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Sample records for aerial image model

  1. Fitting of Parametric Building Models to Oblique Aerial Images

    NASA Astrophysics Data System (ADS)

    Panday, U. S.; Gerke, M.

    2011-09-01

    In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS) data. This leads to inconsistent building outlines, which has a negative influence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of - 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for completeness of

  2. 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.

  3. 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

  4. 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. 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. Moving Object Detection Using Dynamic Motion Modelling from UAV Aerial Images

    PubMed Central

    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. PMID:24892103

  7. 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. PMID:24892103

  8. Shoreline extraction from light detection and ranging digital elevation model data and aerial images

    NASA Astrophysics Data System (ADS)

    Yousef, Amr; Iftekharuddin, Khan M.; Karim, Mohammad A.

    2014-01-01

    There is an increased demand for understanding the accurate position of the shorelines. The automatic extraction of shorelines utilizing the digital elevation models (DEMs) obtained from light detection and ranging (LiDAR), aerial images, and multispectral images has become very promising. In this article, we develop two innovative algorithms that can effectively extract shorelines depending on the available data sources. The first is a multistep morphological technique that works on LiDAR DEM with respect to a tidal datum, whereas the second depends on the availability of training data to extract shorelines from LiDAR DEM fused with aerial images. Unlike similar techniques, the morphological approach detects and eliminates the outliers that result from waves, etc., by means of an anomaly test with neighborhood constraints. Additionally, it eliminates docks, bridges, and fishing piers along the extracted shorelines by means of Hough transform. The second approach extracts the shoreline by means of color space conversion of the aerial images and the support vector machines classifier to segment the fused data into water and land. We perform Monte-Carlo simulations to estimate the confidence interval for the error in shoreline position. Compared with other relevant techniques in literature, the proposed methods offer better accuracy in shoreline extraction.

  9. Urban Object Extraction from Digital Surface Model and Digital Aerial Images

    NASA Astrophysics Data System (ADS)

    Grigillo, D.; Kanjir, U.

    2012-07-01

    The paper describes two different methods for extraction of two types of urban objects from lidar digital surface model (DSM) and digital aerial images. Within the preprocessing digital terrain model (DTM) and orthoimages for three test areas were generated from aerial images using automatic photogrammetric methods. Automatic building extraction was done using DSM and multispectral orthoimages. First, initial building mask was created from the normalized digital surface model (nDSM), then vegetation was eliminated from the building mask using multispectral orthoimages. The final building mask was produced employing several morphological operations and buildings were vectorised using Hough transform. Automatic extraction of other green urban features (trees and natural ground) started from orthoimages using iterative object-based classification. This method required careful selection of segmentation parameters; in addition to basic spectral bands also information from nDSM was included. After the segmentation of images the segments were classified based on their attributes (spatial, spectral, geometrical, texture) using rule set classificator. First iteration focused on visible (i.e. unshaded) urban features, and second iteration on objects in deep shade. Results from both iterations were merged into appropriate classes. Evaluation of the final results (completeness, correctness and quality) was carried out on a per-area level and on a per-object level by ISPRS Commission III, WG III/4.

  10. a computational modeling for image motion velocity on focal plane of aerial & aerospace frame camera

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Jin, G.; Li, Z. Y.

    As the resolving power and geometric accuracy of aerial aerospace imaging is demanded to be higher the researches in technology of IMC become very important In order to compensate the image motion on focal plane the rule of FPIMV Focal Plane Image Motion Velocity should be grasped while the posture of aircraft and the modes of imaging are under changing In this paper a reasonable computational modeling scheme to the problem is introduced Coordinates transformation method is utilized for calculation of forward FPIMV under different condition of vertical and sloped imaging meanwhile integrated with three axes posture and angle velocity of aircraft Forward FPIMV combine with pitch roll and yaw FPIMV is considered simultaneously and the derivation calculating expressions of frame camera FPIMV under different conditions is presented in detail The solution is applied to computational simulation and has been confirmed to be effective based on the calculation result and it lays the foundation for our farther researches on frame camera IMC technology Key words IMC FPIMV Focal Plane Image Motion Velocity Coordinates transformation method

  11. Implementation of a segmentation method for agricultural fields in aerial sequences of images based on CSAR model

    NASA Astrophysics Data System (ADS)

    Chen, Haijun; Houkes, Zweitze

    1998-09-01

    In this paper, a segmentation method for agricultural fields in aerial sequences of images based on the Circular Symmetri Auto-Regressive (CSAR) model is presented. The image sequences assumed to be acquired by a video camera (RGB-CCD system) from an aeroplane, which moves linearly over the scene. The objects in the scenes being considered in this paper, are agricultural fields. The classes of agricultural fields to be distinguished are determined by the type of crop, e.g. potatoes sugar beet, wheat, etc. In order to recognize and classify these fields from aerial sequence of images, a reliable segmentatio is required. Here texture features are used for segmentation. The implementation of segmentation for agricultural fields in aerial sequences of images is based on CSAR model in texture analysis. By comparing the estimated parameters of CSAR model from different area in an image, the characteristics and the class of a texture may be determined. The paper describes the segmentation method and its evaluation through experiments. Based on segmentation results, classification for surface texture of vegetation from aerial sequences of images is realized.

  12. 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.

  13. 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.

  14. 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.

  15. Model-based recognition and classification for surface texture of vegetation from an aerial sequence of images

    NASA Astrophysics Data System (ADS)

    Chen, Haijun; Houkes, Zweitze

    1997-12-01

    In this paper, a model based recognition and classification method for surface texture of vegetation from aerial sequence of images is presented. The image sequences are assumed to be acquired by a video camera (RGB-CCD system) from an aeroplane, which moves linearly over the scene. The objects in the scenes being considered in this paper, are agricultural fields. The classes of agricultural fields to be distinguished are determined by the type of crop, e.g. potatoes, sugar beet, what, etc. In order to recognize and classify these fields from aerial sequence of images, a common approach is in the use of surface texture. Here the circular symmetric auto- regressive (CSAR) random model is used for texture analysis. By manipulating the estimated value against its real value, the characteristics of a texture image may be determined. A hypothesize-and verify algorithm is used for model recognition. Based on all kinds of models, classification for surface texture of vegetation from aerial sequences of images is realized.

  16. Discovering discriminative graphlets for aerial image categories recognition.

    PubMed

    Zhang, Luming; Han, Yahong; Yang, Yi; Song, Mingli; Yan, Shuicheng; Tian, Qi

    2013-12-01

    Recognizing aerial image categories is useful for scene annotation and surveillance. Local features have been demonstrated to be robust to image transformations, including occlusions and clutters. However, the geometric property of an aerial image (i.e., the topology and relative displacement of local features), which is key to discriminating aerial image categories, cannot be effectively represented by state-of-the-art generic visual descriptors. To solve this problem, we propose a recognition model that mines graphlets from aerial images, where graphlets are small connected subgraphs reflecting both the geometric property and color/texture distribution of an aerial image. More specifically, each aerial image is decomposed into a set of basic components (e.g., road and playground) and a region adjacency graph (RAG) is accordingly constructed to model their spatial interactions. Aerial image categories recognition can subsequently be casted as RAG-to-RAG matching. Based on graph theory, RAG-to-RAG matching is conducted by comparing all their respective graphlets. Because the number of graphlets is huge, we derive a manifold embedding algorithm to measure different-sized graphlets, after which we select graphlets that have highly discriminative and low redundancy topologies. Through quantizing the selected graphlets from each aerial image into a feature vector, we use support vector machine to discriminate aerial image categories. Experimental results indicate that our method outperforms several state-of-the-art object/scene recognition models, and the visualized graphlets indicate that the discriminative patterns are discovered by our proposed approach. PMID:23955764

  17. 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.

  18. Modeling aerial refueling operations

    NASA Astrophysics Data System (ADS)

    McCoy, Allen B., III

    Aerial Refueling (AR) is the act of offloading fuel from one aircraft (the tanker) to another aircraft (the receiver) in mid flight. Meetings between tanker and receiver aircraft are referred to as AR events and are scheduled to: escort one or more receivers across a large body of water; refuel one or more receivers; or train receiver pilots, tanker pilots, and boom operators. In order to efficiently execute the Aerial Refueling Mission, the Air Mobility Command (AMC) of the United States Air Force (USAF) depends on computer models to help it make tanker basing decisions, plan tanker sorties, schedule aircraft, develop new organizational doctrines, and influence policy. We have worked on three projects that have helped AMC improve its modeling and decision making capabilities. Optimal Flight Planning. Currently Air Mobility simulation and optimization software packages depend on algorithms which iterate over three dimensional fuel flow tables to compute aircraft fuel consumption under changing flight conditions. When a high degree of fidelity is required, these algorithms use a large amount of memory and CPU time. We have modeled the rate of aircraft fuel consumption with respect to AC GrossWeight, Altitude and Airspeed. When implemented, this formula will decrease the amount of memory and CPU time needed to compute sortie fuel costs and cargo capacity values. We have also shown how this formula can be used in optimal control problems to find minimum costs flight plans. Tanker Basing Demand Mismatch Index. Since 1992, AMC has relied on a Tanker Basing/AR Demand Mismatch Index which aggregates tanker capacity and AR demand data into six regions. This index was criticized because there were large gradients along regional boundaries. Meanwhile tankers frequently cross regional boundaries to satisfy the demand for AR support. In response we developed continuous functions to score locations with respect to their proximity to demand for AR support as well as their

  19. 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.

  20. 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

    2016-01-01

    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

  1. 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

  2. Floating aerial LED signage based on aerial imaging by retro-reflection (AIRR).

    PubMed

    Yamamoto, Hirotsugu; Tomiyama, Yuka; Suyama, Shiro

    2014-11-01

    We propose a floating aerial LED signage technique by utilizing retro-reflection. The proposed display is composed of LEDs, a half mirror, and retro-reflective sheeting. Directivity of the aerial image formation and size of the aerial image have been investigated. Furthermore, a floating aerial LED sign has been successfully formed in free space.

  3. Calculating aerial images from EUV masks

    NASA Astrophysics Data System (ADS)

    Pistor, Thomas V.; Neureuther, Andrew R.

    1999-06-01

    Aerial images for line/space patterns, arrays of posts and an arbitrary layout pattern are calculated for EUV masks in a 4X EUV imaging system. Both mask parameters and illumination parameters are varied to investigate their effects on the aerial image. To facilitate this study, a parallel version of TEMPEST with a Fourier transform boundary condition was developed and run on a network of 24 microprocessors. Line width variations are observed when absorber thickness or sidewall angle changes. As the line/space pattern scales to smaller dimensions, the aspect ratios of the absorber features increase, introducing geometric shadowing and reducing aerial image intensity and contrast. 100nm square posts have circular images of diameter close to 100nm, but decreasing in diameter significantly when the corner round radius at the mask becomes greater than 50 nm. Exterior mask posts image slightly smaller and with higher ellipticity than interior mask posts. The aerial image of the arbitrary test pattern gives insight into the effects of the off-axis incidence employed in EUV lithography systems.

  4. 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.

  5. 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.

  6. Aerial photographs and satellite images

    USGS Publications Warehouse

    U.S. Geological Survey

    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.

  7. Wafer weak point detection based on aerial images or WLCD

    NASA Astrophysics Data System (ADS)

    Ning, Guoxiang; Philipp, Peter; Litt, Lloyd C.; Ackmann, Paul; Crell, Christian; Chen, Norman

    2015-10-01

    Aerial image measurement is a key technique for model based optical proximity correction (OPC) verification. Actual aerial images obtained by AIMS (aerial image measurement system) or WLCD (wafer level critical dimension) can detect printed wafer weak point structures in advance of wafer exposure and defect inspection. Normally, the potential wafer weak points are determined based on optical rule check (ORC) simulation in advance. However, the correlation to real wafer weak points is often not perfect due to the contribution of mask three dimension (M3D) effects, actual mask errors, and scanner lens effects. If the design weak points can accurately be detected in advance, it will reduce the wafer fab cost and improve cycle time. WLCD or AIMS tools are able to measure the aerial images CD and bossung curve through focus window. However, it is difficult to detect the wafer weak point in advance without defining selection criteria. In this study, wafer weak points sensitive to mask mean-to-nominal values are characterized for a process with very high MEEF (normally more than 4). Aerial image CD uses fixed threshold to detect the wafer weak points. By using WLCD through threshold and focus window, the efficiency of wafer weak point detection is also demonstrated. A novel method using contrast range evaluation is shown in the paper. Use of the slope of aerial images for more accurate detection of the wafer weak points using WLCD is also discussed. The contrast range can also be used to detect the wafer weak points in advance. Further, since the mean to nominal of the reticle contributes to the effective contrast range in a high MEEF area this work shows that control of the mask error is critical for high MEEF layers such as poly, active and metal layers. Wafer process based weak points that cannot be detected by wafer lithography CD or WLCD will be discussed.

  8. 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. PMID:25794407

  9. 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.

  10. Uncertainty in 2D hydrodynamic models from errors in roughness parameterization based on aerial images

    NASA Astrophysics Data System (ADS)

    Straatsma, Menno; Huthoff, Fredrik

    2011-01-01

    In The Netherlands, 2D-hydrodynamic simulations are used to evaluate the effect of potential safety measures against river floods. In the investigated scenarios, the floodplains are completely inundated, thus requiring realistic representations of hydraulic roughness of floodplain vegetation. The current study aims at providing better insight into the uncertainty of flood water levels due to uncertain floodplain roughness parameterization. The study focuses on three key elements in the uncertainty of floodplain roughness: (1) classification error of the landcover map, (2), within class variation of vegetation structural characteristics, and (3) mapping scale. To assess the effect of the first error source, new realizations of ecotope maps were made based on the current floodplain ecotope map and an error matrix of the classification. For the second error source, field measurements of vegetation structure were used to obtain uncertainty ranges for each vegetation structural type. The scale error was investigated by reassigning roughness codes on a smaller spatial scale. It is shown that classification accuracy of 69% leads to an uncertainty range of predicted water levels in the order of decimeters. The other error sources are less relevant. The quantification of the uncertainty in water levels can help to make better decisions on suitable flood protection measures. Moreover, the relation between uncertain floodplain roughness and the error bands in water levels may serve as a guideline for the desired accuracy of floodplain characteristics in hydrodynamic models.

  11. 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.

  12. 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

  13. Model-based automatic 3d building model generation by integrating LiDAR and aerial images

    NASA Astrophysics Data System (ADS)

    Habib, A.; Kwak, E.; Al-Durgham, M.

    2011-12-01

    Accurate, detailed, and up-to-date 3D building models are important for several applications such as telecommunication network planning, urban planning, and military simulation. Existing building reconstruction approaches can be classified according to the data sources they use (i.e., single versus multi-sensor approaches), the processing strategy (i.e., data-driven, model-driven, or hybrid), or the amount of user interaction (i.e., manual, semiautomatic, or fully automated). While it is obvious that 3D building models are important components for many applications, they still lack the economical and automatic techniques for their generation while taking advantage of the available multi-sensory data and combining processing strategies. In this research, an automatic methodology for building modelling by integrating multiple images and LiDAR data is proposed. The objective of this research work is to establish a framework for automatic building generation by integrating data driven and model-driven approaches while combining the advantages of image and LiDAR datasets.

  14. Design of an integrated aerial image sensor

    NASA Astrophysics Data System (ADS)

    Xue, Jing; Spanos, Costas J.

    2005-05-01

    The subject of this paper is a novel integrated aerial image sensor (IAIS) system suitable for integration within the surface of an autonomous test wafer. The IAIS could be used as a lithography processing monitor, affording a "wafer's eye view" of the process, and therefore facilitating advanced process control and diagnostics without integrating (and dedicating) the sensor to the processing equipment. The IAIS is composed of an aperture mask and an array of photo-detectors. In order to retrieve nanometer scale resolution of the aerial image with a practical photo-detector pixel size, we propose a design of an aperture mask involving a series of spatial phase "moving" aperture groups. We demonstrate a design example aimed at the 65nm technology node through TEMPEST simulation. The optimized, key design parameters include an aperture width in the range of 30nm, aperture thickness in the range of 70nm, and offer a spatial resolution of about 5nm, all with comfortable fabrication tolerances. Our preliminary simulation work indicates the possibility of the IAIS being applied to the immersion lithography. A bench-top far-field experiment verifies that our approach of the spatial frequency down-shift through forming large Moire patterns is feasible.

  15. 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

  16. 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.

  17. Aerial Measuring System Sensor Modeling

    SciTech Connect

    R. S. Detwiler

    2002-04-01

    This project deals with the modeling the Aerial Measuring System (AMS) fixed-wing and rotary-wing sensor systems, which are critical U.S. Department of Energy's National Nuclear Security Administration (NNSA) Consequence Management assets. The fixed-wing system is critical in detecting lost or stolen radiography or medical sources, or mixed fission products as from a commercial power plant release at high flying altitudes. The helicopter is typically used at lower altitudes to determine ground contamination, such as in measuring americium from a plutonium ground dispersal during a cleanup. Since the sensitivity of these instruments as a function of altitude is crucial in estimating detection limits of various ground contaminations and necessary count times, a characterization of their sensitivity as a function of altitude and energy is needed. Experimental data at altitude as well as laboratory benchmarks is important to insure that the strong effects of air attenuation are modeled correctly. The modeling presented here is the first attempt at such a characterization of the equipment for flying altitudes. The sodium iodide (NaI) sensors utilized with these systems were characterized using the Monte Carlo N-Particle code (MCNP) developed at Los Alamos National Laboratory. For the fixed wing system, calculations modeled the spectral response for the 3-element NaI detector pod and High-Purity Germanium (HPGe) detector, in the relevant energy range of 50 keV to 3 MeV. NaI detector responses were simulated for both point and distributed surface sources as a function of gamma energy and flying altitude. For point sources, photopeak efficiencies were calculated for a zero radial distance and an offset equal to the altitude. For distributed sources approximating an infinite plane, gross count efficiencies were calculated and normalized to a uniform surface deposition of 1 {micro}Ci/m{sup 2}. The helicopter calculations modeled the transport of americium-241 ({sup 241}Am

  18. 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...

  19. Aerial image retargeting (AIR): achieving litho-friendly designs

    NASA Astrophysics Data System (ADS)

    Yehia Hamouda, Ayman; Word, James; Anis, Mohab; Karim, Karim S.

    2011-04-01

    In this work, we present a new technique to detect non-Litho-Friendly design areas based on their Aerial Image signature. The aerial image is calculated for the litho target (pre-OPC). This is followed by the fixing (retargeting) the design to achieve a litho friendly OPC target. This technique is applied and tested on 28 nm metal layer and shows a big improvement in the process window performance. For an optimized Aerial-Image-Retargeting (AIR) recipe is very computationally efficient and its runtime doesn't consume more than 1% of the OPC flow runtime.

  20. 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

  1. Historic Image: Aerial view of Mount of Victory Plot. Photograph ...

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

    Historic Image: Aerial view of Mount of Victory Plot. Photograph 1961. NCA History Collection - Cypress Hills National Cemetery, Mount of Victory Plot Unit, 625 Jamaica Avenue, Brooklyn, Kings County, NY

  2. Optimization and application of Retinex algorithm in aerial image processing

    NASA Astrophysics Data System (ADS)

    Sun, Bo; He, Jun; Li, Hongyu

    2008-04-01

    In this paper, we provide a segmentation based Retinex for improving the visual quality of aerial images obtained under complex weather conditions. With the method, an aerial image will be segmented into different regions, and then an adaptive Gaussian based on the segmentations will be used to process it. The method addresses the problems existing in previously developed Retinex algorithms, such as halo artifacts and graying-out artifacts. The experimental result also shows evidence of its better effect.

  3. Building FAÇADE Separation in Vertical Aerial Images

    NASA Astrophysics Data System (ADS)

    Meixner, P.; Wendel, A.; Bischof, H.; Leberl, F.

    2012-07-01

    Three-dimensional models of urban environments have great appeal and offer promises of interesting applications. While initially it was of interest to just have such 3D data, it increasingly becomes evident that one really would like to have interpreted urban objects. To be able to interpret buildings we have to split a visible whole building block into its different single buildings. Usually this is done using cadastral information to divide the single land parcels. The problem in this case is that sometimes the building boundaries derived from the cadastre are insufficiently accurate due to several reasons like old databases with lower accuracies or inaccuracies due to transformation between two coordinate systems. For this reason it can happen that a cadastral boundary coming from an old map is displaced by up to several meters and therefore divides two buildings incorrectly. To overcome such problems we incorporate the information from vertical aerial images. We introduce a façade separation method that is able to find individual building façades using multi view stereo. The purpose is to identify the individual façades and separate them from one another before on proceeds with the analysis of a façade's details. The source was a set of overlapping, thus "redundant" vertical aerial images taken by an UltraCam digital aerial camera. Therefore in a first step we determine the building block outlines using the building classification and use the height values from the Digital Surface Model (DSM) to determine approximate "façade quadrilaterals". We also incorporate height discontinuities using the height profiles along the building outlines to enhance our façade separation. In a next step we detect repeated pattern in these "façade images" and use them to separate the façades respectively building blocks from one another. We show that this method can be successfully used to separate building façades using vertical aerial images with a very high detection

  4. 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

  5. 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.

  6. Oblique Aerial Images and Their Use in Cultural Heritage Documentation

    NASA Astrophysics Data System (ADS)

    Höhle, J.

    2013-07-01

    Oblique images enable three-dimensional (3d) modelling of objects with vertical dimensions. Such imagery is nowadays systematically taken of cities and may easily become available. The documentation of cultural heritage can take advantage of these sources of information. Two new oblique camera systems are presented and characteristics of such images are summarized. A first example uses images of a new multi-camera system for the derivation of orthoimages, façade plots with photo texture, 3d scatter plots, and dynamic 3d models of a historic church. The applied methodology is based on automatically derived point clouds of high density. Each point will be supplemented with colour and other attributes. The problems experienced in these processes and the solutions to these problems are presented. The applied tools are a combination of professional tools, free software, and of own software developments. Special attention is given to the quality of input images. Investigations are carried out on edges in the images. The combination of oblique and nadir images enables new possibilities in the processing. The use of the near-infrared channel besides the red, green, and blue channel of the applied multispectral imagery is also of advantage. Vegetation close to the object of interest can easily be removed. A second example describes the modelling of a monument by means of a non-metric camera and a standard software package. The presented results regard achieved geometric accuracy and image quality. It is concluded that the use of oblique aerial images together with image-based processing methods yield new possibilities of economic and accurate documentation of tall monuments.

  7. PSM and thin OMOG reticles aerial imaging metrology comparison study

    NASA Astrophysics Data System (ADS)

    Cohen, Yaron; Finders, Jo; Mangan, Shmoolik; Englard, Ilan; Mouraille, Orion; Janssen, Maurice; Miyazaki, Junji; Connolly, Brid; Kojima, Yosuke; Higuchi, Masaru

    2012-02-01

    For sub 20nm features, IC (integrated circuits) designs include an increasing number of features approaching the resolution limits of the scanner compared to the previous generation of IC designs. This trend includes stringent design rules and complex, ever smaller optical proximity correction (OPC) structures. In this regime, a new type of mask, known as opaque MoSi on glass (OMOG), has been introduced to overcome the shortcomings of the well-established phase shift masks (PSM). This paper reviews the fundamental aerial imaging differences between identically designed PSM and thin OMOG masks. The masks were designed for scanner qualification tests and therefore contain large selections of 1D and 2D features, including various biases and OPCs. Aerial critical dimension uniformity (CDU) performance for various features on both masks are reported. Furthermore, special efforts have been made to emphasize the advantages of aerial imaging metrology versus wafer metrology in terms of shortening scanner qualification cycle time.

  8. 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

  9. 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...

  10. 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.

  11. 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.

  12. 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...

  13. Aberration analysis in aerial images formed by lithographic lenses

    NASA Astrophysics Data System (ADS)

    Freitag, Wolfgang; Grossmann, Wilfried; Grunewald, Uwe

    1992-05-01

    A test procedure for the final assembly of lenses that does not need exposed photographic plates is introduced. It is based on the metrological simulation of optical ray tracing. A measuring example illustrates its suitabilty for ultraviolet optical systems in particular. The measuring apparatus displays the distortion vectors directly in the aerial image, gives a wave-front analysis, and performs an analogous distortion analysis.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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…

  1. 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.

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

    PubMed

    Kakeya, Hideki; Ishizuka, Shuta; Sato, Yuya

    2014-10-01

    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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  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. Net-Faim: distributed computation of aerial images

    NASA Astrophysics Data System (ADS)

    Hollerbach, Uwe

    1998-06-01

    Simulation of aerial images is an important part of modern microchip manufacturing, but computation of the image of an entire mask is a challenging problem requiring a large amount of memory and CPU time. Fortunately, it is possible to decompose the large problem of computing the full image into many smaller, mostly independent, sub-problems. In this paper, one particular decomposition is described and implemented. The target platform is a heterogeneous group of networked workstations. The program, net-faim, was designed to be robust, to scale well with available resources, and to place modest demands on participating workstations. All of these design criteria have been realized. The overall performance of the distributed computation is linearly proportional to the sum of the performances of the individual processors, up to a rather high level of parallelism. Robustness is achieved by not relying on any one server to complete a given task; instead, if an idle server is available, the task is sent out to the idle server even if it has previously been sent to another server. The task is only retired when a server returns the completed answer. This 'paranoid' method of processing tasks has the pleasant side effect of doing automatic dynamic load balancing. The results of runs with several different configurations, both of participating workstations and of sub- domain sizes, are displayed.

  9. A scheduling model for the aerial relay system

    NASA Technical Reports Server (NTRS)

    Ausrotas, R. A.; Liu, E. W.

    1980-01-01

    The ability of the Aerial Relay System to handle the U.S. transcontinental large hub passenger flow was analyzed with a flexible, interactive computer model. The model incorporated city pair time of day demand and a demand allocation function which assigned passengers to their preferred flights.

  10. Overview of meteorological measurements for aerial spray modeling.

    PubMed

    Rafferty, J E; Biltoft, C A; Bowers, J F

    1996-06-01

    The routine meteorological observations made by the National Weather Service have a spatial resolution on the order of 1,000 km, whereas the resolution needed to conduct or model aerial spray applications is on the order of 1-10 km. Routinely available observations also do not include the detailed information on the turbulence and thermal structure of the boundary layer that is needed to predict the transport, dispersion, and deposition of aerial spray releases. This paper provides an overview of the information needed to develop the meteorological inputs for an aerial spray model such as the FSCBG and discusses the different types of instruments that are available to make the necessary measurements.

  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. Vehicle detection from high-resolution aerial images based on superpixel and color name features

    NASA Astrophysics Data System (ADS)

    Chen, Ziyi; Cao, Liujuan; Yu, Zang; Chen, Yiping; Wang, Cheng; Li, Jonathan

    2016-03-01

    Automatic vehicle detection from aerial images is emerging due to the strong demand of large-area traffic monitoring. In this paper, we present a novel framework for automatic vehicle detection from the aerial images. Through superpixel segmentation, we first segment the aerial images into homogeneous patches, which consist of the basic units during the detection to improve efficiency. By introducing the sparse representation into our method, powerful classification ability is achieved after the dictionary training. To effectively describe a patch, the Histogram of Oriented Gradient (HOG) is used. We further propose to integrate color information to enrich the feature representation by using the color name feature. The final feature consists of both HOG and color name based histogram, by which we get a strong descriptor of a patch. Experimental results demonstrate the effectiveness and robust performance of the proposed algorithm for vehicle detection from aerial 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. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Aerial imaging study of the mask-induced line-width roughness of EUV lithography masks

    NASA Astrophysics Data System (ADS)

    Wojdyla, Antoine; Donoghue, Alexander; Benk, Markus P.; Naulleau, Patrick P.; Goldberg, Kenneth A.

    2016-03-01

    EUV lithography uses reflective photomasks to print features on a wafer through the formation of an aerial image. The aerial image is influenced by the mask's substrate and pattern roughness and by photon shot noise, which collectively affect the line-width on wafer prints, with an impact on local critical dimension uniformity (LCDU). We have used SHARP, an actinic mask-imaging microscope, to study line-width roughness (LWR) in aerial images at sub-nanometer resolution. We studied the impact of photon density and the illumination partial coherence on recorded images, and found that at low coherence settings, the line-width roughness is dominated by photon noise, while at high coherence setting, the effect of speckle becomes more prominent, dominating photon noise for exposure levels of 4 photons/nm2 at threshold on the mask size.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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...

  7. 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.

  8. A comparison of visual statistics for the image enhancement of FORESITE aerial images with those of major image classes

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

    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 within 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 the 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.

  9. Learning Scene Categories from High Resolution Satellite Image for Aerial Video Analysis

    SciTech Connect

    Cheriyadat, Anil M

    2011-01-01

    Automatic scene categorization can benefit various aerial video processing applications. This paper addresses the problem of predicting the scene category from aerial video frames using a prior model learned from satellite imagery. We show that local and global features in the form of line statistics and 2-D power spectrum parameters respectively can characterize the aerial scene well. The line feature statistics and spatial frequency parameters are useful cues to distinguish between different urban scene categories. We learn the scene prediction model from highresolution satellite imagery to test the model on the Columbus Surrogate Unmanned Aerial Vehicle (CSUAV) dataset ollected by high-altitude wide area UAV sensor platform. e compare the proposed features with the popular Scale nvariant Feature Transform (SIFT) features. Our experimental results show that proposed approach outperforms te SIFT model when the training and testing are conducted n disparate data sources.

  10. Quantitative evaluation of mask phase defects from through-focus EUV aerial images

    SciTech Connect

    Mochi, Iacopo; Yamazoe, Kenji; Neureuther, Andrew; Goldberg, Kenneth A.

    2011-02-21

    Mask defects inspection and imaging is one of the most important issues for any pattern transfer lithography technology. This is especially true for EUV lithography where the wavelength-specific properties of masks and defects necessitate actinic inspection for a faithful prediction of defect printability and repair performance. In this paper we will present a technique to obtain a quantitative characterization of mask phase defects from EUV aerial images. We apply this technique to measure the aerial image phase of native defects on a blank mask, measured with the SEMATECH Berkeley Actinic Inspection Tool (AIT) an EUV zoneplate microscope that operates at Lawrence Berkeley National Laboratory. The measured phase is compared with predictions made from AFM top-surface measurements of those defects. While amplitude defects are usually easy to recognize and quantify with standard inspection techniques like scanning electron microscopy (SEM), defects or structures that have a phase component can be much more challenging to inspect. A phase defect can originate from the substrate or from any level of the multilayer. In both cases its effect on the reflected field is not directly related to the local topography of the mask surface, but depends on the deformation of the multilayer structure. Using the AIT, we have previously showed that EUV inspection provides a faithful and reliable way to predict the appearance of mask defect on the printed wafer; but to obtain a complete characterization of the defect we need to evaluate quantitatively its phase component. While aerial imaging doesn't provide a direct measurement of the phase of the object, this information is encoded in the through focus evolution of the image intensity distribution. Recently we developed a technique that allows us to extract the complex amplitude of EUV mask defects using two aerial images from different focal planes. The method for the phase reconstruction is derived from the Gerchberg-Saxton (GS

  11. 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.

  12. 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.

  13. Building roof segmentation from aerial images using a lineand region-based watershed segmentation technique.

    PubMed

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

    2015-02-02

    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.

  14. An asymmetric re-weighting method for the precision combined bundle adjustment of aerial oblique images

    NASA Astrophysics Data System (ADS)

    Xie, Linfu; Hu, Han; Wang, Jingxue; Zhu, Qing; Chen, Min

    2016-07-01

    Combined bundle adjustment is a fundamental step in the processing of massive oblique images. Traditional bundle adjustment designed for nadir images gives identical weights to different parts of image point observations made from different directions, due to the assumption that the errors in the observations follow the same Gaussian distribution. However, because of their large tilt angles, aerial oblique images have trapezoidal footprints on the ground, and their areas correspond to conspicuously different ground sample distances. The errors in different observations no longer conform to the above assumption, which leads to suboptimal bundle adjustment accuracy and restricts subsequent 3D applications. To model the distribution of the errors correctly for the combined bundle adjustment of oblique images, this paper proposes an asymmetric re-weighting method. The scale of each pixel is used to determine a re-weighting factor, and each pixel is subsequently projected onto the ground to identify another anisotropic re-weighting factor using the shape of its quadrangle. Next, these two factors are integrated into the combined bundle adjustment using asymmetric weights for the image point observations; greater weights are assigned to observations with fine resolutions, and those with coarse resolutions are penalized. This paper analyzes urban and rural images captured by three different five-angle camera systems, from both proprietary datasets and the ISPRS/EuroSDR benchmark. The results reveal that the proposed method outperforms the traditional method in both back-projected and triangulated precision by approximately 5-10% in most cases. Furthermore, the misalignments of point clouds generated by the different cameras are significantly alleviated after combined bundle adjustment.

  15. 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.

  16. 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 ...

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Increased productivity of repair verification by offline analysis of aerial images

    NASA Astrophysics Data System (ADS)

    Villa, Ernesto; Sartelli, Luca; Miyashita, Hiroyuki; Scheruebl, Thomas; Richter, Rigo; Thaler, Thomas

    2010-05-01

    Using AIMSTM to qualify repairs of defects on photomasks is the industry standard. AIMSTM provides a reasonable matching of lithographic imaging performances without the need of wafer prints. The need of utilisation of this capability by photomask manufacturers has risen due to the increased complexity of layouts incorporating aggressive RET and phase shift technologies as well as tighter specifications have pushed aerial image metrology to consider CD performance results in addition to the traditional intensity verification. The content of the paper describes the utilisation of the AIMSTM Repair Verification (RV) software for the verification of aerial images in a mask shop production environment. The software is used to analyze images from various AIMSTM tool generations and the two main routines, Multi Slice Analysis (MSA) and Image Compare (IC), are used to compare defective and non-defective areas of aerial images. It is detailed how the RV software cleans "non real" errors potentially induced by operator misjudgements, thus providing accurate and repeatable analyses all proven against the results achieved manually. A user friendly GUI drives the user through few simple, fast and safe operations and automatically provides summary tables containing all the relevant results of the analysis that can be easily exported in a proper format and sent out to the customer as a technical documentation. This results in a sensible improvement of the throughput of the printability evaluation process in a mask manufacturing environment, providing reliable analyses at a higher productivity.

  2. 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

  3. 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

  4. 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.

  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. Comparison of Digital Surface Models for Snow Depth Mapping with Uav and Aerial Cameras

    NASA Astrophysics Data System (ADS)

    Boesch, R.; Bühler, Y.; Marty, M.; Ginzler, C.

    2016-06-01

    Photogrammetric workflows for aerial images have improved over the last years in a typically black-box fashion. Most parameters for building dense point cloud are either excessive or not explained and often the progress between software releases is poorly documented. On the other hand, development of better camera sensors and positional accuracy of image acquisition is significant by comparing product specifications. This study shows, that hardware evolutions over the last years have a much stronger impact on height measurements than photogrammetric software releases. Snow height measurements with airborne sensors like the ADS100 and UAV-based DSLR cameras can achieve accuracies close to GSD * 2 in comparison with ground-based GNSS reference measurements. Using a custom notch filter on the UAV camera sensor during image acquisition does not yield better height accuracies. UAV based digital surface models are very robust. Different workflow parameter variations for ADS100 and UAV camera workflows seem to have only random effects.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. A Semi-Automated Single Day Image Differencing Technique to Identify Animals in Aerial Imagery

    PubMed Central

    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. PMID:24454827

  13. A supervised method for object-based 3D building change detection on aerial stereo images

    NASA Astrophysics Data System (ADS)

    Qin, R.; Gruen, A.

    2014-08-01

    There is a great demand for studying the changes of buildings over time. The current trend for building change detection combines the orthophoto and DSM (Digital Surface Models). The pixel-based change detection methods are very sensitive to the quality of the images and DSMs, while the object-based methods are more robust towards these problems. In this paper, we propose a supervised method for building change detection. After a segment-based SVM (Support Vector Machine) classification with features extracted from the orthophoto and DSM, we focus on the detection of the building changes of different periods by measuring their height and texture differences, as well as their shapes. A decision tree analysis is used to assess the probability of change for each building segment and the traffic lighting system is used to indicate the status "change", "non-change" and "uncertain change" for building segments. The proposed method is applied to scanned aerial photos of the city of Zurich in 2002 and 2007, and the results have demonstrated that our method is able to achieve high detection accuracy.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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. PMID:22368479

  5. 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.

  6. Analyzing Spectral Characteristics of Shadow Area from ADS-40 High Radiometric Resolution Aerial Images

    NASA Astrophysics Data System (ADS)

    Hsieh, Yi-Ta; Wu, Shou-Tsung; Chen, Chaur-Tzuhn; Chen, Jan-Chang

    2016-06-01

    The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolution aerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i) The DN values in shadow area are much lower than in nonshadow area; (ii) DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii) The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv) The shadow area NIR of vegetation category also shows a strong reflection; (v) Generally, vegetation indexes (NDVI) still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40) is potential for the extract land cover information of shadow areas.

  7. Extracting Semantically Annotated 3d Building Models with Textures from Oblique Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Frommholz, D.; Linkiewicz, M.; Meissner, H.; Dahlke, D.; Poznanska, A.

    2015-03-01

    This paper proposes a method for the reconstruction of city buildings with automatically derived textures that can be directly used for façade element classification. Oblique and nadir aerial imagery recorded by a multi-head camera system is transformed into dense 3D point clouds and evaluated statistically in order to extract the hull of the structures. For the resulting wall, roof and ground surfaces high-resolution polygonal texture patches are calculated and compactly arranged in a texture atlas without resampling. The façade textures subsequently get analyzed by a commercial software package to detect possible windows whose contours are projected into the original oriented source images and sparsely ray-casted to obtain their 3D world coordinates. With the windows being reintegrated into the previously extracted hull the final building models are stored as semantically annotated CityGML "LOD-2.5" objects.

  8. 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.

  9. Fractal methods for extracting artificial objects from the unmanned aerial vehicle images

    NASA Astrophysics Data System (ADS)

    Markov, Eugene

    2016-04-01

    Unmanned aerial vehicles (UAVs) have become used increasingly in earth surface observations, with a special interest put into automatic modes of environmental control and recognition of artificial objects. Fractal methods for image processing well detect the artificial objects in digital space images but were not applied previously to the UAV-produced imagery. Parameters of photography, on-board equipment, and image characteristics differ considerably for spacecrafts and UAVs. Therefore, methods that work properly with space images can produce different results for the UAVs. In this regard, testing the applicability of fractal methods for the UAV-produced images and determining the optimal range of parameters for these methods represent great interest. This research is dedicated to the solution of this problem. Specific features of the earth's surface images produced with UAVs are described in the context of their interpretation and recognition. Fractal image processing methods for extracting artificial objects are described. The results of applying these methods to the UAV images are presented.

  10. 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.

  11. Aerial imaging technology for photomask qualification: from a microscope to a metrology tool

    NASA Astrophysics Data System (ADS)

    Garetto, Anthony; Scherübl, Thomas; Peters, Jan Hendrik

    2012-09-01

    Photomasks carry the structured information of the chip designs printed with lithography scanners onto wafers. These structures, for the most modern technologies, are enlarged by a factor of 4 with respect to the final circuit design, and 20-60 of these photomasks are needed for the production of a single completed chip used, for example, in computers or cell phones. Lately, designs have been reported to be on the drawing board with close to 100 of these layers. Each of these photomasks will be reproduced onto the wafer several hundred times and typically 5000-50 000 wafers will be produced with each of them. Hence, the photomasks need to be absolutely defect-free to avoid any fatal electrical shortcut in the design or drastic performance degradation. One well-known method in the semiconductor industry is to analyze the aerial image of the photomask in a dedicated tool referred to as Aerial Imaging Measurement System, which emulates the behavior of the respective lithography scanner used for the imaging of the mask. High-end lithography scanners use light with a wavelength of 193 nm and high numerical apertures (NAs) of 1.35 utilizing a water film between the last lens and the resist to be illuminated (immersion scanners). Complex illumination shapes enable the imaging of structures well below the wavelength used. Future lithography scanners will work at a wavelength of 13.5 nm [extreme ultraviolet (EUV)] and require the optical system to work with mirrors in vacuum instead of the classical lenses used in current systems. The exact behavior of these systems is emulated by the Aerial Image Measurement System (AIMS™; a Trademark of Carl Zeiss). With these systems, any position of the photomask can be imaged under the same illumination condition used by the scanners, and hence, a prediction of the printing behavior of any structure can be derived. This system is used by mask manufacturers in their process flow to review critical defects or verify defect repair

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Low cost 3D-modelling of a complex archaeological site using aerial photography in the hinterland of Petra, Jordan

    NASA Astrophysics Data System (ADS)

    Emaus, R.; Goossens, R.

    2015-02-01

    Individual archaeological sites can sometimes show a complex morphology. One such site is the Roman quarries located one kilometre northwest of the Roman fortress at Udhruh, in the hinterland of Petra. In archaeology there are various platforms such as balloons, kites and unmanned aerial vehicles (uav's) from which low altitude aerial photographs can be taken that have been proven to work. All with their specific advantages above others in different circumstances. By designing a very distinct setup for the kite and optimizing the workflow accordingly, an effective and steady platform for the camera was created. The Quarries were photographed from the air and the images then provided enough material to accurately create a 3D model of the site.

  17. 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.

  18. Three-dimensional building roof boundary extraction using high-resolution aerial image and LiDAR data

    NASA Astrophysics Data System (ADS)

    Dal Poz, A. P.; Fazan, Antonio J.

    2014-10-01

    This paper presents a semiautomatic method for rectilinear building roof boundary extraction, based on the integration of high-resolution aerial image and LiDAR (Light Detection and Ranging) data. The proposed method is formulated as an optimization problem, in which a snakes-based objective function is developed to represent the building roof boundaries in an object-space coordinate system. Three-dimensional polylines representing building roof boundaries are obtained by optimizing the objective function using the dynamic programming optimization technique. The results of our experiments showed that the proposed method satisfactorily performed the task of extracting different building roof boundaries from aerial image and LiDAR data.

  19. Multi-Scale Matching for the Automatic Location of Control Points in Large Scale Aerial Images Using Terrestrial Scenes

    NASA Astrophysics Data System (ADS)

    Berveglieri, A.; Tommaselli, A. M. G.

    2014-03-01

    A technique to automatically locate Ground Control Points (GCPs) in large aerial images is presented considering the availability of low accuracy direct georeferencing data. The approach is based on image chips of GCPs extracted from vertical terrestrial images. A strategy combining image matching techniques was implemented to select correct matches. These matches were used to define a 2D transformation with which the GCP is projected close to its correct position, reducing the search space in the aerial image. Area-based matching with some refinements is used to locate GCPs with sub-pixel precision. Experiments were performed with multi-scale images and assessed with a bundle block adjustment simulating an indirect sensor orientation. The accuracy analysis was accomplished based on discrepancies obtained from GCPs and check points. The results were better than interactive measurements and a planimetric accuracy of 1/5 of the Ground Sample Distance (GSD) for the check points was achieved.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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...

  8. 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...

  9. A Non-destructive Imaging Method for Detecting Defect in Mortal Sample by High-intensity Aerial Ultrasonic Wave

    NASA Astrophysics Data System (ADS)

    Osumi, Ayumu; Ito, Youichi

    We have studied a method of non-contact ultrasonic inspection that uses high-intensity aerial ultrasonic waves and optical equipment. Specially, the object is excited in noncontact way using high-intensity aerial ultrasonic waves and the vibration velocity on the object surface is measured with a laser Doppler vibrometer (LDV). We analysis the vibration information on the surface of the object with the defect area and image the defect shape in materials. In this paper, it was examined to detect the defect in mortal by proposed method.

  10. 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.

  11. Multimodal detection of man-made objects in simulated aerial images

    NASA Astrophysics Data System (ADS)

    Baran, Matthew S.; Tutwiler, Richard L.; Natale, Donald J.; Bassett, Michael S.; Harner, Matthew P.

    2013-05-01

    This paper presents an approach to multi-modal detection of man-made objects from aerial imagery. Detections are made in polarization imagery, hyperspectral imagery, and LIDAR point clouds then fused into a single confidence map. The detections are based on reflective, spectral, and geometric features of man-made objects in airborne images. The polarization imagery detector uses the Stokes parameters and the degree of linear polarization to find highly polarizing objects. The hyperspectral detector matches scene spectra to a library of man-made materials using a combination of the spectral gradient angle and the generalized likelihood ratio test. The LIDAR detector clusters 3D points into objects using principle component analysis and prunes the detections by size and shape. Once the three channels are mapped into detection images, the information can be fused without some of the problems of multi-modal fusion, such as edge reversal. The imagery used in this system was simulated with a first-principles ray tracing image generator known as DIRSIG.

  12. 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

  13. 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

  14. Integrating aerial geophysical data in multiple-point statistics simulations to assist groundwater flow models

    NASA Astrophysics Data System (ADS)

    Dickson, Neil E. M.; Comte, Jean-Christophe; Renard, Philippe; Straubhaar, Julien A.; McKinley, Jennifer M.; Ofterdinger, Ulrich

    2015-08-01

    The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by low-permeability volcanic dykes in Northern Ireland, UK. The use of two two-dimensional bivariate training images aids in creating spatial probability distributions of heterogeneities of hydrogeological interest, despite relatively `noisy' magnetics data (i.e. including hydrogeologically irrelevant urban noise and regional geologic effects). These distributions are incorporated into a hierarchy system where previously published density function and upscaling methods are applied to derive regional distributions of equivalent hydraulic conductivity tensor K. Several K models, as determined by several stochastic realisations of MPS dyke locations, are computed within groundwater flow models and evaluated by comparing modelled heads with field observations. Results show a significant improvement in model calibration when compared to a simplistic homogeneous and isotropic aquifer model that does not account for the dyke occurrence evidenced by airborne magnetic data. The best model is obtained when normal and reverse polarity dykes are computed separately within MPS simulations and when a probability threshold of 0.7 is applied. The presented stochastic approach also provides improvement when compared to a previously published deterministic anisotropic model based on the unprocessed (i.e. noisy) airborne magnetics. This demonstrates the potential of coupling MPS to airborne geophysical data for regional groundwater modelling.

  15. Use of Aerial Images for Regular Updates of Buildings in the Fundamental Base of Geographic Data of the Czech Republic

    NASA Astrophysics Data System (ADS)

    Hron, V.; Halounova, L.

    2015-03-01

    Digital aerial images (DAI) include position, elevation and also spectral information (visible bands and near-infrared band) about the captured area. The aim of this paper is to present the possibilities of automatic analysis of DAI for updating of the Fundamental Base of Geographic Data of the Czech Republic with a focus on buildings. Regular updates of buildings (automatic detection of new and demolished buildings) are based on the analysis of coloured point clouds created by an automatic image matching technique from each time period. The created approach compares point clouds from different time periods to each other. The advantage of this solution is that it is independent of the manner of keeping the buildings in the database. It does not matter whether the buildings in the database have correct positions and their footprints correspond to the roof shapes or external walls. The involved method is robust because a digital surface model generated by image matching techniques can contain numerous errors. Shaded areas and objects with blurred textures are problematic for automatic image correlation algorithms and lead to false results. For this reason, derived layers containing additional information are used. Shadow masks (layers with modelled shadows) are used for the verification of indications and to filter out errors in the shaded areas using a contextual evaluation. Furthermore, additional information about the road and railway networks and morphological operations of opening and closing were used to achieve more accurate results. All these information sources are then evaluated using decision logic, which uses the generally applicable rules that are available for different datasets without the need for modification. The method was tested on different datasets with various types of buildings (villages, suburbs and city centres) which cover more than 20 square kilometres. The developed solution leads to very promising results without the need of acquiring

  16. Mass image data storage system for high resolution aerial photographic survey

    NASA Astrophysics Data System (ADS)

    Zen, Luan; Tan, Jiubin; Zhao, Zhongwen

    2008-10-01

    In order to make it possible for an image data acquisition and storage system used for aerial photographic survey to have a continuous storage speed of 144 MB/s and data storage capacity of 260GB, three main problems have been solved in this paper. First, with multi-channel synchronous DMA transfer, parallel data storage of four SCSI hard disks is realized. It solved the problem of the data transfer rate too high for direct storage. Then, to increase the data transfer rate, a high speed BUS based on LVDS and a SCSI control circuit based on FAS368M were designed. It solved the problem of PCI BUS limiting the storage speed. Finally, the problem of the SCSI hard disk continuous storage speed declining led by much time interval between two DMA transfers is solved by optimizing DMA channel. The practical system test shows that the acquisition and storage system has a continuous storage speed of 150 MB/s and a data storage capacity of 280GB. Therefore, it is a new storage method for high speed and mass image data.

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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

  3. Three-dimensional imaging applications in Earth Sciences using video data acquired from an unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    McLeod, Tara

    For three dimensional (3D) aerial images, unmanned aerial vehicles (UAVs) are cheaper to operate and easier to fly than the typical manned craft mounted with a laser scanner. This project explores the feasibility of using 2D video images acquired with a UAV and transforming them into 3D point clouds. The Aeryon Scout -- a quad-copter micro UAV -- flew two missions: the first at York University Keele campus and the second at the Canadian Wollastonite Mine Property. Neptec's ViDAR software was used to extract 3D information from the 2D video using structure from motion. The resulting point clouds were sparsely populated, yet captured vegetation well. They were used successfully to measure fracture orientation in rock walls. Any improvement in the video resolution would cascade through the processing and improve the overall results.

  4. 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

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

    PubMed

    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

  6. Miniaturization of high spectral spatial resolution hyperspectral imagers on unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Hill, Samuel L.; Clemens, Peter

    2015-06-01

    Traditional airborne environmental monitoring has frequently deployed hyperspectral imaging as a leading tool for characterizing and analyzing a scene's critical spectrum-based signatures for applications in agriculture genomics and crop health, vegetation and mineral monitoring, and hazardous material detection. As the acceptance of hyperspectral evaluation grows in the airborne community, there has been a dramatic trend in moving the technology from use on midsize aircraft to Unmanned Aerial Systems (UAS). The use of UAS accomplishes a number of goals including the reduction in cost to run multiple seasonal evaluations over smaller but highly valuable land-areas, the ability to use frequent data collections to make rapid decisions on land management, and the improvement of spatial resolution by flying at lower altitudes (<500 ft.). Despite this trend, there are several key parameters affecting the use of traditional hyperspectral instruments in UAS with payloads less than 10 lbs. where size, weight and power (SWAP) are critical to how high and how far a given UAS can fly. Additionally, on many of the light-weight UAS, users are frequently trying to capture data from one or more instruments to augment the hyperspectral data collection, thus reducing the amount of SWAP available to the hyperspectral instrumentation. The following manuscript will provide an analysis on a newly-developed miniaturized hyperspectral imaging platform, the Nano-Hyperspec®, which provides full hyperspectral resolution and traditional hyperspectral capabilities without sacrificing performance to accommodate the decreasing SWAP of smaller and smaller UAS platforms. The analysis will examine the Nano-Hyperspec flown in several UAS airborne environments and the correlation of the systems data with LiDAR and other GIS datasets.

  7. 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

  8. 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.

  9. 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).

  10. Semi-Automated Classification of Gray Scale Aerial Photographs using Geographic Object Based Image Analysis (GEOBIA) Technique

    NASA Astrophysics Data System (ADS)

    Harb Rabia, Ahmed; Terribile, Fabio

    2013-04-01

    Aerial photography is an important source of high resolution remotely sensed data. Before 1970, aerial photographs were the only remote sensing data source for land use and land cover classification. Using these old aerial photographs improve the final output of land use and land cover change detection. However, classic techniques of aerial photographs classification like manual interpretation or screen digitization require great experience, long processing time and vast effort. A new technique needs to be developed in order to reduce processing time and effort and to give better results. Geographic object based image analysis (GEOBIA) is a newly developed area of Geographic Information Science and remote sensing in which automatic segmentation of images into objects of similar spectral, temporal and spatial characteristics is undertaken. Unlike pixel-based technique, GEOBIA deals with the object properties such as texture, square fit, roundness and many other properties that can improve classification results. GEOBIA technique can be divided into two main steps; segmentation and classification. Segmentation process is grouping adjacent pixels into objects of similar spectral and spatial characteristics. Classification process is assigning classes to the generated objects based on the characteristics of the individual objects. This study aimed to use GEOBIA technique to develop a novel approach for land use and land cover classification of aerial photographs that saves time and effort and gives improved results. Aerial photographs from 1954 of Valle Telesina in Italy were used in this study. Images were rectified and georeferenced in Arcmap using topographic maps. Images were then processed in eCognition software to generate land use and land cover map of 1954. A decision tree rule set was developed in eCognition to classify images and finally nine classes of general land use and land cover in the study area were recognized (forest, trees stripes, agricultural

  11. 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.

  12. High-resolution Brillouin analysis in a carbon-fiber-composite unmanned aerial vehicle model wing

    NASA Astrophysics Data System (ADS)

    Stern, Yonatan; London, Yosef; Preter, Eyal; Antman, Yair; Shlomi, Orel; Silbiger, Maayan; Adler, Gadi; Zadok, Avi

    2016-05-01

    Standard optical fibers are successfully embedded within a model wing of an unmanned aerial vehicle, constructed of carbon fiber and epoxy, during its production. Time-gated Brillouin optical correlation domain analysis along the embedded optical fibers is performed with a spatial resolution of 4 cm. Tests were carried out using a portable measurement setup prototype. The results represent an important step towards applications of high-resolution Brillouin analysis outside the research laboratory.

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. Terrestrial and unmanned aerial system imagery for deriving photogrammetric three-dimensional point clouds and volume models of mass wasting sites

    NASA Astrophysics Data System (ADS)

    Hämmerle, Martin; Schütt, Fabian; Höfle, Bernhard

    2016-04-01

    Three-dimensional (3-D) geodata of mass wasting sites are important to model surfaces, volumes, and their changes over time. With a photogrammetric approach commonly known as structure from motion, 3-D point clouds can be derived from image collections in a straightforward way. The quality of point clouds covering a quarry dump derived from terrestrial and aerial imagery is compared and assessed. A comprehensive set of quality indicators is calculated and compared to surveyed reference data and to a terrestrial LiDAR point cloud. The examined indicators are completeness of coverage, point density, vertical accuracy, multiscale point cloud distance, scaling accuracy, and dump volume. It is found that the photogrammetric datasets generally represent the examined dump well with, for example, an area coverage of up to 90% and 100% in case of terrestrial and aerial imagery, respectively, a maximum scaling difference of 0.62%, and volume estimations reaching up to 100% of the LiDAR reference. Combining the advantages of 3-D geodata derived from terrestrial (high detail, accurate volume calculation even with a small number of input images) and aerial images (high coverage) can be a promising method to further improve the quality of 3-D geodata derived with low-cost approaches.

  18. Comparative evaluation of iterative and non-iterative methods to ground coordinate determination from single aerial images

    NASA Astrophysics Data System (ADS)

    Sheng, Yongwei

    2004-04-01

    The single-ray backprojection problem refers to the process of determining ground coordinates of pixels in a single aerial image with the support of a digital surface model or a digital elevation model. Several methods have been employed to solve this problem. The iterative photogrammetric (IP) method, based on the inverse collinearity equations, is widely used in photogrammetry. The ray-tracing (RT) method, which is popular in computer graphics, computes the coordinates by intersecting the view ray with the surface. A third one is an iterative ray-tracing (IRT) method, which finds the intersection point by extending the view ray towards the surface by a certain step once a time until it hits the surface. Since the methods become diversified, there is a need to compare and evaluate them. This paper analyzes the principles of these three methods, tests them using a variety of data sets, and provides a comprehensive comparison on their strategies, parameter selection, divergence, occlusion-compliance, precision, robustness, and efficiency. The major difference of these methods is in the strategy of computing the intersection between the view ray and the surface, and this leads to their varied performance. It is found that the IP method is the most computationally efficient and can produce precise coordinates for simple surfaces, but it may surfer from the divergence and occlusion-induced problems for complicated ones. The rigorous RT method is precise, occlusion-compliant and parameter-free, but it is computationally intensive. The IRT method is intermediate in terms of efficiency. If the initial step is small enough, it can adequately address the occlusion-induced problem and produce satisfactory coordinates for complicated surfaces. This comparison provides a guide to method selection for the single-ray backprojection problem.

  19. Robust image reconstruction enhancement based on Gaussian mixture model estimation

    NASA Astrophysics Data System (ADS)

    Zhao, Fan; Zhao, Jian; Han, Xizhen; Wang, He; Liu, Bochao

    2016-03-01

    The low quality of an image is often characterized by low contrast and blurred edge details. Gradients have a direct relationship with image edge details. More specifically, the larger the gradients, the clearer the image details become. Robust image reconstruction enhancement based on Gaussian mixture model estimation is proposed here. First, image is transformed to its gradient domain, obtaining the gradient histogram. Second, the gradient histogram is estimated and extended using a Gaussian mixture model, and the predetermined function is constructed. Then, using histogram specification technology, the gradient field is enhanced with the constraint of the predetermined function. Finally, a matrix sine transform-based method is applied to reconstruct the enhanced image from the enhanced gradient field. Experimental results show that the proposed algorithm can effectively enhance different types of images such as medical image, aerial image, and visible image, providing high-quality image information for high-level processing.

  20. 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

  1. 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...

  2. Self-calibration of digital aerial camera using combined orthogonal models

    NASA Astrophysics Data System (ADS)

    Babapour, Hadi; Mokhtarzade, Mehdi; Valadan Zoej, Mohamad Javad

    2016-07-01

    The emergence of new digital aerial cameras and the diverse design and technology used in this type of cameras require in-situ calibration. Self-calibration methods, e.g. the Fourier model, are primarily used; however, additional parameters employed in such methods have not yet met the expectations to desirably model the complex multiple distortions existing in the digital aerial cameras. The present study proposes the Chebyshev-Fourier (CHF) and Jacobi-Fourier (JF) combined orthogonal models. The models are evaluated for the multiple distortions using both simulated and real data, the latter being derived from an UltraCam digital camera. The results indicate that the JF model is superior to the other methods where, e.g., in the UltraCam scenario, it improves the planimetric and vertical accuracy over the Fourier model by 18% and 22%, respectively. Furthermore, a 30% and 16% of reduction in external and internal correlation is obtained via this approach which is very promising.

  3. 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

  4. 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

  5. Roughness Estimation from Point Clouds - A Comparison of Terrestrial Laser Scanning and Image Matching by Unmanned Aerial Vehicle Acquisitions

    NASA Astrophysics Data System (ADS)

    Rutzinger, Martin; Bremer, Magnus; Ragg, Hansjörg

    2013-04-01

    Recently, terrestrial laser scanning (TLS) and matching of images acquired by unmanned arial vehicles (UAV) are operationally used for 3D geodata acquisition in Geoscience applications. However, the two systems cover different application domains in terms of acquisition conditions and data properties i.e. accuracy and line of sight. In this study we investigate the major differences between the two platforms for terrain roughness estimation. Terrain roughness is an important input for various applications such as morphometry studies, geomorphologic mapping, and natural process modeling (e.g. rockfall, avalanche, and hydraulic modeling). Data has been collected simultaneously by TLS using an Optech ILRIS3D and a rotary UAV using an octocopter from twins.nrn for a 900 m² test site located in a riverbed in Tyrol, Austria (Judenbach, Mieming). The TLS point cloud has been acquired from three scan positions. These have been registered using iterative closest point algorithm and a target-based referencing approach. For registration geometric targets (spheres) with a diameter of 20 cm were used. These targets were measured with dGPS for absolute georeferencing. The TLS point cloud has an average point density of 19,000 pts/m², which represents a point spacing of about 5 mm. 15 images where acquired by UAV in a height of 20 m using a calibrated camera with focal length of 18.3 mm. A 3D point cloud containing RGB attributes was derived using APERO/MICMAC software, by a direct georeferencing approach based on the aircraft IMU data. The point cloud is finally co-registered with the TLS data to guarantee an optimal preparation in order to perform the analysis. The UAV point cloud has an average point density of 17,500 pts/m², which represents a point spacing of 7.5 mm. After registration and georeferencing the level of detail of roughness representation in both point clouds have been compared considering elevation differences, roughness and representation of different grain

  6. [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.

  7. Urban 3D GIS From LiDAR and digital aerial images

    NASA Astrophysics Data System (ADS)

    Zhou, Guoqing; Song, C.; Simmers, J.; Cheng, P.

    2004-05-01

    This paper presents a method, which integrates image knowledge and Light Detection And Ranging (LiDAR) point cloud data for urban digital terrain model (DTM) and digital building model (DBM) generation. The DBM is an Object-Oriented data structure, in which each building is considered as a building object, i.e., an entity of the building class. The attributes of each building include roof types, polygons of the roof surfaces, height, parameters describing the roof surfaces, and the LiDAR point array within the roof surfaces. Each polygon represents a roof surface of building. This type of data structure is flexible for adding other building attributes in future, such as texture information and wall information. Using image knowledge extracted, we developed a new method of interpolating LiDAR raw data into grid digital surface model (DSM) with considering the steep discontinuities of buildings. In this interpolation method, the LiDAR data points, which are located in the polygon of roof surfaces, first are determined, and then interpolation via planar equation is employed for grid DSM generation. The basic steps of our research are: (1) edge detection by digital image processing algorithms; (2) complete extraction of the building roof edges by digital image processing and human-computer interactive operation; (3) establishment of DBM; (4) generation of DTM by removing surface objects. Finally, we implement the above functions by MS VC++ programming. The outcome of urban 3D DSM, DTM and DBM is exported into urban database for urban 3D GIS.

  8. 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.

  9. 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.

  10. Modeling the distribution of illicit oily discharges detected by aerial surveillance in western Canadian marine waters.

    PubMed

    Serra-Sogas, Norma; O'Hara, Patrick D; Canessa, Rosaline

    2014-10-15

    Oily discharges from vessel operations have been documented in Canada's Pacific region by the National Aerial Surveillance Program (NASP) since the early 1990s. We explored a number of regression methods to explain the distribution and counts per grid cell of oily discharges detected from 1998 to 2007 using independent predictor variables, while trying to address the large number of zeros present in the data. Best-fit models indicate that discharges are generally concentrated close to shore typically in association with small harbours, and with major commercial and tourist centers. Oily discharges were also concentrated in Barkley Sound and at the entrance of Juan de Fuca Strait. The identification of important factors associated with discharge patterns, and predicting discharge rates in areas with surveillance effort can be used to inform future surveillance. Model output can also be used as inputs for risk models for existing conditions and as baseline for future scenarios.

  11. Modeling the distribution of illicit oily discharges detected by aerial surveillance in western Canadian marine waters.

    PubMed

    Serra-Sogas, Norma; O'Hara, Patrick D; Canessa, Rosaline

    2014-10-15

    Oily discharges from vessel operations have been documented in Canada's Pacific region by the National Aerial Surveillance Program (NASP) since the early 1990s. We explored a number of regression methods to explain the distribution and counts per grid cell of oily discharges detected from 1998 to 2007 using independent predictor variables, while trying to address the large number of zeros present in the data. Best-fit models indicate that discharges are generally concentrated close to shore typically in association with small harbours, and with major commercial and tourist centers. Oily discharges were also concentrated in Barkley Sound and at the entrance of Juan de Fuca Strait. The identification of important factors associated with discharge patterns, and predicting discharge rates in areas with surveillance effort can be used to inform future surveillance. Model output can also be used as inputs for risk models for existing conditions and as baseline for future scenarios. PMID:25212467

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. Unsupervised and stable LBG algorithm for data classification: application to aerial multicomponent images

    NASA Astrophysics Data System (ADS)

    Taher, A.; Chehdi, K.; Cariou, C.

    2015-10-01

    In this paper a stable and unsupervised Linde-Buzo-Gray (LBG) algorithm named LBGO is presented. The originality of the proposed algorithm relies: i) on the utilization of an adaptive incremental technique to initialize the class centres that calls into question the intermediate initializations; this technique makes the algorithm stable and deterministic, and the classification results do not vary from a run to another, and ii) on the unsupervised evaluation criteria of the intermediate classification result to estimate the optimal number of classes; this makes the algorithm unsupervised. The efficiency of this optimized version of LBG is shown through some experimental results on synthetic and real aerial hyperspectral data. More precisely we have tested our proposed classification approach regarding three aspects: firstly for its stability, secondly for its correct classification rate, and thirdly for the correct estimation of number of classes.

  20. 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.

  1. 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.

  2. 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

  3. Measuring Change in Arctic Coastal Environments Using Repeat Aerial Photography and SfM Elevation Models

    NASA Astrophysics Data System (ADS)

    Gibbs, A.; Nolan, M.; Kinsman, N.; Richmond, B. M.

    2015-12-01

    Aerial- and ground-based photography can provide valuable information about coastal environments in space and time including the presence or absence of shorefast ice, beach characteristics and morphology, high-water indicators produced during storm surge events, bluff failure mechanisms, and habitat identification. Recent advances in digital photogrammetry and construction of Digital Elevation Models (DEM) using Structure-from-Motion (SfM) algorithms allow for improved mapping and analysis of coastal change in 3-dimensions at a relatively low cost. For example, analyses can include delineating shorelines based on a tidal datum, mapping inundation extent based on a known or modeled flood level, or quantifying volumetric change. Repeat aerial surveys and associated orthophoto and DEM construction serve as a powerful monitoring tool that can provide insights into the mechanisms responsible for coastal change. Along the extensive and remote coast of Alaska, high-quality imagery and elevation data are rare, in part because traditional methods of acquiring the data are cost prohibitive. Here we evaluate the usefulness of data sets acquired using small aircraft and SfM techniques for evaluating seasonal change to the beach and permafrost bluffs at Barter Island, Alaska during the summer of 2014. Considerable bluff retreat and morphological change were measured along a 2.7 km stretch of coast with net mean volume loss of approximately 28,000 ± 540 m3 between the top and the base of the bluffs. The pattern of change was dominantly landward retreat of the top of the bluffs and removal of the debris fan at the base of the bluffs. Barrier-spit overwash and migration and deposition of storm berms were also observed and accurately measured. Our results suggest that this is a cost-effective method for mapping coastal change in remote environments leading to a similar data acquisition effort for the State of Alaska, primarily for shoreline and coastal hazard mapping purposes

  4. 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

  5. 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.

  6. Mapping potential of digitized aerial photographs and space images for site-specific crop management

    NASA Astrophysics Data System (ADS)

    Nielsen, Gerald A.; Long, Daniel S.; Queen, Lloyd P.

    1996-11-01

    In site-specific crop management, treatments (e.g., fertilizer and herbicides) are applied precisely where they are needed. Global positioning system receivers allow accurate navigation of field implements and creation of crop yield maps. Remote sensing products help producers explain the wide range of yields shown on these maps and become the basis for digitized field management maps. Previous sources of remote sensing products for agriculture did not provide services that generated a sustained demand by crop producers, often because data were not delivered quickly enough. Public Access Resource Centers could provide a nearly uninterrupted electronic flow of data from NASA's MODIS and other sensors that could help producers and their advisors monitor crop conditions. This early warning/opportunity system would provide a low-cost way to discover conditions that merit examination on the ground. High-spatial-resolution digital aerial photographs or data from new commercial satellite companies would provide the basis for site-specific treatments. These detailed data are too expensive to acquire often and must be timed so as to represent differences in water supply characteristics and crop yield potentials. Remote sensing products must be linked to specific prescriptions that crop produces use to control operations and improve outcomes.

  7. 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.

  8. Monitoring morphological changes in an arid zone by spaceborne images and aerial photography between 1945 - 2009; the Yamin Plateau, Israel

    NASA Astrophysics Data System (ADS)

    Hetz, Guy; Blumberg, Dan; Avraham, Dody; Cohen, Hai

    2010-05-01

    This research focuses on a geomorphic mapping of the Yamin Plateau in southern Israel which is part of the Yamin-Rotem Syncline and covers about 200 km2. This area has been restricted since the 1950s and therefore, provides a unique opportunity to study undisturbed geomorphic processes. Nowadays, the national nuclear waste depository is located in this area accepting waste from industrial factories, research institutes and hospitals. This is the main reason why environmental processes are of major interest in terms of landform changes in space and time. The exposed geology section of the Yamin Plateau mostly consists of the Miocene Hazeva Group where sedimentary processes started 20 million years ago and continued for 12-14 million years. Two formations of the Miocene Hazeva Group appear in the study area Zefa and Rotem. The compositions of these two formations are similar and sometimes defined as "the main sand body" in the Hazeva Group. The restriction of the area stopped the grazing and let the development of a biological soil crust on the surface. The research objective was to document and characterize landform changes from 1945 until 2009 within the Yamin Plateau based on spaceborne images and aerial photography. All the parameters we extracted in the laboratory were validated with field measurements. A combination of the spaceborne images, aerial photography and field measurements leads us to the following conclusions: The research results show that soil stabilization processes took place earlier than the area closure. Inspite of decreasing precipitation tendencies as measured during the last 50 years in Yamin Plateau, the vegetation cover increased from 55% in 1945 to 67% in 2009. The main reason for this is the area closure and reduction in grazing along with developing of vegetation and biological soil crusts. Field studies and image processing of aerial photographs and recent QuickBird images alongside grain-size distribution show that in the past there

  9. 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.

  10. 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.

  11. An aerial composite imaging method with multiple upright cameras based on axis-shift theory

    NASA Astrophysics Data System (ADS)

    Fang, Junyong; Liu, Xue; Xue, Yongqi; Tong, Qingxi

    2010-11-01

    Several composite camera systems were made for wide coverage by using 3 or 4 oblique cameras. A virtual projecting center and image was used for geometrical correction and mosaic with different projecting angles and different spatial resolutions caused by oblique cameras. An imaging method based axis-shift theory is proposed to acquire wide coverage images by several upright cameras. Four upright camera lenses have the same wide angle of view. The optic axis of lens is not on the center of CCD, and each CCD in each camera covers only one part of the whole focus plane. Oblique deformation caused by oblique camera would be avoided by this axis-shift imaging method. The principle and parameters are given and discussed. A prototype camera system is constructed by common DLSR (digital single lens reflex) cameras. The angle of view could exceed 80 degrees along the flight direction when the focal length is 24mm, and the ratio of base line to height could exceed 0.7 when longitudinal overlap is 60%. Some original and mosaic images captured by this prototype system in some ground and airborne experiments are given at last. Experimental results of image test show that the upright imaging method can effectively avoid the oblique deformation and meet the geometrical precision of image mosaic.

  12. A Method for Georeferencing Very-Large-Scale-Aerial (VLSA) Images in Sagebrush Steppe Communities.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    VLSA imagery is captured with a digital camera, mounted on a light, piloted aircraft. VLSA images are high quality and have been used to measure cover of plant functional groups and some species, bare ground, litter, and rock, but the actual image location is known imprecisely (± 30 m). This impreci...

  13. EROS Main Image File: A Picture Perfect Database for Landsat Imagery and Aerial Photography.

    ERIC Educational Resources Information Center

    Jack, Robert F.

    1984-01-01

    Describes Earth Resources Observation System online database, which provides access to computerized images of Earth obtained via satellite. Highlights include retrieval system and commands, types of images, search strategies, other online functions, and interpretation of accessions. Satellite information, sources and samples of accessions, and…

  14. Correlation of Sub-Aerial Beach Change with Numerical Model Derived Nearshore Wave Conditions

    NASA Astrophysics Data System (ADS)

    Hansen, J. E.; Erikson, L.; Barnard, P. L.; Eshleman, J. L.

    2007-12-01

    Wave-induced sediment transport on and off of beaches is difficult to understand and predict without thorough knowledge of the nearshore wave conditions. Wave data is commonly provided by a buoy located offshore in deep water that measures waves prior to shoaling and refraction. Irregular bathymetry causes dissimilar refraction and shoaling and can lead to variable wave conditions in the nearshore environment. To account for wave propagation over varying bathymetry, numerical wave models are good tools for estimating the nearshore wave climate from offshore wave data. Ocean Beach in San Francisco, CA is an energetic, intermediately sloping beach that was the subject of frequent sub-aerial topographic surveys in 2005 and 2006, with some surveys being as close as two days apart. Sediment volume change derived from these surveys was correlated to nearshore wave heights estimated from offshore buoy measurements and the application of the numerical wave model SWAN (Simulating WAves Nearshore). The SWAN model was used to create a "look-up" table of nearshore wave heights from over 4500 combinations of offshore wave heights, periods, and directions. The model was run using a nested grid scheme using three separate spatial resolutions, with the finest being closest to shore. Correlations between the sub-aerial beach volume data at five morphologically different reaches of Ocean Beach and the SWAN derived wave heights from just outside of the surf zone (in 5, 7.5, or 10 m of water depending on wave height) are generally low, with R2 values less than 0.5, with the highest being 0.61. Although the coefficients of determination are low in most instances the significance exceeds 90%. The reason for the low coefficients of determination is not known but is currently being investigated; some possible reasons are improper characterization of the lengthy time series of wave data between surveys (up to 28 days), or the ignored effect of strong along-shore directed tidal currents (O

  15. 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.

  16. 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. PMID:24146963

  17. 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

  18. 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

    2016-01-01

    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

  19. 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.

  20. 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

  1. 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…

  2. 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.

  3. 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.

  4. 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.

  5. Advances in hardware, software, and automation for 193nm aerial image measurement systems

    NASA Astrophysics Data System (ADS)

    Zibold, Axel M.; Schmid, R.; Seyfarth, A.; Waechter, M.; Harnisch, W.; Doornmalen, H. v.

    2005-05-01

    A new, second generation AIMS fab 193 system has been developed which is capable of emulating lithographic imaging of any type of reticles such as binary and phase shift masks (PSM) including resolution enhancement technologies (RET) such as optical proximity correction (OPC) or scatter bars. The system emulates the imaging process by adjustment of the lithography equivalent illumination and imaging conditions of 193nm wafer steppers including circular, annular, dipole and quadrupole type illumination modes. The AIMS fab 193 allows a rapid prediction of wafer printability of critical mask features, including dense patterns and contacts, defects or repairs by acquiring through-focus image stacks by means of a CCD camera followed by quantitative image analysis. Moreover the technology can be readily applied to directly determine the process window of a given mask under stepper imaging conditions. Since data acquisition is performed electronically, AIMS in many applications replaces the need for costly and time consuming wafer prints using a wafer stepper/ scanner followed by CD SEM resist or wafer analysis. The AIMS fab 193 second generation system is designed for 193nm lithography mask printing predictability down to the 65nm node. In addition to hardware improvements a new modular AIMS software is introduced allowing for a fully automated operation mode. Multiple pre-defined points can be visited and through-focus AIMS measurements can be executed automatically in a recipe based mode. To increase the effectiveness of the automated operation mode, the throughput of the system to locate the area of interest, and to acquire the through-focus images is increased by almost a factor of two in comparison with the first generation AIMS systems. In addition a new software plug-in concept is realised for the tools. One new feature has been successfully introduced as "Global CD Map", enabling automated investigation of global mask quality based on the local determination of

  6. 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

    1964-11-01

    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.

  7. 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.

  8. Automated identification of rivers and shorelines in aerial imagery using image texture

    NASA Astrophysics Data System (ADS)

    McKay, Paul; Blain, Cheryl Ann; Linzell, Robert

    2011-06-01

    A method has been developed which automatically extracts river and river bank locations from arbitrarily sourced high resolution (~1m) visual spectrum imagery without recourse to multi-spectral or even color information. This method relies on quantifying the difference in image texture between the relatively smooth surface of the river water and the rougher surface of the vegetated land or built environment bordering it and then segmenting the image into high and low roughness regions. The edges of the low roughness regions then define the river banks. The method can be coded in any language without recourse to proprietary tools and requires minimal operator intervention. As this sort of imagery is increasingly being made freely available through such services as Google Earth or Worldwind this technique can be used to extract river features when more specialized imagery or software is not available.

  9. 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.

  10. EUV pattern defect detection sensitivity based on aerial image linewidth measurements

    SciTech Connect

    Goldberg, K. A.; Mochi, I.; Naulleau, P.; Liang, T.; Yan, P.-Y.; Huh, S.

    2010-02-12

    As the quality of EUV-wavelength mask inspection microscopes improves over time, the image properties and intensity profiles of reflected light can be evaluated in ever-greater detail. The SEMATECH Berkeley Actinic Inspection Tool (AIT) is one such microscope, featuring mask resolution values that match or exceed those available through lithographic printing in current photoresists. In order to evaluate the defect detection sensitivity of the AIT for dense line patterns on typical masks, the authors study the line width roughness (LWR) on two masks, as measured in the EUV images. They report the through-focus and pitch dependence of contrast, image log slope, linewidth, and LWR. The AIT currently reaches LWR 3{sigma} values close to 9 nm for 175 nm half-pitch lines. This value is below 10% linewidth for nearly all lines routinely measured in the AIT. Evidence suggests that this lower level may arise from the mask's inherent pattern roughness. While the sensitivity limit of the AlT has not yet been established, it is clear that the AIT has the required sensitivity to detect defects that cause 10% linewidth changes in line sizes of 125 nm and larger.

  11. Theoretical study for aerial image intensity in resist in high numerical aperture projection optics and experimental verification with one-dimensional patterns

    NASA Astrophysics Data System (ADS)

    Shibuya, Masato; Takada, Akira; Nakashima, Toshiharu

    2016-04-01

    In optical lithography, high-performance exposure tools are indispensable to obtain not only fine patterns but also preciseness in pattern width. Since an accurate theoretical method is necessary to predict these values, some pioneer and valuable studies have been proposed. However, there might be some ambiguity or lack of consensus regarding the treatment of diffraction by object, incoming inclination factor onto image plane in scalar imaging theory, and paradoxical phenomenon of the inclined entrance plane wave onto image in vector imaging theory. We have reconsidered imaging theory in detail and also phenomenologically resolved the paradox. By comparing theoretical aerial image intensity with experimental pattern width for one-dimensional pattern, we have validated our theoretical consideration.

  12. Modelling trends in woody vegetation structure in semi-arid Australia as determined from aerial photography.

    PubMed

    Fensham, Roderick John; Low Choy, Sama J; Fairfax, Russell James; Cavallaro, Paul C

    2003-08-01

    Accounting of carbon stocks in woody vegetation for greenhouse purposes requires definition of medium term trends with accurate error assessment. Tree and shrub cover was sampled through time at randomly located sites over a large area of central Queensland, Australia using aerial photography from 1945 to 1999. Calibration models developed from field data for the same land types as those represented within the study area allowed for the extrapolation of overstorey and understorey cover, basal area and biomass values and these were modelled as trends over the latter half of the 20th century. These structural attributes have declined over the region because of land clearing with values for biomass changing from a mean of 58.0(+/-1.2)t/ha in 1953 to 41.1(+/-1.0)t/ha in 1991. The biomass of Acacia on clay and Eucalypt on texture contrast soils land types has declined most dramatically. Within uncleared vegetation there was an overall trend of increase from 56.1(+/-1.2)t/ha in 1951 to 67.6(+/-1.3)t/ha in 1995. The increase in structural attributes within uncleared vegetation was most pronounced for the Eucalypt on texture contrast soils and Eucalypt on clay land types. It was demonstrated that the sites sampled were representative of their land types and that spatial bias of the photography, undetected tree-killing, sampling error, inherent variability of structural attributes and measurement error should not have impacted greatly on bias or precision of trend estimates for well-sampled land types. Certainly the errors are not likely to be substantial for trends averaged over all land types and they provide an accurate assessment of the magnitude and direction of change. The technique presented here would appear to be a robust means of accounting for the above-ground woody component of woodlands and open forests and will also contribute to a broader understanding of savanna dynamics. PMID:12877875

  13. 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.

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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 ...

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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.

  15. The construction of landslides achieves by using 1969 CORONA (KH-4B) image and aerial photos- A case study of the catchment of Te-chi reservoir

    NASA Astrophysics Data System (ADS)

    Jen, Chia-Hung; Dirk, Wenske; Lin, Jiun-Chuan; Böse, Margot

    2010-05-01

    Taiwan before the construction of the Central Cross-Island Highway. The ortho-rectified CORONA image and aerial photos can be used to identify landslides and provide more information about the causes of landslides and the consequences of road construction, landform evolution and agriculture practice. The long term landslide archive can be used in the study of landscape evolution and hazard assessment. There are more than 800 landslides identified in CORONA image and 900 landslides in 1980 aerial photos, which were caused by road construction, farming practice and channel erosion.

  16. 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.

  17. 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.

  18. 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)

  19. 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.

  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. 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.

  2. Multi-temporal analysis of aerial images for the investigation of spatial-temporal dynamics of shallow erosion - a case study from the Tyrolean Alps

    NASA Astrophysics Data System (ADS)

    Wiegand, C.; Geitner, C.; Heinrich, K.; Rutzinger, M.

    2012-04-01

    Small and shallow eroded areas characterize the landscape of many pastures and meadows in the Alps. The extent of such erosion phenomena varies between 2 m2 and 200 m2. These patches tend to be only a few decimetres thick, with a maximum depth of 2 m. The processes involved are shallow landslides, superficial erosion by snow and livestock trampling. Key parameters that influence the emergence of shallow erosion are the geological, topographical and climatic circumstances in an area as well as its soils, vegetation and land use. The negative impact of this phenomenon includes not only the loss of soil but also the reduced attractiveness of the landscape, especially in tourist regions. One approach identifying and mapping geomorphological elements is remote sensing. The analysis of aerial images is a suitable method for identifying the multi-temporal dynamics of shallow eroded areas because of the good spatial and temporal resolution. For this purpose, we used a pixel-based approach to detect these areas semi-automatically in an orthophoto. In a first step, each aerial image was classified using dynamic thresholds derived from the histogram of the orthophoto. In a second step, the identified areas of erosion were filtered and visually in-terpreted. Based on this procedure, eroded areas with a minimum size of 5 m2 were detected in a test site located in the Inner Schmirn Valley (Tyrol, Austria). The altitude of the test site ranges between 1,980 m and 2,370 m, with a mean inclination of 36°, facing E to SE. Geologically, the slope is part of the "Hohe Tauern Window", characterized by "Bündner schists" deficient in lime and regolith. Until the 1960s, the slope was used as a hay meadow. Orthophotos from 2000, 2003, 2007 and 2010 were used for this investigation. Older aerial images were not suitable because of their lower resolution and poor ortho-rectification. However, they are useful for relating the results of the ten-year time-span to a larger temporal context

  3. Analysis of nanometer-isolated trench diffract aerial image of both conventional and second-generation synchrotron-based proximity x-ray lithography

    NASA Astrophysics Data System (ADS)

    Xie, Changqing; Chen, Dapeng; Liu, Ming; Ye, Tianchun; Yi, Futing

    2005-01-01

    In this paper, Beam Propagation Method (BPM) with Fast Fourier Transforms(FFT) is employed to efficiently calculate the diffract image in the wafer plane for both conventional and second generation synchrotron-based proximity x-ray lithography(PXL). In the simulation, a dark-field isolated space pattern silicon nitride/Ta x-ray mask is used for conventional PXL and a diamond /Ta x-ray mask is used for second generation PXL, the diffract image"s dependency on absorber thickness, mask-wafer gap, effective total blur, linewidth and absorber sidewall slope has been numerically evaluated. For conventional PXL, in order to obtain a isolated trench resolution of 50nm, the mask-wafer gap should be controlled below 5 micron, the optimization condition is mask-wafer gap 5 micron, Ta absorber thickness 300nm, effective total blur 10nm, absorber sidewall slope 3°, the corresponding aerial image contrast is 0.457; For second generation, in order to obtain a isolated trench resolution of 50nm, the mask-wafer gap can be as large as 10 micron. In order to obtain a isolated trench resolution of 35nm, mask-wafer gap should be controlled below 5 micron.

  4. 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.

  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. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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

    2015-01-01

    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

  11. Robust image modeling techniques with an image restoration application

    NASA Astrophysics Data System (ADS)

    Kashyap, Rangasami L.; Eom, Kie-Bum

    1988-08-01

    A robust parameter-estimation algorithm for a nonsymmetric half-plane (NSHP) autoregressive model, where the driving noise is a mixture of a Gaussian and an outlier process, is presented. The convergence of the estimation algorithm is proved. An algorithm to estimate parameters and original image intensity simultaneously from the impulse-noise-corrupted image, where the model governing the image is not available, is also presented. The robustness of the parameter estimates is demonstrated by simulation. Finally, an algorithm to restore realistic images is presented. The entire image generally does not obey a simple image model, but a small portion (e.g., 8 x 8) of the image is assumed to obey an NSHP model. The original image is divided into windows and the robust estimation algorithm is applied for each window. The restoration algorithm is tested by comparing it to traditional methods on several different images.

  12. 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

  13. Fault-Tolerant Trajectory Tracking of Unmanned Aerial Vehicles Using Immunity-Based Model Reference Adaptive Control

    NASA Astrophysics Data System (ADS)

    Wilburn, Brenton K.

    This dissertation presents the design, development, and simulation testing of an adaptive trajectory tracking algorithm capable of compensating for various aircraft subsystem failures and upset conditions. A comprehensive adaptive control framework, here within referred to as the immune model reference adaptive control (IMRAC) algorithm, is developed by synergistically merging core concepts from the biologically- inspired artificial immune system (AIS) paradigm with more traditional optimal and adaptive control techniques. In particular, a model reference adaptive control (MRAC) algorithm is enhanced with the detection and learning capabilities of a novel, artificial neural network augmented AIS scheme. With the given modifications, the MRAC scheme is capable of detecting and identifying a given failure or upset condition, learning how to adapt to the problem, responding in a manner specific to the given failure condition, and retaining the learning parameters for quicker adaptation to subsequent failures of the same nature. The IMRAC algorithm developed in this dissertation is applicable to a wide range of control problems. However, the proposed methodology is demonstrated in simulation for an unmanned aerial vehicle. The results presented show that the IMRAC algorithm is an effective and valuable extension to traditional optimal and adaptive control techniques. The implementation of this methodology can potentially have significant impacts on the operational safety of many complex systems.

  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. Moving Obstacle Avoidance for Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Lin, Yucong

    There has been a vast increase in applications of Unmanned Aerial Vehicles (UAVs) in civilian domains. To operate in the civilian airspace, a UAV must be able to sense and avoid both static and moving obstacles for flight safety. While indoor and low-altitude environments are mainly occupied by static obstacles, risks in space of higher altitude primarily come from moving obstacles such as other aircraft or flying vehicles in the airspace. Therefore, the ability to avoid moving obstacles becomes a necessity for Unmanned Aerial Vehicles. Towards enabling a UAV to autonomously sense and avoid moving obstacles, this thesis makes the following contributions. Initially, an image-based reactive motion planner is developed for a quadrotor to avoid a fast approaching obstacle. Furthermore, A Dubin's curve based geometry method is developed as a global path planner for a fixed-wing UAV to avoid collisions with aircraft. The image-based method is unable to produce an optimal path and the geometry method uses a simplified UAV model. To compensate these two disadvantages, a series of algorithms built upon the Closed-Loop Rapid Exploratory Random Tree are developed as global path planners to generate collision avoidance paths in real time. The algorithms are validated in Software-In-the-Loop (SITL) and Hardware-In-the-Loop (HIL) simulations using a fixed-wing UAV model and in real flight experiments using quadrotors. It is observed that the algorithm enables a UAV to avoid moving obstacles approaching to it with different directions and speeds.

  16. 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.

  17. Modeling Aircraft Position and Conservatively Calculating Airspace Violations for an Autonomous Collision Awareness System for Unmanned Aerial Systems

    NASA Astrophysics Data System (ADS)

    Ueunten, Kevin K.

    With the scheduled 30 September 2015 integration of Unmanned Aerial System (UAS) into the national airspace, the Federal Aviation Administration (FAA) is concerned with UAS capabilities to sense and avoid conflicts. Since the operator is outside the cockpit, the proposed collision awareness plugin (CAPlugin), based on probability and error propagation, conservatively predicts potential conflicts with other aircraft and airspaces, thus increasing the operator's situational awareness. The conflict predictions are calculated using a forward state estimator (FSE) and a conflict calculator. Predicting an aircraft's position, modeled as a mixed Gaussian distribution, is the FSE's responsibility. Furthermore, the FSE supports aircraft engaged in the following three flight modes: free flight, flight path following and orbits. The conflict calculator uses the FSE result to calculate the conflict probability between an aircraft and airspace or another aircraft. Finally, the CAPlugin determines the highest conflict probability and warns the operator. In addition to discussing the FSE free flight, FSE orbit and the airspace conflict calculator, this thesis describes how each algorithm is implemented and tested. Lastly two simulations demonstrates the CAPlugin's capabilities.

  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. PMID:24852023

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Evaluation of the short-term sea cliff retreat along the Tróia-Sines Embayed Coast (Costa da Galé sector), using stereo digital aerial images and Bayesian inference

    NASA Astrophysics Data System (ADS)

    Gama, C.; Jalobeanu, A.

    2011-12-01

    Monitoring the sediment budget of coastal systems is essential to understand the costal equilibrium, and is an important aspect to be considered in coastal management. Thus, the identification and the quantitative evaluation of sedimentary sources and sinks are the first steps towards a better understanding of the dynamics of coastal morphology. The Tróia-Sines Embayed Coast (TSEC) in the southwest Portuguese coast corresponds to a continuous sandy beach that extends for approximately 65 km. It is limited at north by the Sado river estuary and at south by the Sines cape. Beaches are discontinuously limited landward by dunes (≈42 km) and by sea cliffs (≈18 km) made of poorly consolidated Plio-Plistocene detrital deposits. Cliff erosion by subaerial processes or gullying is a continuous phenomenon that contributes a significant amount of sediment to the TSEC coastal system, which is what we want to measure. Mainly due to winter rainfall, sea cliffs develop debris fans at the backshore inner limit, therefore we chose to make morphological measurements at one year interval. Thus, two series digital aerial images at 20 cm resolution were acquired in Oct 2008 and July 2009, supported by a collection of ground control points (GCP) to constrain the sensor orientation. Digital aerial stereo image pairs are used as main data source to reconstruct digital surface models (DSM). A new stereo photogrammetric method is used, based on dense disparity maps and Bayesian inference (Jalobeanu et al, 2010 and Jalobeanu, 2011). The originality of this method is in the computation of the spatial distribution of elevation errors in the DSM using stochastic modelling and probabilistic inference, which helps to detect the statistically significant changes in the estimated topography. The difference between the two generated DSMs is used to characterize the variability of the main subaerial beach morphodynamics parameters, such as: i) the alongshore beach configuration; ii) the beach

  5. 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.

  6. 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.

  7. A distribution model for the aerial application of granular agricultural particles

    NASA Technical Reports Server (NTRS)

    Fernandes, S. T.; Ormsbee, A. I.

    1978-01-01

    A model is developed to predict the shape of the distribution of granular agricultural particles applied by aircraft. The particle is assumed to have a random size and shape and the model includes the effect of air resistance, distributor geometry and aircraft wake. General requirements for the maintenance of similarity of the distribution for scale model tests are derived and are addressed to the problem of a nongeneral drag law. It is shown that if the mean and variance of the particle diameter and density are scaled according to the scaling laws governing the system, the shape of the distribution will be preserved. Distributions are calculated numerically and show the effect of a random initial lateral position, particle size and drag coefficient. A listing of the computer code is included.

  8. Adaptive planning of emergency aerial photogrammetric mission

    NASA Astrophysics Data System (ADS)

    Shen, Fuqiang; Zhu, Qing; Zhang, Junxiao; Miao, Shuangxi; Zhou, Xingxia; Cao, Zhenyu

    2015-12-01

    Aiming at the diversity of emergency aerial photogrammetric mission requirements, complex ground and air environmental constraints make the planning mission time-consuming. This paper presents a fast adaptation for the UAV aerial photogrammetric mission planning. First, Building emergency aerial UAVs mission the unified expression of UAVs model and mechanical model of performance parameters in the semantic space make the integrated expression of mission requirements and low altitude environment. Proposed match assessment method which based on resource and mission efficiency. Made the Adaptive match of UAV aerial resources and mission. According to the emergency aerial resource properties, considering complex air-ground environment and mission requirements constraints. Made accurate design of UAV route. Experimental results show, the method scientific and efficient, greatly enhanced the emergency response rate.

  9. Autocorrelation and regularization in digital images. II - Simple image models

    NASA Technical Reports Server (NTRS)

    Jupp, David L. B.; Strahler, Alan H.; Woodcock, Curtis E.

    1989-01-01

    The variogram function used in geostatistical analysis is a useful statistic in the analysis of remotely sensed images. Using the results derived by Jupp et al. (1988), the basic second-order, or covariance, properties of scenes modeled by simple disks of varying size and spacing after imaging into disk-shaped pixels are analyzed to explore the relationship betwee image variograms and discrete object scene structure. The models provide insight into the nature of real images of the earth's surface and the tools for a complete analysis of the more complex case of three-dimensional illuminated discrete-object images.

  10. Phase contrast radiography: Image modeling and optimization

    NASA Astrophysics Data System (ADS)

    Arhatari, Benedicta D.; Mancuso, Adrian P.; Peele, Andrew G.; Nugent, Keith A.

    2004-12-01

    We consider image formation for the phase-contrast radiography technique where the radiation source is extended and spatially incoherent. A model is developed for this imaging process which allows us to define an objective filtering criterion that can be applied to the recovery of quantitative phase images from data obtained at different propagation distances. We test our image model with experimental x-ray data. We then apply our filter to experimental neutron phase radiography data and demonstrate improved image quality.

  11. 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

  12. Image-Based Flow Modeling

    NASA Astrophysics Data System (ADS)

    Dillard, Seth; Mousel, John; Buchholz, James; Udaykumar, H. S.

    2009-11-01

    A preliminary method has been developed to model complex moving boundaries interacting with fluids in two dimensions using video files. Image segmentation techniques are employed to generate sharp object interfaces which are cast as level sets embedded in a Cartesian flow domain. In this way, boundary evolution is effected directly through imagery rather than by way of functional approximation. Videos of an American eel swimming in a water tunnel apparatus and a guinea pig duodenum undergoing peristaltic contractions in vitro serve as external and internal flow examples, which are evaluated for wake structure and mixing efficacy, respectively.

  13. Long-distance aerial dispersal modelling of Culicoides biting midges: case studies of incursions into Australia

    PubMed Central

    2014-01-01

    Background Previous studies investigating long-distance, wind-borne dispersal of Culicoides have utilised outbreaks of clinical disease (passive surveillance) to assess the relationship between incursion and dispersal event. In this study, species of exotic Culicoides and isolates of novel bluetongue viruses, collected as part of an active arbovirus surveillance program, were used for the first time to assess dispersal into an endemic region. Results A plausible dispersal event was determined for five of the six cases examined. These include exotic Culicoides specimens for which a possible dispersal event was identified within the range of two days – three weeks prior to their collection and novel bluetongue viruses for which a dispersal event was identified between one week and two months prior to their detection in cattle. The source location varied, but ranged from Lombok, in eastern Indonesia, to Timor-Leste and southern Papua New Guinea. Conclusions Where bluetongue virus is endemic, the concurrent use of an atmospheric dispersal model alongside existing arbovirus and Culicoides surveillance may help guide the strategic use of limited surveillance resources as well as contribute to continued model validation and refinement. Further, the value of active surveillance systems in evaluating models for long-distance dispersal is highlighted, particularly in endemic regions where knowledge of background virus and vector status is beneficial. PMID:24943652

  14. 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.

  15. 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.

  16. Verification of Potency of Aerial Digital Oblique Cameras for Aerial Photogrammetry in Japan

    NASA Astrophysics Data System (ADS)

    Nakada, Ryuji; Takigawa, Masanori; Ohga, Tomowo; Fujii, Noritsuna

    2016-06-01

    Digital oblique aerial camera (hereinafter called "oblique cameras") is an assembly of medium format digital cameras capable of shooting digital aerial photographs in five directions i.e. nadir view and oblique views (forward and backward, left and right views) simultaneously and it is used for shooting digital aerial photographs efficiently for generating 3D models in a wide area. For aerial photogrammetry of public survey in Japan, it is required to use large format cameras, like DMC and UltraCam series, to ensure aerial photogrammetric accuracy. Although oblique cameras are intended to generate 3D models, digital aerial photographs in 5 directions taken with them should not be limited to 3D model production but they may also be allowed for digital mapping and photomaps of required public survey accuracy in Japan. In order to verify the potency of using oblique cameras for aerial photogrammetry (simultaneous adjustment, digital mapping and photomaps), (1) a viewer was developed to interpret digital aerial photographs taken with oblique cameras, (2) digital aerial photographs were shot with an oblique camera owned by us, a Penta DigiCAM of IGI mbH, and (3) accuracy of 3D measurements was verified.

  17. 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

  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. Exterior Orientation Estimation of Oblique Aerial Imagery Using Vanishing Points

    NASA Astrophysics Data System (ADS)

    Verykokou, Styliani; Ioannidis, Charalabos

    2016-06-01

    In this paper, a methodology for the calculation of rough exterior orientation (EO) parameters of multiple large-scale overlapping oblique aerial images, in the case that GPS/INS information is not available (e.g., for old datasets), is presented. It consists of five main steps; (a) the determination of the overlapping image pairs and the single image in which four ground control points have to be measured; (b) the computation of the transformation parameters from every image to the coordinate reference system; (c) the rough estimation of the camera interior orientation parameters; (d) the estimation of the true horizon line and the nadir point of each image; (e) the calculation of the rough EO parameters of each image. A developed software suite implementing the proposed methodology is tested using a set of UAV multi-perspective oblique aerial images. Several tests are performed for the assessment of the errors and show that the estimated EO parameters can be used either as initial approximations for a bundle adjustment procedure or as rough georeferencing information for several applications, like 3D modelling, even by non-photogrammetrists, because of the minimal user intervention needed. Finally, comparisons with a commercial software are made, in terms of automation and correctness of the computed EO parameters.

  20. 11. Photocopy of aerial photograph (original aerial located in the ...

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

    11. Photocopy of aerial photograph (original aerial located in the U.S. Forest Service, Toiyabe National Forest, Carson District Office). AERIAL VIEW OF THE GENOA PEAK ROAD, SPUR. - Genoa Peak Road, Spur, Glenbrook, Douglas County, NV

  1. 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.

  2. 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

  3. Draper Laboratory small autonomous aerial vehicle

    NASA Astrophysics Data System (ADS)

    DeBitetto, Paul A.; Johnson, Eric N.; Bosse, Michael C.; Trott, Christian A.

    1997-06-01

    The Charles Stark Draper Laboratory, Inc. and students from Massachusetts Institute of Technology and Boston University have cooperated to develop an autonomous aerial vehicle that won the 1996 International Aerial Robotics Competition. This paper describes the approach, system architecture and subsystem designs for the entry. This entry represents a combination of many technology areas: navigation, guidance, control, vision processing, human factors, packaging, power, real-time software, and others. The aerial vehicle, an autonomous helicopter, performs navigation and control functions using multiple sensors: differential GPS, inertial measurement unit, sonar altimeter, and a flux compass. The aerial transmits video imagery to the ground. A ground based vision processor converts the image data into target position and classification estimates. The system was designed, built, and flown in less than one year and has provided many lessons about autonomous vehicle systems, several of which are discussed. In an appendix, our current research in augmenting the navigation system with vision- based estimates is presented.

  4. 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).

  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. 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 Central

    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. PMID:25785863

  7. 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.

  8. Aerial photographic reproductions

    USGS Publications Warehouse

    ,

    1975-01-01

    The National Cartographic Information Center of the U.S. Geological Survey maintains records of aerial photographic coverage of the United States and its Territories, based on reports from other Federal agencies as well as State governmental agencies and commercial companies. From these records, the Center furnishes data to prospective purchasers on available photography and the agency holding the aerial film.

  9. 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.

  10. 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.

  11. Composite Digital Terrain Models: Synthesizing Aerial and Terrestrial LiDAR with Conventional Survey Data to Monitor Sediment Transport Through the Sunol Dam Removal Site

    NASA Astrophysics Data System (ADS)

    Storesund, R.; Minear, T.; Saleh, R.

    2007-12-01

    In 2006, the San Francisco Public Utilities Commission removed Sunol dam, located on Alameda Creek, near San Francisco California. The primary goals of the project were to improve fish passage, restore a self- sustaining population of steelhead to the watershed, and eliminate an existing public safety hazard. Approximately 28,300 cubic meters of sand and gravel-sized sediment had accumulated upstream of the dam and was left in place to move downstream naturally over a period of several decades. To create a baseline for future monitoring of sediment transport through the dam area, a combination of Aerial LiDAR, Terrestrial LiDAR, and conventional survey data was compiled and synthesized to generate a three dimensional digital model of the study area both upstream and downstream of the damsite. The primary survey method for characterization of above ground topography was Terrestrial LiDAR, with an approximate point spacing of centimeters. In submerged areas conventional survey techniques were used to augment the Aerial and Terrestrial LiDAR data sets. We found this approach to be effective in developing a high accuracy-high detail sediment volume model from which sediment transport can be monitored and modeled.

  12. 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

  13. 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…

  14. Modeling countermeasures to imaging infrared seekers

    NASA Astrophysics Data System (ADS)

    Cox, Laurence J.; Batten, Michael A.; Carpenter, Stephen R.; Saddleton, Philip A. B.

    2004-12-01

    The threat to aircraft from missiles with imaging infrared seekers has developed more rapidly and in more countries independently than the original infrared missile threat. This is, in part, a consequence of the civil sector's demand for high-resolution infrared imagers and the development of computer processors capable of implementing complex image-processing algorithms im real time. Dstl has developed the Fly-In model to analyse the potential effectiveness of existing countermeasures (CM) to imaging infrared seekers and to test new CM approaches before trialling them against surrogate imaging seekers. The validation of the Fly-In model is extremely important, particularly as the newness of the imaging infrared threat, means that actual examples of the threat are not available for study. Extensive measurements have been carried out on the appearance of flare CM in different infrared wavebands, and on the effects of lasers on the optics and detector of an surrogate imageing seeker. Other parts of the model are derived from other Dstl models, including the NATO Infrared Airborne Target Model (NIRATAM) and HADES (missile dynamics) that are validated against trials' data. Initial studies have shown that existing CM, and those under development, can be very effective against imaging infrared seekers, by defeating the seeker's image-processing algorithms. It is already clear that laser CM will play an increasing role in the defence of aircraft, thereby enhancing aircraft survivability. Moreover, this model will aid the military planner in determining the best mix of CM and the tactics for using them.

  15. Geo-accurate model extraction from three-dimensional image-derived point clouds

    NASA Astrophysics Data System (ADS)

    Nilosek, David; Sun, Shaohui; Salvaggio, Carl

    2012-06-01

    A methodology is proposed for automatically extracting primitive models of buildings in a scene from a three-dimensional point cloud derived from multi-view depth extraction techniques. By exploring the information provided by the two-dimensional images and the three-dimensional point cloud and the relationship between the two, automated methods for extraction are presented. Using the inertial measurement unit (IMU) and global positioning system (GPS) data that accompanies the aerial imagery, the geometry is derived in a world-coordinate system so the model can be used with GIS software. This work uses imagery collected by the Rochester Institute of Technology's Digital Imaging and Remote Sensing Laboratory's WASP sensor platform. The data used was collected over downtown Rochester, New York. Multiple target buildings have their primitive three-dimensional model geometry extracted using modern point-cloud processing techniques.

  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. Oriental - Automatic Geo-Referencing and Ortho-Rectification of Archaeological Aerial Photographs

    NASA Astrophysics Data System (ADS)

    Karel, W.; Doneus, M.; Verhoeve, G.; Bries, C.; Ressl, C.; Pfeifer, N.

    2013-07-01

    This paper presents the newly developed software OrientAL, which aims at providing a fully automated processing chain from aerial photographs to orthophoto maps. It considers the special requirements of archaeological aerial images, including oblique imagery, single images, poor approximate georeferencing, and historic photographs. As a first step the automatic relative orientation of images from an archaeological image archive is presented.

  18. Image Reconstruction Using Analysis Model Prior.

    PubMed

    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

  19. 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

  20. 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.

  1. 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.

  2. "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…

  3. 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.

  4. 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.

  5. Natural image classification in nonlinear network model

    NASA Astrophysics Data System (ADS)

    Azhar, Hanif; Iftekharuddin, Khan; Kozma, Robert; Admala, Abhinav

    2005-08-01

    We study the non-linear behavior of the KIII model for natural image classification. The KIII model is designed to be a dynamic computational model that simulates the sensory cortex. The KIII model has been explored for rudimentary pattern recognition and classification in noisy environment. We extend the study of KIII models in understanding whether self-organized neural populations can be exploited into perceptual and memory producing systems such as in natural image classification. Our goal is to obtain a quantitative index on how well the KIII model behaves when it is assigned the task to identify and distinguish one class of natural image from the other based on color and texture features. For twenty training data, twenty validation data and eighty test data set for four image classes, we obtain 80% correct classification using the KIII. We compare a standard non linear neural network tools such as back propagation for the classification of the same set of natural images and obtain 65% correct classification. We conclude that dynamic neural computational models such as KIII may be suitable candidates for natural image classification.

  6. Unmanned Aerial Vehicle in Cadastral Applications

    NASA Astrophysics Data System (ADS)

    Manyoky, M.; Theiler, P.; Steudler, D.; Eisenbeiss, H.

    2011-09-01

    This paper presents the investigation of UAVs (Unmanned Aerial Vehicles) for use in cadastral surveying. Within the scope of a pilot study UAVs were tested for capturing geodata and compared with conventional data acquisition methods for cadastral surveying. Two study sites were therefore surveyed with a tachymeter-GNSS combination as well as a UAV system. The workflows of both methods were investigated and the resulting data were compared with the requirements of Swiss cadastral surveying. Concerning data acquisition and evaluation, the two systems are found to be comparable in terms of time expenditure, accuracy, and completeness. In conclusion, the UAV image orientation proved to be the limiting factor for the obtained accuracy due to the low- cost camera including camera calibration, image quality, and definition of the ground control points (natural or artificial). However, the required level of accuracy for cadastral surveying was reached. The advantage of UAV systems lies in their high flexibility and efficiency in capturing the surface of an area from a low flight altitude. In addition, further information such as orthoimages, elevation models and 3D objects can easily be gained from UAV images. Altogether, this project endorses the benefit of using UAVs in cadastral applications and the new opportunities they provide for cadastral surveying.

  7. 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

  8. 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

  9. 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

  10. Misaligned Image Integration With Local Linear Model.

    PubMed

    Baba, Tatsuya; Matsuoka, Ryo; Shirai, Keiichiro; Okuda, Masahiro

    2016-05-01

    We present a new image integration technique for a flash and long-exposure image pair to capture a dark scene without incurring blurring or noisy artifacts. Most existing methods require well-aligned images for the integration, which is often a burdensome restriction in practical use. We address this issue by locally transferring the colors of the flash images using a small fraction of the corresponding pixels in the long-exposure images. We formulate the image integration as a convex optimization problem with the local linear model. The proposed method makes it possible to integrate the color of the long-exposure image with the detail of the flash image without causing any harmful effects to its contrast, where we do not need perfect alignment between the images by virtue of our new integration principle. We show that our method successfully outperforms the state of the art in the image integration and reference-based color transfer for challenging misaligned data sets.

  11. 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.

  12. 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.

  13. Composite model of a 3-D image

    NASA Technical Reports Server (NTRS)

    Dukhovich, I. J.

    1980-01-01

    This paper presents a composite model of a moving (3-D) image especially useful for the sequential image processing and encoding. A non-linear predictor based on the composite model is described. The performance of this predictor is used as a measure of the validity of the model for a real image source. The minimization of a total mean square prediction error provides an inequality which determines a condition for the profitable use of the composite model and can serve as a decision device for the selection of the number of subsources within the model. The paper also describes statistical properties of the prediction error and contains results of computer simulation of two non-linear predictors in the case of perfect classification between subsources.

  14. Digital deformation model for fisheye image rectification.

    PubMed

    Hou, Wenguang; Ding, Mingyue; Qin, Nannan; Lai, Xudong

    2012-09-24

    Fisheye lens can provide a wide view over 180°. It then has prominence advantages in three dimensional reconstruction and machine vision applications. However, the serious deformation in the image limits fisheye lens's usage. To overcome this obstacle, a new rectification method named DDM (Digital Deformation Model) is developed based on two dimensional perspective transformation. DDM is a type of digital grid representation of the deformation of each pixel on CCD chip which is built by interpolating the difference between the actual image coordinate and pseudo-ideal coordinate of each mark on a control panel. This method obtains the pseudo-ideal coordinate according to two dimensional perspective transformation by setting four mark's deformations on image. The main advantages are that this method does not rely on the optical principle of fisheye lens and has relatively less computation. In applications, equivalent pinhole images can be obtained after correcting fisheye lens images using DDM.

  15. Joint Modeling of Imaging and Genetics

    PubMed Central

    Batmanghelich, Nematollah K.; Dalca, Adrian V.; Sabuncu, Mert R.; Golland, Polina

    2014-01-01

    We propose a unified Bayesian framework for detecting genetic variants associated with a disease while exploiting image-based features as an intermediate phenotype. Traditionally, imaging genetics methods comprise two separate steps. First, image features are selected based on their relevance to the disease phenotype. Second, a set of genetic variants are identified to explain the selected features. In contrast, our method performs these tasks simultaneously to ultimately assign probabilistic measures of relevance to both genetic and imaging markers. We derive an efficient approximate inference algorithm that handles high dimensionality of imaging genetic data. We evaluate the algorithm on synthetic data and show that it outperforms traditional models. We also illustrate the application of the method on ADNI data. PMID:24684016

  16. Digital deformation model for fisheye image rectification.

    PubMed

    Hou, Wenguang; Ding, Mingyue; Qin, Nannan; Lai, Xudong

    2012-09-24

    Fisheye lens can provide a wide view over 180°. It then has prominence advantages in three dimensional reconstruction and machine vision applications. However, the serious deformation in the image limits fisheye lens's usage. To overcome this obstacle, a new rectification method named DDM (Digital Deformation Model) is developed based on two dimensional perspective transformation. DDM is a type of digital grid representation of the deformation of each pixel on CCD chip which is built by interpolating the difference between the actual image coordinate and pseudo-ideal coordinate of each mark on a control panel. This method obtains the pseudo-ideal coordinate according to two dimensional perspective transformation by setting four mark's deformations on image. The main advantages are that this method does not rely on the optical principle of fisheye lens and has relatively less computation. In applications, equivalent pinhole images can be obtained after correcting fisheye lens images using DDM. PMID:23037373

  17. 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.

  18. Electromagnetohydrodynamic Modeling of Lorentz Effect Imaging

    PubMed Central

    Pourtaheri, Navid; Truong, Trong-Kha; Henriquez, Craig S.

    2013-01-01

    Lorentz Effect Imaging (LEI) is an MRI technique that has been proposed for direct imaging of neuronal activity. While promising results have been obtained in phantoms and in the human median nerve in vivo, its contrast mechanism is still not fully understood. In this paper, computational model simulations were used to investigate how electromagnetohydrodynamics (EMHD) may explain the LEI contrast. Three computational models of an electrolyte-filled phantom subject to an applied current dipole, synchronized to oscillating magnetic field gradients of an LEI protocol, were developed to determine the velocity and displacement of water molecules as well as the resulting signal loss in an MR image. The simulated images were compared to images from previous LEI phantom experiments with identical properties for different stimulus current amplitudes and polarities. The first model, which evaluated ion trajectories based on Stokes flow using different mobility values, did not generate an appreciable signal loss due to an insufficient number of water molecules associated with the ion hydration shells. The second model, which computed particle drift based on the Lorentz force of charged particles in free space, was able to approximate the magnitude, but not the distribution of signal loss observed in the experimental images. The third model, which computed EMHD based on the Lorentz force and Navier-Stokes equations for flow of a conducting fluid, provided results consistent with both the magnitude and distribution of signal loss seen in the LEI experiments. Our EMHD model further yields information on electrical potential, velocity, displacement, and pressure, which are not readily available in an experiment, thereby providing a robust means to study and optimize LEI for imaging neuronal activity in the human cortex. PMID:24056273

  19. Recovering ego-motion from optical flow for aerial navigation

    NASA Astrophysics Data System (ADS)

    Wen, Tongxin; Deng, He; Liu, Jianguo

    2011-11-01

    A new solution to recover 6DoF (Degrees of Freedom) ego-motion is present. The problem is to estimate the ego-motion information solely from dense optical flow (OF) field efficiently and robustly, free of Inertial Measurement Unit (IMU). The algorithm is a hierarchical framework and in each level there exist three parts, which are the optical flow Computation(OFC), the ego-motion estimation(EME) from two different models, and image warping(IW) according to the EME for the next level. The numerical precision of the algorithm under noise was investigated in the paper. We also compared its performance with Srinivasan's interpolation method and the 4DoF affine model on real aerial images. Our method are more accurate under large displacements and can resist the impacts of the rotations around x and y axis in a reasonable extent during computer navigation simulation.

  20. 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.

  1. Unmanned Aerial Systems and Spectroscopy for Remote Sensing Applications in Archaeology

    NASA Astrophysics Data System (ADS)

    Themistocleous, K.; Agapiou, A.; Cuca, B.; Hadjimitsis, D. G.

    2015-04-01

    Remote sensing has open up new dimensions in archaeological research. Although there has been significant progress in increasing the resolution of space/aerial sensors and image processing, the detection of the crop (and soil marks) formations, which relate to buried archaeological remains, are difficult to detect since these marks may not be visible in the images if observed over different period or at different spatial/spectral resolution. In order to support the improvement of earth observation remote sensing technologies specifically targeting archaeological research, a better understanding of the crop/soil marks formation needs to be studied in detail. In this paper the contribution of both Unmanned Aerial Systems as well ground spectroradiometers is discussed in a variety of examples applied in the eastern Mediterranean region (Cyprus and Greece) as well in Central Europe (Hungary). In- situ spectroradiometric campaigns can be applied for the removal of atmospheric impact to simultaneous satellite overpass images. In addition, as shown in this paper, the systematic collection of ground truth data prior to the satellite/aerial acquisition can be used to detect the optimum temporal and spectral resolution for the detection of stress vegetation related to buried archaeological remains. Moreover, phenological studies of the crops from the area of interest can be simulated to the potential sensors based on their Relative Response Filters and therefore prepare better the satellite-aerial campaigns. Ground data and the use of Unmanned Aerial Systems (UAS) can provide an increased insight for studying the formation of crop and soil marks. New algorithms such as vegetation indices and linear orthogonal equations for the enhancement of crop marks can be developed based on the specific spectral characteristics of the area. As well, UAS can be used for remote sensing applications in order to document, survey and model cultural heritage and archaeological sites.

  2. 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.

  3. 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

  4. Methods for classification of agricultural fields in aerial sequences: a comparative study

    NASA Astrophysics Data System (ADS)

    Houkes, Zweitze; Chen, Haijun; Blacquiere, Jan-Friso

    1998-12-01

    A comparative study of a selection of classification methods for agricultural fields in sequences of aerial images is presented. The image sequences are acquired by an RGB-CCD video camera which is assumed to be on board of an airplane, moving linear over the scene. The objects in the scenes being considered are agricultural fields. The classes of agricultural fields to be distinguished are determined by the type of crop, e.g. potatoes, sugar beet, wheat, etc. In order to recognize and classify these fields obtained from the aerial sequences of images, a common approach is in the use of surface texture. Textural features are extracted from the images to effectively characterize the vegetation. Methods based on Circular Symmetric Auto-Regression, Co-Occurrence Matrix and Local Binary Patterns are selected for the comparative study. The experiments are carried out with image sequences taken from a scaled model of a landscape and a selection from the Brodatz set. A few training images are used to set up the model bases for the three methods. The methods are tested using the same regions from other images of the sequence, and other sequences of images of similar fields. Comparison fa the methods is based on the confusion matrix. Sensitivity to variations in flight direction, variations in altitude and luminance conditions are being considered.

  5. Remote sensing image fusion via quaternion model

    NASA Astrophysics Data System (ADS)

    Serief, Chahira

    Due to the design constraints of optical satellite sensors, there is an inverse relationship between their spectral and spatial resolution. Consequently, remote sensing spaceborne imagery is usually offered to the community as two separate products: a high spatial resolution panchromatic (PAN) image and low spatial resolution multispectral (MS) image. However, multispectral (MS) images having both high spectral and spatial resolution are generally desired for various remote sensing applications such as land use, precision agriculture, pollution monitoring and mapping urban areas. This tradeoff of spectral and spatial resolutions can be resolved by injecting fine spatial information extracted from the PAN image into the MS images. This process is known as pansharpening and it has become a powerful and economical solution to take advantage of the high spatial information of the PAN image and the essential spectral information of MS images. The problem of pansharpening has been studied for approximately three decades and the literature on the subject is both rich and diverse. The existing pansharpening methods differ in the way the spatial details are extracted from the PAN image and injected into the MS bands. The main challenge in pansharpening techniques is to preserve as much as possible, the original spectral information while improving the spatial resolution. However, state-of-the-art pansharpening methods are based on a marginal scheme which relies on color separation (RGB decomposition for example) of the spectral images resulting in significant loss of spectral information. This is due to the fact that marginal schemes cannot capture the correlation among spectral channels. A mathematically elegant solution to this problem can be found in the hypercomplex numbers, in particular quaternion model. The quaternion model allows handling color images as a single entity and allows consequently capturing the correlations among spectral channels. The goal of this

  6. 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.

  7. Aerial Perspective Artistry

    ERIC Educational Resources Information Center

    Wolfe, Linda

    2010-01-01

    This article presents a lesson centering on aerial perspective artistry of students and offers suggestions on how art teachers should carry this project out. This project serves to develop students' visual perception by studying reproductions by famous artists. This lesson allows one to imagine being lured into a landscape capable of captivating…

  8. 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.

  9. Aerial photographic reproductions

    USGS Publications Warehouse

    U.S. Geological Survey

    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.

  10. 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.

  11. 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. PMID:27596102

  12. Modeling of functional brain imaging data

    NASA Astrophysics Data System (ADS)

    Horwitz, Barry

    1999-03-01

    The richness and complexity of data sets obtained from functional neuroimaging studies of human cognitive behavior, using techniques such as positron emission tomography and functional magnetic resonance imaging, have until recently not been exploited by computational neural modeling methods. In this article, following a brief introduction to functional neuroimaging methodology, two neural modeling approaches for use with functional brain imaging data are described. One, which uses structural equation modeling, examines the effective functional connections between various brain regions during specific cognitive tasks. The second employs large-scale neural modeling to relate functional neuroimaging signals in multiple, interconnected brain regions to the underlying neurobiological time-varying activities in each region. These two modeling procedures are illustrated using a visual processing paradigm.

  13. 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

  14. Attempt of UAV oblique images and MLS point clouds for 4D modelling of roadside pole-like objects

    NASA Astrophysics Data System (ADS)

    Lin, Yi; West, Geoff

    2014-11-01

    The state-of-the-art remote sensing technologies, namely Unmanned Aerial Vehicle (UAV) based oblique imaging and Mobile Laser Scanning (MLS) show great potential for spatial information acquisition. This study investigated the combination of the two data sources for 4D modelling of roadside pole-like objects. The data for the analysis were collected by the Microdrone md4-200 UAV imaging system and the Sensei MLS system developed by the Finnish Geodetic Institute. Pole extraction, 3D structural parameter derivation and texture segmentation were deployed on the oblique images and point clouds, and their results were fused to yield the 4D models for one example of pole-like objects, namely lighting poles. The combination techniques proved promising.

  15. 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.

  16. 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.

  17. High-fidelity synthetic IR imaging model

    NASA Astrophysics Data System (ADS)

    Wegener, Michael; Drake, Richard

    2000-07-01

    This paper describes a High Fidelity Synthetic IR Imaging Model which attempts to generate accurate static images as would be seen by a defined IR sensor given the target type and the atmospheric conditions. The model attempts to be quite general in its accommodation of physical processes yet maintain radiometric accuracy. Its main application are to assist in the validation of real-time IR scene generation software, and as a tool which can be used for range performance studies of electro-optical systems. The software model allows facet modeling of targets including temperature profiles and material properties. LOWTRAN/MODTRAN is used to provide atmospheric data for transmittance and self-radiation. Optical systems are described in terms of their transmittance and point spread function, both as functions of wavelength, and a self radiation term having temperature and material properties. At each wavelength desired the model generates descriptions of the flux distribution falling on the focal plane of the sensor system. The flux from different sources is added together to form the total flux distribution on the focal plane. Pixels on the focal plane are modeled by groups of facets with associated material properties allowing the shape and wavelength sensitivity to be expressed. The raw pixel output is obtained by integrating the flux distribution over the component facets and across wavelengths. Following non-uniformity modeling a convolution is applied which models readout smearing. Bandlimited noise is then added. The model is also able to generate and apply a matched filter to the output image. The model is designed to use common commercial software tools such as Multigen for target modeling and Open GL for the rendering. The model currently executes on Silicon Graphics hardware.

  18. 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.

  19. 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.

  20. 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

  1. 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. PMID:26353289

  2. Pore-scale imaging and modelling

    NASA Astrophysics Data System (ADS)

    Blunt, Martin J.; Bijeljic, Branko; Dong, Hu; Gharbi, Oussama; Iglauer, Stefan; Mostaghimi, Peyman; Paluszny, Adriana; Pentland, Christopher

    2013-01-01

    Pore-scale imaging and modelling - digital core analysis - is becoming a routine service in the oil and gas industry, and has potential applications in contaminant transport and carbon dioxide storage. This paper briefly describes the underlying technology, namely imaging of the pore space of rocks from the nanometre scale upwards, coupled with a suite of different numerical techniques for simulating single and multiphase flow and transport through these images. Three example applications are then described, illustrating the range of scientific problems that can be tackled: dispersion in different rock samples that predicts the anomalous transport behaviour characteristic of highly heterogeneous carbonates; imaging of super-critical carbon dioxide in sandstone to demonstrate the possibility of capillary trapping in geological carbon storage; and the computation of relative permeability for mixed-wet carbonates and implications for oilfield waterflood recovery. The paper concludes by discussing limitations and challenges, including finding representative samples, imaging and simulating flow and transport in pore spaces over many orders of magnitude in size, the determination of wettability, and upscaling to the field scale. We conclude that pore-scale modelling is likely to become more widely applied in the oil industry including assessment of unconventional oil and gas resources. It has the potential to transform our understanding of multiphase flow processes, facilitating more efficient oil and gas recovery, effective contaminant removal and safe carbon dioxide storage.

  3. [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.

  4. [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. PMID:26571671

  5. 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.

  6. AERIAL RADIOLOGICAL SURVEYS

    SciTech Connect

    Proctor, A.E.

    1997-06-09

    Measuring terrestrial gamma radiation from airborne platforms has proved to be a useful method for characterizing radiation levels over large areas. Over 300 aerial radiological surveys have been carried out over the past 25 years including U.S. Department of Energy (DOE) sites, commercial nuclear power plants, Formerly Utilized Sites Remedial Action Program/Uranium Mine Tailing Remedial Action Program (FUSRAP/UMTRAP) sites, nuclear weapons test sites, contaminated industrial areas, and nuclear accident sites. This paper describes the aerial measurement technology currently in use by the Remote Sensing Laboratory (RSL) for routine environmental surveys and emergency response activities. Equipment, data-collection and -analysis methods, and examples of survey results are described.

  7. 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.

  8. Modeling the amplitude statistics of ultrasonic images.

    PubMed

    Eltoft, Torbørn

    2006-02-01

    In this paper, a new statistical model for representing the amplitude statistics of ultrasonic images is presented. The model is called the Rician inverse Gaussian (RiIG) distribution, due to the fact that it is constructed as a mixture of the Rice distribution and the Inverse Gaussian distribution. The probability density function (pdf) of the RiIG model is given in closed form as a function of three parameters. Some theoretical background on this new model is discussed, and an iterative algorithm for estimating its parameters from data is given. Then, the appropriateness of the RiIG distribution as a model for the amplitude statistics of medical ultrasound images is experimentally studied. It is shown that the new distribution can fit to the various shapes of local histograms of linearly scaled ultrasound data better than existing models. A log-likelihood cross-validation comparison of the predictive performance of the RiIG, the K, and the generalized Nakagami models turns out in favor of the new model. Furthermore, a maximum a posteriori (MAP) filter is developed based on the RiIG distribution. Experimental studies show that the RiIG MAP filter has excellent filtering performance in the sense that it smooths homogeneous regions, and at the same time preserves details.

  9. 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

  10. 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).

  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. Cardiovascular Magnetic Resonance Imaging in Experimental Models

    PubMed Central

    Price, Anthony N.; Cheung, King K.; Cleary, Jon O; Campbell, Adrienne E; Riegler, Johannes; Lythgoe, Mark F

    2010-01-01

    Cardiovascular magnetic resonance (CMR) imaging is the modality of choice for clinical studies of the heart and vasculature, offering detailed images of both structure and function with high temporal resolution. Small animals are increasingly used for genetic and translational research, in conjunction with models of common pathologies such as myocardial infarction. In all cases, effective methods for characterising a wide range of functional and anatomical parameters are crucial for robust studies. CMR is the gold-standard for the non-invasive examination of these models, although physiological differences, such as rapid heart rate, make this a greater challenge than conventional clinical imaging. However, with the help of specialised magnetic resonance (MR) systems, novel gating strategies and optimised pulse sequences, high-quality images can be obtained in these animals despite their small size. In this review, we provide an overview of the principal CMR techniques for small animals for example cine, angiography and perfusion imaging, which can provide measures such as ejection fraction, vessel anatomy and local blood flow, respectively. In combination with MR contrast agents, regional dysfunction in the heart can also be identified and assessed. We also discuss optimal methods for analysing CMR data, particularly the use of semi-automated tools for parameter measurement to reduce analysis time. Finally, we describe current and emerging methods for imaging the developing heart, aiding characterisation of congenital cardiovascular defects. Advanced small animal CMR now offers an unparalleled range of cardiovascular assessments. Employing these methods should allow new insights into the structural, functional and molecular basis of the cardiovascular system. PMID:21331311

  13. 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.

  14. State-space models for optical imaging.

    PubMed

    Myers, Kary L; Brockwell, Anthony E; Eddy, William F

    2007-09-20

    Measurement of stimulus-induced changes in activity in the brain is critical to the advancement of neuroscience. Scientists use a range of methods, including electrode implantation, surface (scalp) electrode placement, and optical imaging of intrinsic signals, to gather data capturing underlying signals of interest in the brain. These data are usually corrupted by artifacts, complicating interpretation of the signal; in the context of optical imaging, two primary sources of corruption are the heartbeat and respiration cycles. We introduce a new linear state-space framework that uses the Kalman filter to remove these artifacts from optical imaging data. The method relies on a likelihood-based analysis under the specification of a formal statistical model, and allows for corrections to the signal based on auxiliary measurements of quantities closely related to the sources of contamination, such as physiological processes. Furthermore, the likelihood-based modeling framework allows us to perform both goodness-of-fit testing and formal hypothesis testing on parameters of interest. Working with data collected by our collaborators, we demonstrate the method of data collection in an optical imaging study of a cat's brain.

  15. 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.

  16. 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

  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. 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

  19. 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.

  20. 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. 

  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. 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.

  3. 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.

  4. 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.

  5. Infrared film for aerial photography

    USGS Publications Warehouse

    Anderson, William H.

    1979-01-01

    Considerable interest has developed recently in the use of aerial photographs for agricultural management. Even the simplest hand-held aerial photographs, especially those taken with color infrared film, often provide information not ordinarily available through routine ground observation. When fields are viewed from above, patterns and variations become more apparent, often allowing problems to be spotted which otherwise may go undetected.

  6. Controller Design of Quadrotor Aerial Robot

    NASA Astrophysics Data System (ADS)

    Yali, Yu; SunFeng; Yuanxi, Wang

    This paper deduced the nonlinear dynamic model of a quadrotor aerial robot, which was a VTOL (vertical tale-off and landing) unmanned air vehicle. Since that is a complex model with the highly nonlinear multivariable strongly coupled and under-actuated property, the controller design of it was very difficult. Aimed at attaining the excellent controller, the whole system can be divided into three interconnected parts: attitude subsystem, vertical subsystem, position subsystem. Then nonlinear control strategy of them has been described, such as SDRE and Backstepping. The controller design was presented to stabilize the whole system. Through simulation result indicates, the various models have shown that the control law stabilize a quadrotor aerial robot with good tracking performance and robotness of the system.

  7. 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.

  8. Bio-inspired color image enhancement model

    NASA Astrophysics Data System (ADS)

    Zheng, Yufeng

    2009-05-01

    Human being can perceive natural scenes very well under various illumination conditions. Partial reasons are due to the contrast enhancement of center/surround networks and opponent analysis on the human retina. In this paper, we propose an image enhancement model to simulate the color processes in the human retina. Specifically, there are two center/surround layers, bipolar/horizontal and ganglion/amacrine; and four color opponents, red (R), green (G), blue (B), and yellow (Y). The central cell (bipolar or ganglion) takes the surrounding information from one or several horizontal or amacrine cells; and bipolar and ganglion both have ON and OFF sub-types. For example, a +R/-G bipolar (red-center- ON/green-surround-OFF) will be excited if only the center is illuminated, or inhibited if only the surroundings (bipolars) are illuminated, or stay neutral if both center and surroundings are illuminated. Likewise, other two color opponents with ON-center/OFF-surround, +G/-R and +B/-Y, follow the same rules. The yellow (Y) channel can be obtained by averaging red and green channels. On the other hand, OFF-center/ON-surround bipolars (i.e., -R/+G and -G/+R, but no - B/+Y) are inhibited when the center is illuminated. An ON-bipolar (or OFF-bipolar) only transfers signals to an ONganglion (or OFF-ganglion), where amacrines provide surrounding information. Ganglion cells have strong spatiotemporal responses to moving objects. In our proposed enhancement model, the surrounding information is obtained using weighted average of neighborhood; excited or inhibited can be implemented with pixel intensity increase or decrease according to a linear or nonlinear response; and center/surround excitations are decided by comparing their intensities. A difference of Gaussian (DOG) model is used to simulate the ganglion differential response. Experimental results using natural scenery pictures proved that, the proposed image enhancement model by simulating the two-layer center

  9. Modeling synthetic radar image from a digital terrain model

    NASA Astrophysics Data System (ADS)

    Durand, Philippe; Jaupi, Luan; Ghorbanzadeh, Dariush; Rudant, Jean Paul

    2015-03-01

    In this paper we propose to simulate SAR radar images that can be acquired by aircraft or satellite. This corresponds to a real problematic, in fact, an airborne radar data acquisition campaign, was conducted in the south east of France. We want to estimate the geometric deformations that a digital terrain model can be subjected. By extrapolation, this construction should also allow to understand the image distortion if a plane is replaced by a satellite. This manipulation allow to judge the relevance of a space mission to quantify geological and geomorphological data. The radar wave is an electromagnetic wave, they have the advantage of overcoming atmospheric conditions since more wavelength is large is better crossing the cloud layer. Therefore imaging radar provides continuous monitoring.

  10. 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.

  11. 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

  12. Quantitative bioluminescence imaging of mouse tumor models.

    PubMed

    Tseng, Jen-Chieh; Kung, Andrew L

    2015-01-05

    Bioluminescence imaging (BLI) has become an essential technique for preclinical evaluation of anticancer therapeutics and provides sensitive and quantitative measurements of tumor burden in experimental cancer models. For light generation, a vector encoding firefly luciferase is introduced into human cancer cells that are grown as tumor xenografts in immunocompromised hosts, and the enzyme substrate luciferin is injected into the host. Alternatively, the reporter gene can be expressed in genetically engineered mouse models to determine the onset and progression of disease. In addition to expression of an ectopic luciferase enzyme, bioluminescence requires oxygen and ATP, thus only viable luciferase-expressing cells or tissues are capable of producing bioluminescence signals. Here, we summarize a BLI protocol that takes advantage of advances in hardware, especially the cooled charge-coupled device camera, to enable detection of bioluminescence in living animals with high sensitivity and a large dynamic range.

  13. 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.

  14. 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

  15. 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. PMID:22389620

  16. Metrics for image-based modeling of target acquisition

    NASA Astrophysics Data System (ADS)

    Fanning, Jonathan D.

    2012-06-01

    This paper presents an image-based system performance model. The image-based system model uses an image metric to compare a given degraded image of a target, as seen through the modeled system, to the set of possible targets in the target set. This is repeated for all possible targets to generate a confusion matrix. The confusion matrix is used to determine the probability of identifying a target from the target set when using a particular system in a particular set of conditions. The image metric used in the image-based model should correspond closely to human performance. The image-based model performance is compared to human perception data on Contrast Threshold Function (CTF) tests, naked eye Triangle Orientation Discrimination (TOD), and TOD including an infrared camera system. Image-based system performance modeling is useful because it allows modeling of arbitrary image processing. Modern camera systems include more complex image processing, much of which is nonlinear. Existing linear system models, such as the TTP metric model implemented in NVESD models such as NV-IPM, assume that the entire system is linear and shift invariant (LSI). The LSI assumption makes modeling nonlinear processes difficult, such as local area processing/contrast enhancement (LAP/LACE), turbulence reduction, and image fusion.

  17. 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.

  18. 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.

  19. 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.

  20. Improving Measurement of Forest Structural Parameters by Co-Registering of High Resolution Aerial Imagery and Low Density LiDAR Data

    PubMed Central

    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. PMID:22573971

  1. 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.

  2. 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".

  3. AERIAL MEASURING SYSTEM IN JAPAN

    SciTech Connect

    Lyons, Craig; Colton, David

    2012-01-01

    The U.S. Department of Energy National Nuclear Security Agency’s Aerial Measuring System deployed personnel and equipment to partner with the U.S. Air Force in Japan to conduct multiple aerial radiological surveys. These were the first and most comprehensive sources of actionable information for U.S. interests in Japan and provided early confirmation to the government of Japan as to the extent of the release from the Fukushima Daiichi Nuclear Power Generation Station. Many challenges were overcome quickly during the first 48 hours; including installation and operation of Aerial Measuring System equipment on multiple U.S. Air Force Japan aircraft, flying over difficult terrain, and flying with talented pilots who were unfamiliar with the Aerial Measuring System flight patterns. These all combined to make for a dynamic and non-textbook situation. In addition, the data challenges of the multiple and on-going releases, and integration with the Japanese government to provide valid aerial radiological survey products that both military and civilian customers could use to make informed decisions, was extremely complicated. The Aerial Measuring System Fukushima response provided insight in addressing these challenges and gave way to an opportunity for the expansion of the Aerial Measuring System’s mission beyond the borders of the US.

  4. 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.

  5. 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

  6. 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.

  7. Role of Imaging Specrometer Data for Model-based Cross-calibration of Imaging Sensors

    NASA Technical Reports Server (NTRS)

    Thome, Kurtis John

    2014-01-01

    Site characterization benefits from imaging spectrometry to determine spectral bi-directional reflectance of a well-understood surface. Cross calibration approaches, uncertainties, role of imaging spectrometry, model-based site characterization, and application to product validation.

  8. Use of aerial photographs for assessment of soil organic carbon and delineation of agricultural management zones.

    NASA Astrophysics Data System (ADS)

    Bartholomeus, H.; Kooistra, L.

    2012-04-01

    For quantitative estimation of soil properties by means of remote sensing, often hyperspectral data are used. But these data are scarce and expensive, which prohibits wider implementation of the developed techniques in agricultural management. For precision agriculture, observations at a high spatial resolution are required. Colour aerial photographs at this scale are widely available, and can be acquired at no of very low costs. Therefore, we investigated whether publically available aerial photographs can be used to a) automatically delineate management zones and b) estimate levels of organic carbon spatially. We selected three study areas within the Netherlands that cover a large variance in soil type (peat, sand, and clay). For the fields of interest, RGB aerial photographs with a spatial resolution of 50 cm were extracted from a publically available data provider. Further pre-processing exists of geo-referencing only. Since the images originate from different sources and are potentially acquired under unknown illumination conditions, the exact radiometric properties of the data are unknown. Therefore, we used spectral indices to emphasize the differences in reflectance and normalize for differences in radiometry. To delineate management zones we used image segmentation techniques, using the derived indices as input. Comparison with management zone maps as used by the farmers shows that there is good correspondence. Regression analysis between a number of soil properties and the derived indices shows that organic carbon is the major explanatory variable for differences in index values within the fields. However, relations do not hold for large regions, indicating that local models will have to be used, which is a problem that is also still relevant for hyperspectral remote sensing data. With this research, we show that low-cost aerial photographs can be a valuable tool for quantitative analysis of organic carbon and automatic delineation of management zones

  9. Blind Image Inpainting Based on TV Model and Edge Detection

    NASA Astrophysics Data System (ADS)

    Wang, Xin-Yu; Deng, Liang-Jian

    Blind image inpainting is an approach to estimate the original image, when there is no or little knowledge of the degraded process. In this paper, the algorithm of blind image inpainting is based on edge detection methods to generate one inpainting mask H automatically. And then we combine the inpainting mask H with a TV model to get image blind inpainted. Experiment results demonstrate that the proposed algorithms is effective with application to both the synthetic and real-world images.

  10. Ecological Energetics of an Abundant Aerial Insectivore, the Purple Martin

    PubMed Central

    Kelly, Jeffrey F.; Bridge, Eli S.; Frick, Winifred F.; Chilson, Phillip B.

    2013-01-01

    The atmospheric boundary layer and lower free atmosphere, or aerosphere, is increasingly important for human transportation, communication, environmental monitoring, and energy production. The impacts of anthropogenic encroachment into aerial habitats are not well understood. Insectivorous birds and bats are inherently valuable components of biodiversity and play an integral role in aerial trophic dynamics. Many of these insectivores are experiencing range-wide population declines. As a first step toward gaging the potential impacts of these declines on the aerosphere’s trophic system, estimates of the biomass and energy consumed by aerial insectivores are needed. We developed a suite of energetics models for one of the largest and most common avian aerial insectivores in North America, the Purple Martin (Prognesubis). The base model estimated that Purple Martins consumed 412 (± 104) billion insects*y-1 with a biomass of 115,860 (± 29,192) metric tonnes*y-1. During the breeding season Purple Martins consume 10.3 (+ 3.0) kg of prey biomass per km3 of aerial habitat, equal to about 36,000 individual insects*km-3. Based on these calculations, the cumulative seasonal consumption of insects*km-3 is greater in North America during the breeding season than during other phases of the annual cycle, however the maximum daily insect consumption*km-3 occurs during fall migration. This analysis provides the first range-wide quantitative estimate of the magnitude of the trophic impact of this large and common aerial insectivore. Future studies could use a similar modeling approach to estimate impacts of the entire guild of aerial insectivores at a variety of temporal and spatial scales. These analyses would inform our understanding of the impact of population declines among aerial insectivores on the aerosphere’s trophic dynamics. PMID:24086755

  11. AXAF-1 High Resolution Assembly Image Model and Comparison with X-Ray Ground Test Image

    NASA Technical Reports Server (NTRS)

    Zissa, David E.

    1999-01-01

    The x-ray ground test of the AXAF-I High Resolution Mirror Assembly was completed in 1997 at the X-ray Calibration Facility at Marshall Space Flight Center. Mirror surface measurements by HDOS, alignment results from Kodak, and predicted gravity distortion in the horizontal test configuration are being used to model the x-ray test image. The Marshall Space Flight Center (MSFC) image modeling serves as a cross check with Smithsonian Astrophysical observatory modeling. The MSFC image prediction software has evolved from the MSFC model of the x-ray test of the largest AXAF-I mirror pair in 1991. The MSFC image modeling software development is being assisted by the University of Alabama in Huntsville. The modeling process, modeling software, and image prediction will be discussed. The image prediction will be compared with the x-ray test results.

  12. 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.

  13. 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.

  14. Probabilistic model for quick detection of dissimilar binary images

    NASA Astrophysics Data System (ADS)

    Mustafa, Adnan A. Y.

    2015-09-01

    We present a quick method to detect dissimilar binary images. The method is based on a "probabilistic matching model" for image matching. The matching model is used to predict the probability of occurrence of distinct-dissimilar image pairs (completely different images) when matching one image to another. Based on this model, distinct-dissimilar images can be detected by matching only a few points between two images with high confidence, namely 11 points for a 99.9% successful detection rate. For image pairs that are dissimilar but not distinct-dissimilar, more points need to be mapped. The number of points required to attain a certain successful detection rate or confidence depends on the amount of similarity between the compared images. As this similarity increases, more points are required. For example, images that differ by 1% can be detected by mapping fewer than 70 points on average. More importantly, the model is image size invariant; so, images of any sizes will produce high confidence levels with a limited number of matched points. As a result, this method does not suffer from the image size handicap that impedes current methods. We report on extensive tests conducted on real images of different sizes.

  15. A new level set model for cell image segmentation

    NASA Astrophysics Data System (ADS)

    Ma, Jing-Feng; Hou, Kai; Bao, Shang-Lian; Chen, Chun

    2011-02-01

    In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

  16. Kinetic modeling in PET imaging of hypoxia

    PubMed Central

    Li, Fan; Joergensen, Jesper T; Hansen, Anders E; Kjaer, Andreas

    2014-01-01

    Tumor hypoxia is associated with increased therapeutic resistance leading to poor treatment outcome. Therefore the ability to detect and quantify intratumoral oxygenation could play an important role in future individual personalized treatment strategies. Positron Emission Tomography (PET) can be used for non-invasive mapping of tissue oxygenation in vivo and several hypoxia specific PET tracers have been developed. Evaluation of PET data in the clinic is commonly based on visual assessment together with semiquantitative measurements e.g. standard uptake value (SUV). However, dynamic PET contains additional valuable information on the temporal changes in tracer distribution. Kinetic modeling can be used to extract relevant pharmacokinetic parameters of tracer behavior in vivo that reflects relevant physiological processes. In this paper, we review the potential contribution of kinetic analysis for PET imaging of hypoxia. PMID:25250200

  17. Vehicle detection in aerial surveillance using dynamic Bayesian networks.

    PubMed

    Cheng, Hsu-Yung; Weng, Chih-Chia; Chen, Yi-Ying

    2012-04-01

    We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.

  18. 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].

  19. 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.

  20. 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...

  1. 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...

  2. Modeling habitat suitability for Greater Rheas based on satellite image texture.

    PubMed

    Bellis, Laura M; Pidgeon, Anna M; Radeloff, Volker C; St-Louis, Véronique; Navarro, Joaquín L; Martella, Mónica B

    2008-12-01

    Many wild species are affected by human activities occurring at broad spatial scales. For instance, in South America, habitat loss threatens Greater Rhea (Rhea americana) populations, making it important to model and map their habitat to better target conservation efforts. Spatially explicit habitat modeling is a powerful approach to understand and predict species occurrence and abundance. One problem with this approach is that commonly used land cover classifications do not capture the variability within a given land cover class that might constitute important habitat attribute information. Texture measures derived from remote sensing images quantify the variability in habitat features among and within habitat types; hence they are potentially a powerful tool to assess species-habitat relationships. Our goal was to explore the utility of texture measures for habitat modeling and to develop a habitat suitability map for Greater Rheas at the home range level in grasslands of Argentina. Greater Rhea group size obtained from aerial surveys was regressed against distance to roads, houses, and water, and land cover class abundance (dicotyledons, crops, grassland, forest, and bare soil), normalized difference vegetation index (NDVI), and selected first- and second-order texture measures derived from Landsat Thematic Mapper (TM) imagery. Among univariate models, Rhea group size was most strongly positively correlated with texture variables derived from near infrared reflectance measurement (TM band 4). The best multiple regression models explained 78% of the variability in Greater Rhea group size. Our results suggest that texture variables captured habitat heterogeneity that the conventional land cover classification did not detect. We used Greater Rhea group size as an indicator of habitat suitability; we categorized model output into different habitat quality classes. Only 16% of the study area represented high-quality habitat for Greater Rheas (group size > or =15

  3. 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.

  4. A coherent model for turbid imaging with confocal microscopy

    PubMed Central

    Glazowski, Christopher E.; Zavislan, James

    2013-01-01

    We present an engineering model of coherent imaging within a turbid volume, such as human tissues, with a confocal microscope. The model is built to analyze the statistical effect of aberrations and multiply scattered light on the resulting image. Numerical modeling of theory is compared with experimental results. We describe the construction of a stable phantom that represents the statistical effect of object turbidity on the image recorded. The model and phantom can serve as basis for system optimization in turbid imaging. PMID:23577285

  5. A Drosophila model to image phagosome maturation.

    PubMed

    Shandala, Tetyana; Lim, Chiaoxin; Sorvina, Alexandra; Brooks, Douglas A

    2013-01-01

    Phagocytosis involves the internalization of extracellular material by invagination of the plasma membrane to form intracellular vesicles called phagosomes, which have functions that include pathogen degradation. The degradative properties of phagosomes are thought to be conferred by sequential fusion with endosomes and lysosomes; however, this maturation process has not been studied in vivo. We employed Drosophila hemocytes, which are similar to mammalian professional macrophages, to establish a model of phagosome maturation. Adult Drosophila females, carrying transgenic Rab7-GFP endosome and Lamp1-GFP lysosome markers, were injected with E. coli DH5α and the hemocytes were collected at 15, 30, 45 and 60 minutes after infection. In wild-type females, E. coli were detected within enlarged Rab7-GFP positive phagosomes at 15 to 45 minutes after infection; and were also observed in enlarged Lamp1-GFP positive phagolysosomes at 45 minutes. Two-photon imaging of hemocytes in vivo confirmed this vesicle morphology, including enlargement of Rab7-GFP and Lamp1-GFP structures that often appeared to protrude from hemocytes. The interaction of endosomes and lysosomes with E. coli phagosomes observed in Drosophila hemocytes was consistent with that previously described for phagosome maturation in human ex vivo macrophages. We also tested our model as a tool for genetic analysis using 14-3-3e mutants, and demonstrated altered phagosome maturation with delayed E. coli internalization, trafficking and/or degradation. These findings demonstrate that Drosophila hemocytes provide an appropriate, genetically amenable, model for analyzing phagosome maturation ex vivo and in vivo. PMID:24709696

  6. VisNAV 100: a robust, compact imaging sensor for enabling autonomous air-to-air refueling of aircraft and unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Katake, Anup; Choi, Heeyoul

    2010-01-01

    To enable autonomous air-to-refueling of manned and unmanned vehicles a robust high speed relative navigation sensor capable of proving high accuracy 3DOF information in diverse operating conditions is required. To help address this problem, StarVision Technologies Inc. has been developing a compact, high update rate (100Hz), wide field-of-view (90deg) direction and range estimation imaging sensor called VisNAV 100. The sensor is fully autonomous requiring no communication from the tanker aircraft and contains high reliability embedded avionics to provide range, azimuth, elevation (3 degrees of freedom solution 3DOF) and closing speed relative to the tanker aircraft. The sensor is capable of providing 3DOF with an error of 1% in range and 0.1deg in azimuth/elevation up to a range of 30m and 1 deg error in direction for ranges up to 200m at 100Hz update rates. In this paper we will discuss the algorithms that were developed in-house to enable robust beacon pattern detection, outlier rejection and 3DOF estimation in adverse conditions and present the results of several outdoor tests. Results from the long range single beacon detection tests will also be discussed.

  7. 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.

  8. Joint model of motion and anatomy for PET image reconstruction

    SciTech Connect

    Qiao Feng; Pan Tinsu; Clark, John W. Jr.; Mawlawi, Osama

    2007-12-15

    Anatomy-based positron emission tomography (PET) image enhancement techniques have been shown to have the potential for improving PET image quality. However, these techniques assume an accurate alignment between the anatomical and the functional images, which is not always valid when imaging the chest due to respiratory motion. In this article, we present a joint model of both motion and anatomical information by integrating a motion-incorporated PET imaging system model with an anatomy-based maximum a posteriori image reconstruction algorithm. The mismatched anatomical information due to motion can thus be effectively utilized through this joint model. A computer simulation and a phantom study were conducted to assess the efficacy of the joint model, whereby motion and anatomical information were either modeled separately or combined. The reconstructed images in each case were compared to corresponding reference images obtained using a quadratic image prior based maximum a posteriori reconstruction algorithm for quantitative accuracy. Results of these studies indicated that while modeling anatomical information or motion alone improved the PET image quantitation accuracy, a larger improvement in accuracy was achieved when using the joint model. In the computer simulation study and using similar image noise levels, the improvement in quantitation accuracy compared to the reference images was 5.3% and 19.8% when using anatomical or motion information alone, respectively, and 35.5% when using the joint model. In the phantom study, these results were 5.6%, 5.8%, and 19.8%, respectively. These results suggest that motion compensation is important in order to effectively utilize anatomical information in chest imaging using PET. The joint motion-anatomy model presented in this paper provides a promising solution to this problem.

  9. 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.

  10. Applicability Evaluation of Object Detection Method to Satellite and Aerial Imageries

    NASA Astrophysics Data System (ADS)

    Kamiya, K.; Fuse, T.; Takahashi, M.

    2016-06-01

    Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ object detection before object recognition can save a computational time and cost, and thus take a significant role. However, there is not enough knowledge whether object detection method can perform well on satellite and aerial imageries. In addition, it also has to be studied how characteristics of satellite and aerial imageries affect the object detection performance. This study employ binarized normed gradients (BING) method that runs significantly fast and is robust to rotation and noise. For our experiments, 11-bits BGR-IR satellite imageries from WorldView-3, and BGR-color aerial imageries are used respectively, and we create thousands of ground truth samples. We conducted several experiments to compare the performances with different images, to verify whether combination of different resolution images improved the performance, and to analyze the applicability of mixing satellite and aerial imageries. The results showed that infrared band had little effect on the detection rate, that 11-bit images performed less than 8-bit images and that the better spatial resolution brought the better performance. Another result might imply that mixing higher and lower resolution images for training dataset could help detection performance. Furthermore, we found that aerial images improved the detection performance on satellite images.

  11. Accuracy of DSM based on digital aerial image matching. (Polish Title: Dokładność NMPT tworzonego metodą automatycznego dopasowania cyfrowych zdjęć lotniczych)

    NASA Astrophysics Data System (ADS)

    Kubalska, J. L.; Preuss, R.

    2013-12-01

    Digital Surface Models (DSM) are used in GIS data bases as single product more often. They are also necessary to create other products such as3D city models, true-ortho and object-oriented classification. This article presents results of DSM generation for classification of vegetation in urban areas. Source data allowed producing DSM with using of image matching method and ALS data. The creation of DSM from digital images, obtained by Ultra Cam-D digital Vexcel camera, was carried out in Match-T by INPHO. This program optimizes the configuration of images matching process, which ensures high accuracy and minimize gap areas. The analysis of the accuracy of this process was made by comparison of DSM generated in Match-T with DSM generated from ALS data. Because of further purpose of generated DSM it was decided to create model in GRID structure with cell size of 1 m. With this parameter differential model from both DSMs was also built that allowed determining the relative accuracy of the compared models. The analysis indicates that the generation of DSM with multi-image matching method is competitive for the same surface model creation from ALS data. Thus, when digital images with high overlap are available, the additional registration of ALS data seems to be unnecessary.

  12. 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

  13. [A medical image semantic modeling based on hierarchical Bayesian networks].

    PubMed

    Lin, Chunyi; Ma, Lihong; Yin, Junxun; Chen, Jianyu

    2009-04-01

    A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in allusion to characters of medical images. It used GMM (Gaussian mixture models) to map low-level image features into object semantics with probabilities, then it captured high-level semantics through fusing these object semantics using a Bayesian network, so that it built a multi-layer medical image semantic model, aiming to enable automatic image annotation and semantic retrieval by using various keywords at different semantic levels. As for the validity of this method, we have built a multi-level semantic model from a small set of astrocytoma MRI (magnetic resonance imaging) samples, in order to extract semantics of astrocytoma in malignant degree. Experiment results show that this is a superior approach.

  14. 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.

  15. 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.

  16. 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.

  17. Antioxidant activity of bulbs and aerial parts of Crocus caspius, impact of extraction methods.

    PubMed

    Khalili, Masomeh; Fathi, Hamed; Ebrahimzadeh, Mohammad Ali

    2016-05-01

    Crocus genus (Iridaceae) is comprises approximately 80 species. In this study in vitro antioxidant activities of extracts from C. caspius bulbs and aerial parts were investigated. Ultrasonically assisted extraction (US), percolation method (PE) and polyphenolic fraction (PP) were used. Antioxidant activities were evaluated with five different tests. Aerial parts US extract with high levels of phenol and flavonoids were the most potent extract in DPPH radical scavenging than others. Aerial parts PE extract had shown very potent reducing power, which was so better than other extracts (p<0.01). Aerial parts PP fraction showed very good Fe(2+) chelating ability. Aerial parts US extract were the most potent extract in scavenging of H(2)O(2). Bulb PP fraction with IC(50)=22.8±0.7 µg ml(-1) was the most potent fraction in nitric oxide scavenging. The results improved high levels of antioxidant activities of C. caspius bulbs and aerial parts in all tested models.

  18. Antioxidant activity of bulbs and aerial parts of Crocus caspius, impact of extraction methods.

    PubMed

    Khalili, Masomeh; Fathi, Hamed; Ebrahimzadeh, Mohammad Ali

    2016-05-01

    Crocus genus (Iridaceae) is comprises approximately 80 species. In this study in vitro antioxidant activities of extracts from C. caspius bulbs and aerial parts were investigated. Ultrasonically assisted extraction (US), percolation method (PE) and polyphenolic fraction (PP) were used. Antioxidant activities were evaluated with five different tests. Aerial parts US extract with high levels of phenol and flavonoids were the most potent extract in DPPH radical scavenging than others. Aerial parts PE extract had shown very potent reducing power, which was so better than other extracts (p<0.01). Aerial parts PP fraction showed very good Fe(2+) chelating ability. Aerial parts US extract were the most potent extract in scavenging of H(2)O(2). Bulb PP fraction with IC(50)=22.8±0.7 µg ml(-1) was the most potent fraction in nitric oxide scavenging. The results improved high levels of antioxidant activities of C. caspius bulbs and aerial parts in all tested models. PMID:27166547

  19. 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.

  20. Calculation and Update of a 3d Building Model of Bavaria Using LIDAR, Image Matching and Catastre Information

    NASA Astrophysics Data System (ADS)

    Aringer, K.; Roschlaub, R.

    2013-09-01

    The Bavarian State Office for Surveying and Geoinformation has launched a statewide 3D Building Model with standardized roof shapes without textures for all 8.1 million buildings in Bavaria. For acquisition of the 3D Building Model LiDAR-data are used as data basis as well as the building ground plans of the official cadastral map and a list of standardized roof shapes. The data management of the 3D Building Model is carried out by a central database with the usage of a nationwide standardized data model and the data exchange interface CityGML. On the one hand the update of the 3D Building Model for new buildings is done by terrestrial building measurements within the maintenance process of the cadastre. On the other hand the roofs of buildings which were built after the LiDAR flight and which were not measured terrestrially yet, are captured by means of picture-based digital surface-models derived from image-matching of oriented aerial photographs (DSM from image matching).

  1. Image-based modeling of lung structure and function

    PubMed Central

    Tawhai, Merryn H.; Lin, Ching-Long

    2010-01-01

    Current state-of-the-art in image-based modeling allows derivation of patient-specific models of the lung, lobes, airways, and pulmonary vascular trees. The application of traditional engineering analyses of fluid and structural mechanics to image-based subject-specific models has the potential to provide new insight into structure-function relationships in the individual via functional interpretation that complements imaging and experimental studies. Three major issues that are encountered in studies of air flow through the bronchial airways are the representation of airway geometry, the imposition of physiological boundary conditions, and the treatment of turbulence. Here we review some efforts to resolve each of these issues, with particular focus on image-based models that have been developed to simulate air flow from the mouth to the terminal bronchiole, and subjected to physiologically meaningful boundary conditions via image registration and soft tissue mechanics models. PMID:21105146

  2. 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.

  3. 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

  4. Model-based segmentation of medical x-ray images

    NASA Astrophysics Data System (ADS)

    Hoare, Frederick; de Jager, Gerhard

    1994-03-01

    This paper discusses the methods used to model the structure of x-ray images of the human body and the individual organs within the body. A generic model of a region is built up from x-ray images to aid in automatic segmentation. By using the ribs from a chest x-ray image as an example, it is shown how models of the different organs can be generated. The generic model of the chest region is built up by using a priori knowledge of the physical structure of the human body. The models of the individual organs are built up by using knowledge of the structure of the organs as well as other information contained within each image. Each image is unique and therefore information from the region surrounding the organs in the image has to be taken into account when adapting the generic model to individual images. Results showing the application of these techniques to x-ray images of the chest region, the labelling of individual organs, and the generation of models of the ribs are presented.

  5. 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

  6. 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

  7. 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

  8. 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.

  9. Appearance can be deceiving: using appearance models in color imaging

    NASA Astrophysics Data System (ADS)

    Johnson, Garrett M.

    2007-01-01

    As color imaging has evolved through the years, our toolset for understanding has similarly evolved. Research in color difference equations and uniform color spaces spawned tools such as CIELAB, which has had tremendous success over the years. Research on chromatic adaptation and other appearance phenomena then extended CIELAB to form the basis of color appearance models, such as CIECAM02. Color difference equations such as CIEDE2000 evolved to reconcile weaknesses in areas of the CIELAB space. Similarly, models such as S-CIELAB were developed to predict more spatially complex color difference calculations between images. Research in all of these fields is still going strong and there seems to be a trend towards unification of some of the tools, such as calculating color differences in a color appearance space. Along such lines, image appearance models have been developed that attempt to combine all of the above models and metric into one common framework. The goal is to allow the color imaging research to pick and choose the appropriate modeling toolset for their needs. Along these lines, the iCAM image appearance model framework was developed to study a variety of color imaging problems. These include image difference and image quality evaluations as well gamut mapping and high-dynamic range (HDR) rendering. It is important to stress that iCAM was not designed to be a complete color imaging solution, but rather a starting point for unifying models of color appearance, color difference, and spatial vision. As such the choice of model components is highly dependent on the problem being addressed. For example, with CIELAB it clearly evident that it is not necessary to use the associated color difference equations to have great success as a deviceindependent color space. Likewise, it may not be necessary to use the spatial filtering components of an image appearance model when performing image rendering. This paper attempts to shed some light on some of the

  10. AERIAL OF VEHICLE ASSEMBLY BUILDING & SURROUNDING AREA

    NASA Technical Reports Server (NTRS)

    1977-01-01

    AERIAL OF VEHICLE ASSEMBLY BUILDING & SURROUNDING AREA KSC-377C-0082.41 116-KSC-377C-82.41, P-15877, ARCHIVE-04151 Aerial view - Shuttle construction progress - VAB and Orbiter Processing Facilities - direction northwest.

  11. 3D model-based still image object categorization

    NASA Astrophysics Data System (ADS)

    Petre, Raluca-Diana; Zaharia, Titus

    2011-09-01

    This paper proposes a novel recognition scheme algorithm for semantic labeling of 2D object present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to infer the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Results obtained show promising performances, with recognition rate up to 84%, which opens interesting perspectives in terms of semantic metadata extraction from still images/videos.

  12. Modeling and simulation of biological systems from image data

    PubMed Central

    Sbalzarini, Ivo F

    2013-01-01

    This essay provides an introduction to the terminology, concepts, methods, and challenges of image-based modeling in biology. Image-based modeling and simulation aims at using systematic, quantitative image data to build predictive models of biological systems that can be simulated with a computer. This allows one to disentangle molecular mechanisms from effects of shape and geometry. Questions like “what is the functional role of shape” or “how are biological shapes generated and regulated” can be addressed in the framework of image-based systems biology. The combination of image quantification, model building, and computer simulation is illustrated here using the example of diffusion in the endoplasmic reticulum. PMID:23533152

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. MAPPING NON-INDIGENOUS EELGRASS ZOSTERA JAPONICA, ASSOCIATED MACROALGAE AND EMERGENT AQUATIC VEGETARIAN HABITATS IN A PACIFIC NORTHWEST ESTUARY USING NEAR-INFRARED COLOR AERIAL PHOTOGRAPHY AND A HYBRID IMAGE CLASSIFICATION TECHNIQUE

    EPA Science Inventory

    We conducted aerial photographic surveys of Oregon's Yaquina Bay estuary during consecutive summers from 1997 through 2001. Imagery was obtained during low tide exposures of intertidal mudflats, allowing use of near-infrared color film to detect and discriminate plant communitie...

  18. MAPPING EELGRASS SPECIES ZOSTERA ZAPONICA AND Z. MARINA, ASSOCIATED MACROALGAE AND EMERGENT AQUATIC VEGETATION HABITATS IN PACIFIC NORTHWEST ESTUARIES USING NEAR-INFRARED COLOR AERIAL PHOTOGRAPHY AND A HYBRID IMAGE CLASSIFICATION TECHNIQUE

    EPA Science Inventory

    Aerial photographic surveys of Oregon's Yaquina Bay estuary were conducted during consecutive summers from 1997 through 2000. Imagery was obtained during low tide exposures of intertidal mudflats, allowing use of near-infrared color film to detect and discriminate plant communit...

  19. Fuzzy object models for newborn brain MR image segmentation

    NASA Astrophysics Data System (ADS)

    Kobashi, Syoji; Udupa, Jayaram K.

    2013-03-01

    Newborn brain MR image segmentation is a challenging problem because of variety of size, shape and MR signal although it is the fundamental study for quantitative radiology in brain MR images. Because of the large difference between the adult brain and the newborn brain, it is difficult to directly apply the conventional methods for the newborn brain. Inspired by the original fuzzy object model introduced by Udupa et al. at SPIE Medical Imaging 2011, called fuzzy shape object model (FSOM) here, this paper introduces fuzzy intensity object model (FIOM), and proposes a new image segmentation method which combines the FSOM and FIOM into fuzzy connected (FC) image segmentation. The fuzzy object models are built from training datasets in which the cerebral parenchyma is delineated by experts. After registering FSOM with the evaluating image, the proposed method roughly recognizes the cerebral parenchyma region based on a prior knowledge of location, shape, and the MR signal given by the registered FSOM and FIOM. Then, FC image segmentation delineates the cerebral parenchyma using the fuzzy object models. The proposed method has been evaluated using 9 newborn brain MR images using the leave-one-out strategy. The revised age was between -1 and 2 months. Quantitative evaluation using false positive volume fraction (FPVF) and false negative volume fraction (FNVF) has been conducted. Using the evaluation data, a FPVF of 0.75% and FNVF of 3.75% were achieved. More data collection and testing are underway.

  20. Efficient pedestrian detection from aerial vehicles with object proposals and deep convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Minnehan, Breton; Savakis, Andreas

    2016-05-01

    As Unmanned Aerial Systems grow in numbers, pedestrian detection from aerial platforms is becoming a topic of increasing importance. By providing greater contextual information and a reduced potential for occlusion, the aerial vantage point provided by Unmanned Aerial Systems is highly advantageous for many surveillance applications, such as target detection, tracking, and action recognition. However, due to the greater distance between the camera and scene, targets of interest in aerial imagery are generally smaller and have less detail. Deep Convolutional Neural Networks (CNN's) have demonstrated excellent object classification performance and in this paper we adopt them to the problem of pedestrian detection from aerial platforms. We train a CNN with five layers consisting of three convolution-pooling layers and two fully connected layers. We also address the computational inefficiencies of the sliding window method for object detection. In the sliding window configuration, a very large number of candidate patches are generated from each frame, while only a small number of them contain pedestrians. We utilize the Edge Box object proposal generation method to screen candidate patches based on an "objectness" criterion, so that only regions that are likely to contain objects are processed. This method significantly reduces the number of image patches processed by the neural network and makes our classification method very efficient. The resulting two-stage system is a good candidate for real-time implementation onboard modern aerial vehicles. Furthermore, testing on three datasets confirmed that our system offers high detection accuracy for terrestrial pedestrian detection in aerial imagery.

  1. Highway 3D model from image and lidar data

    NASA Astrophysics Data System (ADS)

    Chen, Jinfeng; Chu, Henry; Sun, Xiaoduan

    2014-05-01

    We present a new method of highway 3-D model construction developed based on feature extraction in highway images and LIDAR data. We describe the processing road coordinate data that connect the image frames to the coordinates of the elevation data. Image processing methods are used to extract sky, road, and ground regions as well as significant objects (such as signs and building fronts) in the roadside for the 3D model. LIDAR data are interpolated and processed to extract the road lanes as well as other features such as trees, ditches, and elevated objects to form the 3D model. 3D geometry reasoning is used to match the image features to the 3D model. Results from successive frames are integrated to improve the final model.

  2. 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.

  3. 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.

  4. 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. PMID:17699924

  5. 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.

  6. MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics.

    PubMed

    Niessen, Wiro J

    2016-10-01

    MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role. PMID:27344937

  7. MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics.

    PubMed

    Niessen, Wiro J

    2016-10-01

    MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role.

  8. Digital Imaging and Conservation: Model Guidelines.

    ERIC Educational Resources Information Center

    Dean, John F.

    2003-01-01

    Examines the intersection of conservation and digital imaging based on guidelines at the Cornell University (Ithaca, NY) library. Discusses the digitization of artifacts; assessing the condition prior to scanning; scanning considerations, including temperature and humidity, lighting, and security; stable storage of artifacts after scanning; and…

  9. A procedure for orthorectification of sub-decimeter resolution imagery obtained with an unmanned aerial vehicle (UAV)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Digital aerial photography acquired with unmanned aerial vehicles (UAVs) has great value for resource management due to the flexibility and relatively low cost for image acquisition, and very high resolution imagery (5 cm) which allows for mapping bare soil and vegetation types, structure and patter...

  10. Aerial field guide

    NASA Technical Reports Server (NTRS)

    Nummedal, D.

    1978-01-01

    There are two overflights planned for the field conference; one for the Cheney-Palouse tract of the eastern channeled scabland, the other covering the coulees and basins of the western region. The approximate flight lines are indicated on the accompanying LANDSAT images. The first flight will follow the eastern margin of this large scabland tract, passing a series of loess remnants, gravel bars and excavated rock basins. The western scablands overflight will provide a review of the structurally controlled complex pattern of large-scale erosion and deposition characteristic of the region between the upper Grand Coulee (Banks Lake) and the Pasco Basin.

  11. Sonar image segmentation using an unsupervised hierarchical MRF model.

    PubMed

    Mignotte, M; Collet, C; Perez, P; Bouthemy, P

    2000-01-01

    This paper is concerned with hierarchical Markov random field (MRP) models and their application to sonar image segmentation. We present an original hierarchical segmentation procedure devoted to images given by a high-resolution sonar. The sonar image is segmented into two kinds of regions: shadow (corresponding to a lack of acoustic reverberation behind each object lying on the sea-bed) and sea-bottom reverberation. The proposed unsupervised scheme takes into account the variety of the laws in the distribution mixture of a sonar image, and it estimates both the parameters of noise distributions and the parameters of the Markovian prior. For the estimation step, we use an iterative technique which combines a maximum likelihood approach (for noise model parameters) with a least-squares method (for MRF-based prior). In order to model more precisely the local and global characteristics of image content at different scales, we introduce a hierarchical model involving a pyramidal label field. It combines coarse-to-fine causal interactions with a spatial neighborhood structure. This new method of segmentation, called the scale causal multigrid (SCM) algorithm, has been successfully applied to real sonar images and seems to be well suited to the segmentation of very noisy images. The experiments reported in this paper demonstrate that the discussed method performs better than other hierarchical schemes for sonar image segmentation.

  12. Image Discrimination Models for Object Detection in Natural Backgrounds

    NASA Technical Reports Server (NTRS)

    Ahumada, A. J., Jr.

    2000-01-01

    This paper reviews work accomplished and in progress at NASA Ames relating to visual target detection. The focus is on image discrimination models, starting with Watson's pioneering development of a simple spatial model and progressing through this model's descendents and extensions. The application of image discrimination models to target detection will be described and results reviewed for Rohaly's vehicle target data and the Search 2 data. The paper concludes with a description of work we have done to model the process by which observers learn target templates and methods for elucidating those templates.

  13. A parametric vocal fold model based on magnetic resonance imaging.

    PubMed

    Wu, Liang; Zhang, Zhaoyan

    2016-08-01

    This paper introduces a parametric three-dimensional body-cover vocal fold model based on magnetic resonance imaging (MRI) of the human larynx. Major geometric features that are observed in the MRI images but missing in current vocal fold models are discussed, and their influence on vocal fold vibration is evaluated using eigenmode analysis. Proper boundary conditions for the model are also discussed. Based on control parameters corresponding to anatomic landmarks that can be easily measured, this model can be adapted toward a subject-specific vocal fold model for voice production research and clinical applications. PMID:27586774

  14. Simplified Model for Analysing Ion/Photoelectron Images

    NASA Astrophysics Data System (ADS)

    Zhu, Jing-Yi; Wang, Bing-Xing; Guo, Wei; Wang, Yan-Qiu; Wang, Li

    2007-07-01

    Based on the Onion-Peeling algorithm (OPA) principle, we present a simplified model for analysing photoion and photoelectron images, which allows the analysis of experimental raw images. A three-dimensional distribution of the nascent charged particles, from which the radial and angular distributions are deduced, can be obtained more easily by this model than by the commonly used procedures. The analysis results of Xe photoelectron images by this model are compared with those from the standard Hankel-Abel inversion. The results imply that this model can be used for complicated (many peaks) and `difficult' (low signal-to-noise) images with cylindrical symmetries, and can provide a reliable reconstruction in some cases when the commonly used Hankel Abel transform method fails.

  15. Cardiovascular imaging: what have we learned from animal models?

    PubMed Central

    Santos, Arnoldo; Fernández-Friera, Leticia; Villalba, María; López-Melgar, Beatriz; España, Samuel; Mateo, Jesús; Mota, Ruben A.; Jiménez-Borreguero, Jesús; Ruiz-Cabello, Jesús

    2015-01-01

    Cardiovascular imaging has become an indispensable tool for patient diagnosis and follow up. Probably the wide clinical applications of imaging are due to the possibility of a detailed and high quality description and quantification of cardiovascular system structure and function. Also phenomena that involve complex physiological mechanisms and biochemical pathways, such as inflammation and ischemia, can be visualized in a non-destructive way. The widespread use and evolution of imaging would not have been possible without animal studies. Animal models have allowed for instance, (i) the technical development of different imaging tools, (ii) to test hypothesis generated from human studies and finally, (iii) to evaluate the translational relevance assessment of in vitro and ex-vivo results. In this review, we will critically describe the contribution of animal models to the use of biomedical imaging in cardiovascular medicine. We will discuss the characteristics of the most frequent models used in/for imaging studies. We will cover the major findings of animal studies focused in the cardiovascular use of the repeatedly used imaging techniques in clinical practice and experimental studies. We will also describe the physiological findings and/or learning processes for imaging applications coming from models of the most common cardiovascular diseases. In these diseases, imaging research using animals has allowed the study of aspects such as: ventricular size, shape, global function, and wall thickening, local myocardial function, myocardial perfusion, metabolism and energetic assessment, infarct quantification, vascular lesion characterization, myocardial fiber structure, and myocardial calcium uptake. Finally we will discuss the limitations and future of imaging research with animal models. PMID:26539113

  16. Image Retrieval as Linguistic and Nonlinguistic Visual Model Matching.

    ERIC Educational Resources Information Center

    Heidorn, P. Bryan

    1999-01-01

    Reviews research on how people use mental models of images in information retrieval. Discusses cognitive and social processes that give rise the visual models shaped by indexers and searchers. Examines the representation of objects and shapes in visual mental models and how both content-based and concept-based indexes capture aspects of these…

  17. Aerial Observation Needs Workshop, May 13-14, 2015

    SciTech Connect

    Nasiri, Shaima; Serbin, Shawn; Lesmes, David; Petty, Rick; Schmid, Beat; Vogelmann, Andrew; de Boer, Gijs; Dafflon, Baptiste; Guenther, Alex; Moore, David

    2015-10-01

    The mission of the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research (BER) within the U.S. Department of Energy's (DOE) Office of Science is "to advance a robust, predictive understanding of Earth's climate and environmental systems and to inform the development of sustainable solutions to the nation's energy and environmental challenges." Accomplishing this mission requires aerial observations of the atmospheric and terrestrial components of the climate system. CESD is assessing its current and future aerial observation needs to develop a strategy and roadmap of capability requirements for the next decade. To facilitate this process, a workshop was convened that consisted of invited experts in the atmospheric and terrestrial sciences, airborne observations, and modeling. This workshop report summarizes the community input prior to and during the workshop on research challenges and opportunities, as well as specific science questions and observational needs that require aerial observations to address.

  18. A model of PSF estimation for coded mask infrared imaging

    NASA Astrophysics Data System (ADS)

    Zhang, Ao; Jin, Jie; Wang, Qing; Yang, Jingyu; Sun, Yi

    2014-11-01

    The point spread function (PSF) of imaging system with coded mask is generally acquired by practical measure- ment with calibration light source. As the thermal radiation of coded masks are relatively severe than it is in visible imaging systems, which buries the modulation effects of the mask pattern, it is difficult to estimate and evaluate the performance of mask pattern from measured results. To tackle this problem, a model for infrared imaging systems with masks is presented in this paper. The model is composed with two functional components, the coded mask imaging with ideal focused lenses and the imperfection imaging with practical lenses. Ignoring the thermal radiation, the systems PSF can then be represented by a convolution of the diffraction pattern of mask with the PSF of practical lenses. To evaluate performances of different mask patterns, a set of criterion are designed according to different imaging and recovery methods. Furthermore, imaging results with inclined plane waves are analyzed to achieve the variation of PSF within the view field. The influence of mask cell size is also analyzed to control the diffraction pattern. Numerical results show that mask pattern for direct imaging systems should have more random structures, while more periodic structures are needed in system with image reconstruction. By adjusting the combination of random and periodic arrangement, desired diffraction pattern can be achieved.

  19. Super-resolution image reconstruction using diffuse source models.

    PubMed

    Ellis, Michael A; Viola, Francesco; Walker, William F

    2010-06-01

    Image reconstruction is central to many scientific fields, from medical ultrasound and sonar to computed tomography and computer vision. Although lenses play a critical reconstruction role in these fields, digital sensors enable more sophisticated computational approaches. A variety of computational methods have thus been developed, with the common goal of increasing contrast and resolution to extract the greatest possible information from raw data. This paper describes a new image reconstruction method named the Diffuse Time-domain Optimized Near-field Estimator (dTONE). dTONE represents each hypothetical target in the system model as a diffuse region of targets rather than a single discrete target, which more accurately represents the experimental data that arise from signal sources in continuous space, with no additional computational requirements at the time of image reconstruction. Simulation and experimental ultrasound images of animal tissues show that dTONE achieves image resolution and contrast far superior to those of conventional image reconstruction methods. We also demonstrate the increased robustness of the diffuse target model to major sources of image degradation through the addition of electronic noise, phase aberration and magnitude aberration to ultrasound simulations. Using experimental ultrasound data from a tissue-mimicking phantom containing a 3-mm-diameter anechoic cyst, the conventionally reconstructed image has a cystic contrast of -6.3 dB, whereas the dTONE image has a cystic contrast of -14.4 dB.

  20. BgCut: automatic ship detection from UAV images.

    PubMed

    Xu, Chao; Zhang, Dongping; Zhang, Zhengning; Feng, Zhiyong

    2014-01-01

    Ship detection in static UAV aerial images is a fundamental challenge in sea target detection and precise positioning. In this paper, an improved universal background model based on Grabcut algorithm is proposed to segment foreground objects from sea automatically. First, a sea template library including images in different natural conditions is built to provide an initial template to the model. Then the background trimap is obtained by combing some templates matching with region growing algorithm. The output trimap initializes Grabcut background instead of manual intervention and the process of segmentation without iteration. The effectiveness of our proposed model is demonstrated by extensive experiments on a certain area of real UAV aerial images by an airborne Canon 5D Mark. The proposed algorithm is not only adaptive but also with good segmentation. Furthermore, the model in this paper can be well applied in the automated processing of industrial images for related researches.

  1. BgCut: automatic ship detection from UAV images.

    PubMed

    Xu, Chao; Zhang, Dongping; Zhang, Zhengning; Feng, Zhiyong

    2014-01-01

    Ship detection in static UAV aerial images is a fundamental challenge in sea target detection and precise positioning. In this paper, an improved universal background model based on Grabcut algorithm is proposed to segment foreground objects from sea automatically. First, a sea template library including images in different natural conditions is built to provide an initial template to the model. Then the background trimap is obtained by combing some templates matching with region growing algorithm. The output trimap initializes Grabcut background instead of manual intervention and the process of segmentation without iteration. The effectiveness of our proposed model is demonstrated by extensive experiments on a certain area of real UAV aerial images by an airborne Canon 5D Mark. The proposed algorithm is not only adaptive but also with good segmentation. Furthermore, the model in this paper can be well applied in the automated processing of industrial images for related researches. PMID:24977182

  2. BgCut: Automatic Ship Detection from UAV Images

    PubMed Central

    Zhang, Zhengning; Feng, Zhiyong

    2014-01-01

    Ship detection in static UAV aerial images is a fundamental challenge in sea target detection and precise positioning. In this paper, an improved universal background model based on Grabcut algorithm is proposed to segment foreground objects from sea automatically. First, a sea template library including images in different natural conditions is built to provide an initial template to the model. Then the background trimap is obtained by combing some templates matching with region growing algorithm. The output trimap initializes Grabcut background instead of manual intervention and the process of segmentation without iteration. The effectiveness of our proposed model is demonstrated by extensive experiments on a certain area of real UAV aerial images by an airborne Canon 5D Mark. The proposed algorithm is not only adaptive but also with good segmentation. Furthermore, the model in this paper can be well applied in the automated processing of industrial images for related researches. PMID:24977182

  3. Advances and challenges in deformable image registration: From image fusion to complex motion modelling.

    PubMed

    Schnabel, Julia A; Heinrich, Mattias P; Papież, Bartłomiej W; Brady, Sir J Michael

    2016-10-01

    Over the past 20 years, the field of medical image registration has significantly advanced from multi-modal image fusion to highly non-linear, deformable image registration for a wide range of medical applications and imaging modalities, involving the compensation and analysis of physiological organ motion or of tissue changes due to growth or disease patterns. While the original focus of image registration has predominantly been on correcting for rigid-body motion of brain image volumes acquired at different scanning sessions, often with different modalities, the advent of dedicated longitudinal and cross-sectional brain studies soon necessitated the development of more sophisticated methods that are able to detect and measure local structural or functional changes, or group differences. Moving outside of the brain, cine imaging and dynamic imaging required the development of deformable image registration to directly measure or compensate for local tissue motion. Since then, deformable image registration has become a general enabling technology. In this work we will present our own contributions to the state-of-the-art in deformable multi-modal fusion and complex motion modelling, and then discuss remaining challenges and provide future perspectives to the field.

  4. Advances and challenges in deformable image registration: From image fusion to complex motion modelling.

    PubMed

    Schnabel, Julia A; Heinrich, Mattias P; Papież, Bartłomiej W; Brady, Sir J Michael

    2016-10-01

    Over the past 20 years, the field of medical image registration has significantly advanced from multi-modal image fusion to highly non-linear, deformable image registration for a wide range of medical applications and imaging modalities, involving the compensation and analysis of physiological organ motion or of tissue changes due to growth or disease patterns. While the original focus of image registration has predominantly been on correcting for rigid-body motion of brain image volumes acquired at different scanning sessions, often with different modalities, the advent of dedicated longitudinal and cross-sectional brain studies soon necessitated the development of more sophisticated methods that are able to detect and measure local structural or functional changes, or group differences. Moving outside of the brain, cine imaging and dynamic imaging required the development of deformable image registration to directly measure or compensate for local tissue motion. Since then, deformable image registration has become a general enabling technology. In this work we will present our own contributions to the state-of-the-art in deformable multi-modal fusion and complex motion modelling, and then discuss remaining challenges and provide future perspectives to the field. PMID:27364430

  5. Color Sparse Representations for Image Processing: Review, Models, and Prospects.

    PubMed

    Barthélemy, Quentin; Larue, Anthony; Mars, Jérôme I

    2015-11-01

    Sparse representations have been extended to deal with color images composed of three channels. A review of dictionary-learning-based sparse representations for color images is made here, detailing the differences between the models, and comparing their results on the real and simulated data. These models are considered in a unifying framework that is based on the degrees of freedom of the linear filtering/transformation of the color channels. Moreover, this allows it to be shown that the scalar quaternionic linear model is equivalent to constrained matrix-based color filtering, which highlights the filtering implicitly applied through this model. Based on this reformulation, the new color filtering model is introduced, using unconstrained filters. In this model, spatial morphologies of color images are encoded by atoms, and colors are encoded by color filters. Color variability is no longer captured in increasing the dictionary size, but with color filters, this gives an efficient color representation.

  6. Multilabel Image Annotation Based on Double-Layer PLSA Model

    PubMed Central

    Zhang, Jing; Li, Da; Hu, Weiwei; Chen, Zhihua; Yuan, Yubo

    2014-01-01

    Due to the semantic gap between visual features and semantic concepts, automatic image annotation has become a difficult issue in computer vision recently. We propose a new image multilabel annotation method based on double-layer probabilistic latent semantic analysis (PLSA) in this paper. The new double-layer PLSA model is constructed to bridge the low-level visual features and high-level semantic concepts of images for effective image understanding. The low-level features of images are represented as visual words by Bag-of-Words