics-based approach for point spread function (PSF) calculations. It features parametric and Monte Carlo simulation capabilities, and uses a direct integration calculation to permit high spatial sampling of the PSF. Exit pupil optical path difference (OPD) maps can be generated using combinations of Zernike polynomials or shaped power spectral densities. The graphical user interface allows rapid creation of arbitrary pupil geometries, and entry of all other modeling parameters to support basic imaging and radiometric analyses. OPTOOL provides the capability to generate wavefront-error (WFE) maps for arbitrary grid sizes. These maps are 2D arrays containing digital sampled versions of functions ranging from Zernike polynomials to combination of sinusoidal wave functions in 2D, to functions generated from a spatial frequency power spectral distribution (PSD). It also can generate optical transfer functions (OTFs), which are incorporated into the PSF calculation. The user can specify radiometrics for the target and sky background, and key performance parameters for the instrument s focal plane array (FPA). This radiometric and detector model setup is fairly extensive, and includes parameters such as zodiacal background, thermal emission noise, read noise, and dark current. The setup also includes target spectral energy distribution as a function of wavelength for polychromatic sources, detector pixel size, and the FPA s charge

  9. Landsat multispectral sharpening using a sensor system model and panchromatic image

    USGS Publications Warehouse

    Lemeshewsky, G.P.; ,

    2003-01-01

    The thematic mapper (TM) sensor aboard Landsats 4, 5 and enhanced TM plus (ETM+) on Landsat 7 collect imagery at 30-m sample distance in six spectral bands. New with ETM+ is a 15-m panchromatic (P) band. With image sharpening techniques, this higher resolution P data, or as an alternative, the 10-m (or 5-m) P data of the SPOT satellite, can increase the spatial resolution of the multispectral (MS) data. Sharpening requires that the lower resolution MS image be coregistered and resampled to the P data before high spatial frequency information is transferred to the MS data. For visual interpretation and machine classification tasks, it is important that the sharpened data preserve the spectral characteristics of the original low resolution data. A technique was developed for sharpening (in this case, 3:1 spatial resolution enhancement) visible spectral band data, based on a model of the sensor system point spread function (PSF) in order to maintain spectral fidelity. It combines high-pass (HP) filter sharpening methods with iterative image restoration to reduce degradations caused by sensor-system-induced blurring and resembling. Also there is a spectral fidelity requirement: sharpened MS when filtered by the modeled degradations should reproduce the low resolution source MS. Quantitative evaluation of sharpening performance was made by using simulated low resolution data generated from digital color-IR aerial photography. In comparison to the HP-filter-based sharpening method, results for the technique in this paper with simulated data show improved spectral fidelity. Preliminary results with TM 30-m visible band data sharpened with simulated 10-m panchromatic data are promising but require further study.

  10. Remotely deployable aerial inspection using tactile sensors

    SciTech Connect

    MacLeod, C. N.; Cao, J.; Pierce, S. G.; Dobie, G.; Summan, R.; Sullivan, J. C.; Pipe, A. G.

    2014-02-18

    For structural monitoring applications, the use of remotely deployable Non-Destructive Evaluation (NDE) inspection platforms offer many advantages, including improved accessibility, greater safety and reduced cost, when compared to traditional manual inspection techniques. The use of such platforms, previously reported by researchers at the University Strathclyde facilitates the potential for rapid scanning of large areas and volumes in hazardous locations. A common problem for both manual and remote deployment approaches lies in the intrinsic stand-off and surface coupling issues of typical NDE probes. The associated complications of these requirements are obviously significantly exacerbated when considering aerial based remote inspection and deployment, resulting in simple visual techniques being the preferred sensor payload. Researchers at Bristol Robotics Laboratory have developed biomimetic tactile sensors modelled on the facial whiskers (vibrissae) of animals such as rats and mice, with the latest sensors actively sweeping their tips across the surface in a back and forth motion. The current work reports on the design and performance of an aerial inspection platform and the suitability of tactile whisking sensors to aerial based surface monitoring applications.

  11. Three-dimensional face model reproduction method using multiview images

    NASA Astrophysics Data System (ADS)

    Nagashima, Yoshio; Agawa, Hiroshi; Kishino, Fumio

    1991-11-01

    This paper describes a method of reproducing three-dimensional face models using multi-view images for a virtual space teleconferencing system that achieves a realistic visual presence for teleconferencing. The goal of this research, as an integral component of a virtual space teleconferencing system, is to generate a three-dimensional face model from facial images, synthesize images of the model virtually viewed from different angles, and with natural shadow to suit the lighting conditions of the virtual space. The proposed method is as follows: first, front and side view images of the human face are taken by TV cameras. The 3D data of facial feature points are obtained from front- and side-views by an image processing technique based on the color, shape, and correlation of face components. Using these 3D data, the prepared base face models, representing typical Japanese male and female faces, are modified to approximate the input facial image. The personal face model, representing the individual character, is then reproduced. Next, an oblique view image is taken by TV camera. The feature points of the oblique view image are extracted using the same image processing technique. A more precise personal model is reproduced by fitting the boundary of the personal face model to the boundary of the oblique view image. The modified boundary of the personal face model is determined by using face direction, namely rotation angle, which is detected based on the extracted feature points. After the 3D model is established, the new images are synthesized by mapping facial texture onto the model.

  12. Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing

    NASA Technical Reports Server (NTRS)

    Ansar, Adnan I.; Brennan, Shane; Clouse, Daniel S.

    2012-01-01

    As imagery is collected from an airborne platform, an individual viewing the images wants to know from where on the Earth the images were collected. To do this, some information about the camera needs to be known, such as its position and orientation relative to the Earth. This can be provided by common inertial navigation systems (INS). Once the location of the camera is known, it is useful to project an image onto some representation of the Earth. Due to the non-smooth terrain of the Earth (mountains, valleys, etc.), this projection is highly non-linear. Thus, to ensure accurate projection, one needs to project onto a digital elevation map (DEM). This allows one to view the images overlaid onto a representation of the Earth. A code has been developed that takes an image, a model of the camera used to acquire that image, the pose of the camera during acquisition (as provided by an INS), and a DEM, and outputs an image that has been geo-rectified. The world coordinate of the bounds of the image are provided for viewing purposes. The code finds a mapping from points on the ground (DEM) to pixels in the image. By performing this process for all points on the ground, one can "paint" the ground with the image, effectively performing a projection of the image onto the ground. In order to make this process efficient, a method was developed for finding a region of interest (ROI) on the ground to where the image will project. This code is useful in any scenario involving an aerial imaging platform that moves and rotates over time. Many other applications are possible in processing aerial and satellite imagery.

  13. Morphological Degradation Models and their Use in Document Image Restoration

    DTIC Science & Technology

    2001-02-01

    Restoration Qigong Zheng and Tapas Kanungo Language and Media Processing Laboratory Center for Automation Research University of Maryland College Park...IIS9987944 February 2001 Morphological Degradation Models and their Use in Document Image Restoration Qigong Zheng and Tapas Kanungo Morphological...Degradation Models and their Use in Document Image Restoration Qigong Zheng and Tapas Kanungo Language and Media Processing Laboratory Center for Automation

  14. A geometric deformable model for echocardiographic image segmentation

    NASA Technical Reports Server (NTRS)

    Hang, X.; Greenberg, N. L.; Thomas, J. D.

    2002-01-01

    Gradient vector flow (GVF), an elegant external force for parametric deformable models, can capture object boundaries from both sides. A new geometric deformable model is proposed that combines GVF and the geodesic active contour model. The level set method is used as the numerical method of this model. The model is applied for echocardiographic image segmentation.

  15. Images as drivers of progress in cardiac computational modelling.

    PubMed

    Lamata, Pablo; Casero, Ramón; Carapella, Valentina; Niederer, Steve A; Bishop, Martin J; Schneider, Jürgen E; Kohl, Peter; Grau, Vicente

    2014-08-01

    Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved.

  16. Retinal image mosaicing using the radial distortion correction model

    NASA Astrophysics Data System (ADS)

    Lee, Sangyeol; Abràmoff, Michael D.; Reinhardt, Joseph M.

    2008-03-01

    Fundus camera imaging can be used to examine the retina to detect disorders. Similar to looking through a small keyhole into a large room, imaging the fundus with an ophthalmologic camera allows only a limited view at a time. Thus, the generation of a retinal montage using multiple images has the potential to increase diagnostic accuracy by providing larger field of view. A method of mosaicing multiple retinal images using the radial distortion correction (RADIC) model is proposed in this paper. Our method determines the inter-image connectivity by detecting feature correspondences. The connectivity information is converted to a tree structure that describes the spatial relationships between the reference and target images for pairwise registration. The montage is generated by cascading pairwise registration scheme starting from the anchor image downward through the connectivity tree hierarchy. The RADIC model corrects the radial distortion that is due to the spherical-to-planar projection during retinal imaging. Therefore, after radial distortion correction, individual images can be properly mapped onto a montage space by a linear geometric transformation, e.g. affine transform. Compared to the most existing montaging methods, our method is unique in that only a single registration per image is required because of the distortion correction property of RADIC model. As a final step, distance-weighted intensity blending is employed to correct the inter-image differences in illumination encountered when forming the montage. Visual inspection of the experimental results using three mosaicing cases shows our method can produce satisfactory montages.

  17. Sparse representation based image interpolation with nonlocal autoregressive modeling.

    PubMed

    Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

    2013-04-01

    Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

  18. Numerical modelling and image reconstruction in diffuse optical tomography

    PubMed Central

    Dehghani, Hamid; Srinivasan, Subhadra; Pogue, Brian W.; Gibson, Adam

    2009-01-01

    The development of diffuse optical tomography as a functional imaging modality has relied largely on the use of model-based image reconstruction. The recovery of optical parameters from boundary measurements of light propagation within tissue is inherently a difficult one, because the problem is nonlinear, ill-posed and ill-conditioned. Additionally, although the measured near-infrared signals of light transmission through tissue provide high imaging contrast, the reconstructed images suffer from poor spatial resolution due to the diffuse propagation of light in biological tissue. The application of model-based image reconstruction is reviewed in this paper, together with a numerical modelling approach to light propagation in tissue as well as generalized image reconstruction using boundary data. A comprehensive review and details of the basis for using spatial and structural prior information are also discussed, whereby the use of spectral and dual-modality systems can improve contrast and spatial resolution. PMID:19581256

  19. Conceptual model for the use of aerial color infrared photography by mosquito control districts as a survey technique for Psorophora columbiae oviposition habitats in Texas ricelands.

    PubMed

    Welch, J B; Olson, J K; Yates, M M; Benton, A R; Baker, R D

    1989-09-01

    Two photographic missions per year are recommended to provide information on land-use and mosquito oviposition habitats. A winter mission, following a rain, will-provide a view of low areas within fields which may be obscured by summer vegetation. A summer mission will provide current land-use and crop distribution information and may show plant stress conditions due to excessive soil moisture. An aerial color infrared photographic survey with directed ground verification should result in a substantial savings in cost and increased efficiency in surveillance of mosquito producing habitats over ground survey techniques currently employed by mosquito control districts.

  20. Unmanned Aerial Vehicle (UAV) associated DTM quality evaluation and hazard assessment

    NASA Astrophysics Data System (ADS)

    Huang, Mei-Jen; Chen, Shao-Der; Chao, Yu-Jui; Chiang, Yi-Lin; Chang, Kuo-Jen

    2014-05-01

    Taiwan, due to the high seismicity and high annual rainfall, numerous landslides triggered every year and severe impacts affect the island. Concerning to the catastrophic landslides, the key information of landslide, including range of landslide, volume estimation and the subsequent evolution are important when analyzing the triggering mechanism, hazard assessment and mitigation. Thus, the morphological analysis gives a general overview for the landslides and been considered as one of the most fundamental information. We try to integrate several technologies, especially by Unmanned Aerial Vehicle (UAV) and multi-spectral camera, to decipher the consequence and the potential hazard, and the social impact. In recent years, the remote sensing technology improves rapidly, providing a wide range of image, essential and precious information. Benefited of the advancing of informatics, remote-sensing and electric technologies, the Unmanned Aerial Vehicle (UAV) photogrammetry mas been improve significantly. The study tries to integrate several methods, including, 1) Remote-sensing images gathered by Unmanned Aerial Vehicle (UAV) and by aerial photos taken in different periods; 2) field in-situ geologic investigation; 3) Differential GPS, RTK GPS and Ground LiDAR field in-site geoinfomatics measurements; 4) Construct the DTMs before and after landslide, as well as the subsequent periods using UAV and aerial photos; 5) Discrete element method should be applied to understand the geomaterial composing the slope failure, for predicting earthquake-induced and rainfall-induced landslides displacement. First at all, we evaluate the Microdrones MD4-1000 UAV airphotos derived Digital Terrain Model (DTM). The ground resolution of the DSM point cloud of could be as high as 10 cm. By integrated 4 ground control point within an area of 56 hectares, compared with LiDAR DSM and filed RTK-GPS surveying, the mean error is as low as 6cm with a standard deviation of 17cm. The quality of the

  1. The remote characterization of vegetation using Unmanned Aerial Vehicle photography

    NASA Astrophysics Data System (ADS)

    Rango, A.; Laliberte, A.; Winters, C.; Maxwell, C.; Steele, C.

    2008-12-01

    Unmanned Aerial Vehicles (UAVs) can fly in place of piloted aircraft to gather remote sensing information on vegetation characteristics. The type of sensors flown depends on the instrument payload capacity available, so that, depending on the specific UAV, it is possible to obtain video, aerial photographic, multispectral and hyperspectral radiometric, LIDAR, and radar data. The characteristics of several small UAVs less than 55lbs (25kg)) along with some payload instruments will be reviewed. Common types of remote sensing coverage available from a small, limited-payload UAV are video and hyperspatial, digital photography. From evaluation of these simple types of remote sensing data, we conclude that UAVs can play an important role in measuring and monitoring vegetation health and structure of the vegetation/soil complex in rangelands. If we fly our MLB Bat-3 at an altitude of 700ft (213m), we can obtain a digital photographic resolution of 6cm. The digital images acquired cover an area of approximately 29,350sq m. Video imaging is usually only useful for monitoring the flight path of the UAV in real time. In our experiments with the 6cm resolution data, we have been able to measure vegetation patch size, crown width, gap sizes between vegetation, percent vegetation and bare soil cover, and type of vegetation. The UAV system is also being tested to acquire height of the vegetation canopy using shadow measurements and a digital elevation model obtained with stereo images. Evaluation of combining the UAV digital photography with LIDAR data of the Jornada Experimental Range in south central New Mexico is ongoing. The use of UAVs is increasing and is becoming a very promising tool for vegetation assessment and change, but there are several operational components to flying UAVs that users need to consider. These include cost, a whole set of, as yet, undefined regulations regarding flying in the National Air Space(NAS), procedures to gain approval for flying in the NAS

  2. Three very high resolution optical images for land use mapping of a suburban catchment: input to distributed hydrological models

    NASA Astrophysics Data System (ADS)

    Jacqueminet, Christine; Kermadi, Saïda; Michel, Kristell; Jankowfsky, Sonja; Braud, Isabelle; Branger, Flora; Beal, David; Gagnage, Matthieu

    2010-05-01

    Keywords : land cover mapping, very high resolution, remote sensing processing techniques, object oriented approach, distributed hydrological model, peri-urban area Urbanization and other modifications of land use affect the hydrological cycle of suburban catchments. In order to quantify these impacts, the AVuPUR project (Assessing the Vulnerability of Peri-Urban Rivers) is currently developing a distributed hydrological model that includes anthropogenic features. The case study is the Yzeron catchment (150 km²), located close to Lyon city, France. This catchment experiences a growing of urbanization and a modification of traditional land use since the middle of the 20th century, resulting in an increase of flooding, water pollution and river banks erosion. This contribution discusses the potentials of automated data processing techniques on three different VHR images, in order to produce appropriate and detailed land cover data for the models. Of particular interest is the identification of impermeable surfaces (buildings, roads, and parking places) and permeable surfaces (forest areas, agricultural fields, gardens, trees…) within the catchment, because their infiltration capacity and their impact on runoff generation are different. Three aerial and spatial images were acquired: (1) BD Ortho IGN aerial images, 0.50 m resolution, visible bands, may 5th 2008; (2) QuickBird satellite image, 2.44 m resolution, visible and near-infrared bands, august 29th 2008; (3) Spot satellite image, 2.50 m resolution, visible and near-infrared bands, September 22nd 2008. From these images, we developed three image processing methods: (1) a pixel-based method associated to a segmentation using Matlab®, (2) a pixel-based method using ENVI®, (3) an object-based classification using Definiens®. We extracted six land cover types from the BD Ortho IGN (visible bands) and height classes from the satellite images (visible and near infrared bands). The three classified images are

  3. Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

    PubMed

    Zhang, Jiachao; Hirakawa, Keigo

    2017-04-01

    This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

  4. BOREAS Level-0 C-130 Aerial Photography

    NASA Technical Reports Server (NTRS)

    Newcomer, Jeffrey A.; Dominguez, Roseanne; Hall, Forrest G. (Editor)

    2000-01-01

    For BOReal Ecosystem-Atmosphere Study (BOREAS), C-130 and other aerial photography was collected to provide finely detailed and spatially extensive documentation of the condition of the primary study sites. The NASA C-130 Earth Resources aircraft can accommodate two mapping cameras during flight, each of which can be fitted with 6- or 12-inch focal-length lenses and black-and-white, natural-color, or color-IR film, depending upon requirements. Both cameras were often in operation simultaneously, although sometimes only the lower resolution camera was deployed. When both cameras were in operation, the higher resolution camera was often used in a more limited fashion. The acquired photography covers the period of April to September 1994. The aerial photography was delivered as rolls of large format (9 x 9 inch) color transparency prints, with imagery from multiple missions (hundreds of prints) often contained within a single roll. A total of 1533 frames were collected from the C-130 platform for BOREAS in 1994. Note that the level-0 C-130 transparencies are not contained on the BOREAS CD-ROM set. An inventory file is supplied on the CD-ROM to inform users of all the data that were collected. Some photographic prints were made from the transparencies. In addition, BORIS staff digitized a subset of the tranparencies and stored the images in JPEG format. The CD-ROM set contains a small subset of the collected aerial photography that were the digitally scanned and stored as JPEG files for most tower and auxiliary sites in the NSA and SSA. See Section 15 for information about how to acquire additional imagery.

  5. Correlation of breast image alignment using biomechanical modelling

    NASA Astrophysics Data System (ADS)

    Lee, Angela; Rajagopal, Vijay; Bier, Peter; Nielsen, Poul M. F.; Nash, Martyn P.

    2009-02-01

    Breast cancer is one of the most common causes of cancer death among women around the world. Researchers have found that a combination of imaging modalities (such as x-ray mammography, magnetic resonance, and ultrasound) leads to more effective diagnosis and management of breast cancers because each imaging modality displays different information about the breast tissues. In order to aid clinicians in interpreting the breast images from different modalities, we have developed a computational framework for generating individual-specific, 3D, finite element (FE) models of the breast. Medical images are embedded into this model, which is subsequently used to simulate the large deformations that the breasts undergo during different imaging procedures, thus warping the medical images to the deformed views of the breast in the different modalities. In this way, medical images of the breast taken in different geometric configurations (compression, gravity, etc.) can be aligned according to physically feasible transformations. In order to analyse the accuracy of the biomechanical model predictions, squared normalised cross correlation (NCC2) was used to provide both local and global comparisons of the model-warped images with clinical images of the breast subject to different gravity loaded states. The local comparison results were helpful in indicating the areas for improvement in the biomechanical model. To improve the modelling accuracy, we will need to investigate the incorporation of breast tissue heterogeneity into the model and altering the boundary conditions for the breast model. A biomechanical image registration tool of this kind will help radiologists to provide more reliable diagnosis and localisation of breast cancer.

  6. Modeling the statistics of image features and associated text

    NASA Astrophysics Data System (ADS)

    Barnard, Kobus; Duygulu, Pinar; Forsyth, David A.

    2001-12-01

    We present a methodology for modeling the statistics of image features and associated text in large datasets. The models used also serve to cluster the images, as images are modeled as being produced by sampling from a limited number of combinations of mixing components. Furthermore, because our approach models the joint occurrence image features and associated text, it can be used to predict the occurrence of either, based on observations or queries. This supports an attractive approach to image search as well as novel applications such a suggesting illustrations for blocks of text (auto-illustrate) and generating words for images outside the training set (auto-annotate). In this paper we illustrate the approach on 10,000 images of work from the Fine Arts Museum of San Francisco. The images include line drawings, paintings, and pictures of sculpture and ceramics. Many of the images have associated free text whose nature varies greatly, from physical description to interpretation and mood. We incorporate statistical natural language processing in order to deal with free text. We use WordNet to provide semantic grouping information and to help disambiguate word senses, as well as emphasize the hierarchical nature of semantic relationships.

  7. Model-based quantification of image quality

    NASA Technical Reports Server (NTRS)

    Hazra, Rajeeb; Miller, Keith W.; Park, Stephen K.

    1989-01-01

    In 1982, Park and Schowengerdt published an end-to-end analysis of a digital imaging system quantifying three principal degradation components: (1) image blur - blurring caused by the acquisition system, (2) aliasing - caused by insufficient sampling, and (3) reconstruction blur - blurring caused by the imperfect interpolative reconstruction. This analysis, which measures degradation as the square of the radiometric error, includes the sample-scene phase as an explicit random parameter and characterizes the image degradation caused by imperfect acquisition and reconstruction together with the effects of undersampling and random sample-scene phases. In a recent paper Mitchell and Netravelli displayed the visual effects of the above mentioned degradations and presented subjective analysis about their relative importance in determining image quality. The primary aim of the research is to use the analysis of Park and Schowengerdt to correlate their mathematical criteria for measuring image degradations with subjective visual criteria. Insight gained from this research can be exploited in the end-to-end design of optical systems, so that system parameters (transfer functions of the acquisition and display systems) can be designed relative to each other, to obtain the best possible results using quantitative measurements.

  8. A review of the meteorological parameters which affect aerial application

    NASA Technical Reports Server (NTRS)

    Christensen, L. S.; Frost, W.

    1979-01-01

    The ambient wind field and temperature gradient were found to be the most important parameters. Investigation results indicated that the majority of meteorological parameters affecting dispersion were interdependent and the exact mechanism by which these factors influence the particle dispersion was largely unknown. The types and approximately ranges of instrumented capabilities for a systematic study of the significant meteorological parameters influencing aerial applications were defined. Current mathematical dispersion models were also briefly reviewed. Unfortunately, a rigorous dispersion model which could be applied to aerial application was not available.

  9. Dynamics of aerial target pursuit

    NASA Astrophysics Data System (ADS)

    Pal, S.

    2015-12-01

    During pursuit and predation, aerial species engage in multitasking behavior that involve simultaneous target detection, tracking, decision-making, approach and capture. The mobility of the pursuer and the target in a three dimensional environment during predation makes the capture task highly complex. Many researchers have studied and analyzed prey capture dynamics in different aerial species such as insects and bats. This article focuses on reviewing the capture strategies adopted by these species while relying on different sensory variables (vision and acoustics) for navigation. In conclusion, the neural basis of these capture strategies and some applications of these strategies in bio-inspired navigation and control of engineered systems are discussed.

  10. Ghost imaging with twisted Gaussian Schell-model beam.

    PubMed

    Cai, Yangjian; Lin, Qiang; Korotkova, Olga

    2009-02-16

    Based on the classical optical coherence theory, ghost imaging with twisted Gaussian Schell-model (GSM) beams is analyzed. It is found that the twist phase of the GSM beam has strong influence on ghost imaging. As the absolute value of the twist factor increases, the ghost image disappears gradually, but its visibility increases. This phenomenon is caused by the fact that the twist phase enhances the transverse spatial coherence of the twisted GSM beam on propagation.

  11. USGS aerial resolution targets.

    USGS Publications Warehouse

    Salamonowicz, P.H.

    1982-01-01

    It is necessary to measure the achievable resolution of any airborne sensor that is to be used for metric purposes. Laboratory calibration facilities may be inadequate or inappropriate for determining the resolution of non-photographic sensors such as optical-mechanical scanners, television imaging tubes, and linear arrays. However, large target arrays imaged in the field can be used in testing such systems. The USGS has constructed an array of resolution targets in order to permit field testing of a variety of airborne sensing systems. The target array permits any interested organization with an airborne sensing system to accurately determine the operational resolution of its system. -from Author

  12. Image-based modeling of objects and human faces

    NASA Astrophysics Data System (ADS)

    Zhang, Zhengyou

    2000-12-01

    In this paper, provided is an overview of our project on 3D object and face modeling from images taken by a free-moving camera. We strive to advance the state of the art in 3D computer vision, and develop flexible and robust techniques for ordinary users to gain 3D experience from a ste of casually collected 2D images. Applications include product advertisement on the Web, virtual conference, and interactive games. We briefly cover the following topics: camera calibration, stereo rectification, image matching, 3D photo editing, object modeling, and face modeling. Demos on the last three topics will be shown during the conference.

  13. Image quality assessment by preprocessing and full reference model combination

    NASA Astrophysics Data System (ADS)

    Bianco, S.; Ciocca, G.; Marini, F.; Schettini, R.

    2009-01-01

    This paper focuses on full-reference image quality assessment and presents different computational strategies aimed to improve the robustness and accuracy of some well known and widely used state of the art models, namely the Structural Similarity approach (SSIM) by Wang and Bovik and the S-CIELAB spatial-color model by Zhang and Wandell. We investigate the hypothesis that combining error images with a visual attention model could allow a better fit of the psycho-visual data of the LIVE Image Quality assessment Database Release 2. We show that the proposed quality assessment metric better correlates with the experimental data.

  14. Modeling semantic aspects for cross-media image indexing.

    PubMed

    Monay, Florent; Gatica-Perez, Daniel

    2007-10-01

    To go beyond the query-by-example paradigm in image retrieval, there is a need for semantic indexing of large image collections for intuitive text-based image search. Different models have been proposed to learn the dependencies between the visual content of an image set and the associated text captions, then allowing for the automatic creation of semantic indices for unannotated images. The task, however, remains unsolved. In this paper, we present three alternatives to learn a Probabilistic Latent Semantic Analysis model (PLSA) for annotated images, and evaluate their respective performance for automatic image indexing. Under the PLSA assumptions, an image is modeled as a mixture of latent aspects that generates both image features and text captions, and we investigate three ways to learn the mixture of aspects. We also propose a more discriminative image representation than the traditional Blob histogram, concatenating quantized local color information and quantized local texture descriptors. The first learning procedure of a PLSA model for annotated images is a standard EM algorithm, which implicitly assumes that the visual and the textual modalities can be treated equivalently. The other two models are based on an asymmetric PLSA learning, allowing to constrain the definition of the latent space on the visual or on the textual modality. We demonstrate that the textual modality is more appropriate to learn a semantically meaningful latent space, which translates into improved annotation performance. A comparison of our learning algorithms with respect to recent methods on a standard dataset is presented, and a detailed evaluation of the performance shows the validity of our framework.

  15. Analysis of radar images by means of digital terrain models

    NASA Technical Reports Server (NTRS)

    Domik, G.; Leberl, F.; Kobrick, M.

    1984-01-01

    It is pointed out that the importance of digital terrain models in the processing, analysis, and interpretation of remote sensing data is increasing. In investigations related to the study of radar images, digital terrain models can have a particular significance, because radar reflection is a function of the terrain characteristics. A procedure for the analysis and interpretation of radar images is discussed. The procedure is based on a utilization of computer simulation which makes it possible to produce simulated radar images on the basis of a digital terrain model. The simulated radar images are used for the geometric and radiometric rectification of real radar images. A description of the employed procedures is provided, and the obtained results are discussed, taking into account a test area in Northern California.

  16. Modelling of classical ghost images obtained using scattered light

    NASA Astrophysics Data System (ADS)

    Crosby, S.; Castelletto, S.; Aruldoss, C.; Scholten, R. E.; Roberts, A.

    2007-08-01

    The images obtained in ghost imaging with pseudo-thermal light sources are highly dependent on the spatial coherence properties of the incident light. Pseudo-thermal light is often created by reducing the coherence length of a coherent source by passing it through a turbid mixture of scattering spheres. We describe a model for simulating ghost images obtained with such partially coherent light, using a wave-transport model to calculate the influence of the scattering on initially coherent light. The model is able to predict important properties of the pseudo-thermal source, such as the coherence length and the amplitude of the residual unscattered component of the light which influence the resolution and visibility of the final ghost image. We show that the residual ballistic component introduces an additional background in the reconstructed image, and the spatial resolution obtainable depends on the size of the scattering spheres.

  17. Radiological Disaster Simulators for Field and Aerial Measurements

    SciTech Connect

    H. W. Clark, Jr

    2002-11-01

    Simulators have been developed to dramatically improve the fidelity of play for field monitors and aircraft participating in radiological disaster drills and exercises. Simulated radiological measurements for the current Global Positioning System (GPS) location are derived from realistic models of radiological consequences for accidents and malicious acts. The aerial version outputs analog pulses corresponding to the signal that would be produced by various NaI (Tl) detectors at that location. The field monitor version reports the reading for any make/model of survey instrument selected. Position simulation modes are included in the aerial and field versions. The aerial version can generate a flight path based on input parameters or import an externally generated sequence of latitude and longitude coordinates. The field version utilizes a map-based point and click/drag interface to generate individual or a sequence of evenly spaced instrument measurements.

  18. Registering preprocedure volumetric images with intraprocedure 3-D ultrasound using an ultrasound imaging model.

    PubMed

    King, A P; Rhode, K S; Ma, Y; Yao, C; Jansen, C; Razavi, R; Penney, G P

    2010-03-01

    For many image-guided interventions there exists a need to compute the registration between preprocedure image(s) and the physical space of the intervention. Real-time intraprocedure imaging such as ultrasound (US) can be used to image the region of interest directly and provide valuable anatomical information for computing this registration. Unfortunately, real-time US images often have poor signal-to-noise ratio and suffer from imaging artefacts. Therefore, registration using US images can be challenging and significant preprocessing is often required to make the registrations robust. In this paper we present a novel technique for computing the image-to-physical registration for minimally invasive cardiac interventions using 3-D US. Our technique uses knowledge of the physics of the US imaging process to reduce the amount of preprocessing required on the 3-D US images. To account for the fact that clinical US images normally undergo significant image processing before being exported from the US machine our optimization scheme allows the parameters of the US imaging model to vary. We validated our technique by computing rigid registrations for 12 cardiac US/magnetic resonance imaging (MRI) datasets acquired from six volunteers and two patients. The technique had mean registration errors of 2.1-4.4 mm, and 75% capture ranges of 5-30 mm. We also demonstrate how the same approach can be used for respiratory motion correction: on 15 datasets acquired from five volunteers the registration errors due to respiratory motion were reduced by 45%-92%.

  19. Simultaneous sparsity model for histopathological image representation and classification.

    PubMed

    Srinivas, Umamahesh; Mousavi, Hojjat Seyed; Monga, Vishal; Hattel, Arthur; Jayarao, Bhushan

    2014-05-01

    The multi-channel nature of digital histopathological images presents an opportunity to exploit the correlated color channel information for better image modeling. Inspired by recent work in sparsity for single channel image classification, we propose a new simultaneous sparsity model for multi-channel histopathological image representation and classification (SHIRC). Essentially, we represent a histopathological image as a sparse linear combination of training examples under suitable channel-wise constraints. Classification is performed by solving a newly formulated simultaneous sparsity-based optimization problem. A practical challenge is the correspondence of image objects (cellular and nuclear structures) at different spatial locations in the image. We propose a robust locally adaptive variant of SHIRC (LA-SHIRC) to tackle this issue. Experiments on two challenging real-world image data sets: 1) mammalian tissue images acquired by pathologists of the animal diagnostics lab (ADL) at Pennsylvania State University, and 2) human intraductal breast lesions, reveal the merits of our proposal over state-of-the-art alternatives. Further, we demonstrate that LA-SHIRC exhibits a more graceful decay in classification accuracy against the number of training images which is highly desirable in practice where generous training per class is often not available.

  20. A novel duplicate images detection method based on PLSA model

    NASA Astrophysics Data System (ADS)

    Liao, Xiaofeng; Wang, Yongji; Ding, Liping; Gu, Jian

    2012-01-01

    Web image search results usually contain duplicate copies. This paper considers the problem of detecting and clustering duplicate images contained in web image search results. Detecting and clustering the duplicate images together facilitates use