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Sample records for aerial image based

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

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

    DTIC Science & Technology

    1989-08-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  5. 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%.

  6. 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.

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

    PubMed

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

    2014-07-01

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

  8. Aerial Photographs and Satellite Images

    USGS Publications Warehouse

    ,

    1997-01-01

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

  9. 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.

  10. 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.

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

    PubMed

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Makrogiannis, Sokratis; Bourbakis, Nikolaos G.

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

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

    DTIC Science & Technology

    1988-01-19

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

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

    PubMed Central

    Popescu, Dan; Ichim, Loretta; Stoican, Florin

    2017-01-01

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

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

    PubMed

    Popescu, Dan; Ichim, Loretta; Stoican, Florin

    2017-02-23

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

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

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

    2017-02-10

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

  1. 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.

  2. 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

  3. 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.

  4. Detection of linear features in aerial images

    NASA Astrophysics Data System (ADS)

    Gao, Rui

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

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Shi, Wenxuan; Li, Jie

    2012-12-01

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

  8. 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.

  9. 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.

  10. [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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

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

    PubMed

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

    2016-06-22

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

  17. 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

  18. 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...

  19. 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.

  20. 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

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

    PubMed

    Ma, Xu; Cheng, Yongmei; Hao, Shuai

    2016-12-10

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

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

    DTIC Science & Technology

    1983-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  4. System for interactive management of aerial imaging campaigns

    NASA Astrophysics Data System (ADS)

    Wypych, Tom; Kuester, Falko

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

  5. Orientation Strategies for Aerial Oblique Images

    NASA Astrophysics Data System (ADS)

    Wiedemann, A.; Moré, J.

    2012-07-01

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

  6. 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.

  7. Aerial photographs and satellite images

    USGS Publications Warehouse

    ,

    1995-01-01

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

  8. Investigating an Aerial Image First

    ERIC Educational Resources Information Center

    Wyrembeck, Edward P.; Elmer, Jeffrey S.

    2006-01-01

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

  9. 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.

  10. 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.

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

    PubMed

    Kakeya, Hideki; Ishizuka, Shuta; Sato, Yuya

    2014-10-06

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

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

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

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

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

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

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

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

    NASA Astrophysics Data System (ADS)

    Jadkowski, Mark A.

    1996-03-01

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

  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. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed Central

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

    2008-01-01

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

  20. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed

    Hammoudi, Karim; Dornaika, Fadi

    2011-01-01

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

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

    PubMed Central

    Hammoudi, Karim; Dornaika, Fadi

    2011-01-01

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

  5. 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

  6. 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.

  7. 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

  8. Use of simulated neural networks of aerial image classification

    NASA Technical Reports Server (NTRS)

    Medina, Frances I.; Vasquez, Ramon

    1991-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Hidayat, Husnul; Cahyono, A. B.

    2016-11-01

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

  10. 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.

  11. 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.

  12. 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.

  13. MEMS Based Micro Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Joshi, Niranjan; Köhler, Elof; Enoksson, Peter

    2016-10-01

    Designing a flapping wing insect robot requires understanding of insect flight mechanisms, wing kinematics and aerodynamic forces. These subsystems are interconnected and their dependence on one another affects the overall performance. Additionally it requires an artificial muscle like actuator and transmission to power the wings. Several kinds of actuators and mechanisms are candidates for this application with their own strengths and weaknesses. This article provides an overview of the insect scaled flight mechanism along with discussion of various methods to achieve the Micro Aerial Vehicle (MAV) flight. Ongoing projects in Chalmers is aimed at developing a low cost and low manufacturing time MAV. The MAV design considerations and design specifications are mentioned. The wings are manufactured using 3D printed carbon fiber and are under experimental study.

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  15. Advanced Image Processing of Aerial Imagery

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  16. 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.

  17. Automated updating of road databases from aerial images

    NASA Astrophysics Data System (ADS)

    Baltsavias, Emmanuel; Zhang, Chunsun

    2005-03-01

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

  18. 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.

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  1. 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...

  2. 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

  3. 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...

  4. 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.

  5. 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.

  6. Feature extraction with LIDAR data and aerial images

    NASA Astrophysics Data System (ADS)

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

    2006-10-01

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

  7. Deep person re-identification in aerial images

    NASA Astrophysics Data System (ADS)

    Schumann, Arne; Schuchert, Tobias

    2016-10-01

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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  14. 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.

  15. Cost-Based Analysis of Unmanned Aerial Vehicles/Unmanned Aerial Systems in Filling the Role of Logistical Support

    DTIC Science & Technology

    2014-12-01

    UAVs in the U .S . Department of D efense (D OD) inv entory as w ell as the traditional aircraft ctmently used for logistical pwposes. Then, using a...14. SUBJECT TERMS 15. NUMBER OF Cost-benefit, Cost-based, Unmanned Aerial Vehicles, Unmanned Aerial Systems, UAV , UAS, PAGES Logistics, Supp01t...thesis conducts a comparative cost analysis for using unmanned aerial vehicles ( UAVs )/unmanned aerial systems (UASs) for logistical resupply purposes

  16. 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.

  17. 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…

  18. 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.

  19. 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.

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

    DTIC Science & Technology

    2015-03-01

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

  1. Aerial view of entire LTA base after completion of both ...

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

    Aerial view of entire LTA base after completion of both LTA ship hangars. Date unknown but probably circa 1945. - Marine Corps Air Station Tustin, Northern Lighter Than Air Ship Hangar, Meffett Avenue & Maxfield Street, Tustin, Orange County, CA

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. 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

  4. 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.

  5. Research of aerial camera focal pane micro-displacement measurement system based on Michelson interferometer

    NASA Astrophysics Data System (ADS)

    Wang, Shu-juan; Zhao, Yu-liang; Li, Shu-jun

    2014-09-01

    The aerial camera focal plane in the correct position is critical to the imaging quality. In order to adjust the aerial camera focal plane displacement caused in the process of maintenance, a new micro-displacement measuring system of aerial camera focal plane in view of the Michelson interferometer has been designed in this paper, which is based on the phase modulation principle, and uses the interference effect to realize the focal plane of the micro-displacement measurement. The system takes He-Ne laser as the light source, uses the Michelson interference mechanism to produce interference fringes, changes with the motion of the aerial camera focal plane interference fringes periodically, and records the periodicity of the change of the interference fringes to obtain the aerial camera plane displacement; Taking linear CCD and its driving system as the interference fringes picking up tool, relying on the frequency conversion and differentiating system, the system determines the moving direction of the focal plane. After data collecting, filtering, amplifying, threshold comparing, counting, CCD video signals of the interference fringes are sent into the computer processed automatically, and output the focal plane micro displacement results. As a result, the focal plane micro displacement can be measured automatically by this system. This system uses linear CCD as the interference fringes picking up tool, greatly improving the counting accuracy and eliminated the artificial counting error almost, improving the measurement accuracy of the system. The results of the experiments demonstrate that: the aerial camera focal plane displacement measurement accuracy is 0.2nm. While tests in the laboratory and flight show that aerial camera focal plane positioning is accurate and can satisfy the requirement of the aerial camera imaging.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

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

    2009-10-01

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

  11. 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.

  12. 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

  13. 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.

  14. 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.

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

    NASA Technical Reports Server (NTRS)

    Clark, M. M.

    1971-01-01

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

  16. 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.

  17. 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.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

    Greenberg, Shlomo; Guterman, Hugo

    1996-08-01

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

  20. 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.

  1. 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.

  2. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. 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...

  5. Texture mapping based on multiple aerial imageries in urban areas

    NASA Astrophysics Data System (ADS)

    Zhou, Guoqing; Ye, Siqi; Wang, Yuefeng; Han, Caiyun; Wang, Chenxi

    2015-12-01

    In the realistic 3D model reconstruction, the requirement of the texture is very high. Texture is one of the key factors that affecting realistic of the model and using texture mapping technology to realize. In this paper we present a practical approach of texture mapping based on photogrammetry theory from multiple aerial imageries in urban areas. By collinearity equation to matching the model and imageries, and in order to improving the quality of texture, we describe an automatic approach for select the optimal texture to realized 3D building from the aerial imageries of many strip. The texture of buildings can be automatically matching by the algorithm. The experimental results show that the platform of texture mapping process has a high degree of automation and improve the efficiency of the 3D modeling reconstruction.

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

    NASA Astrophysics Data System (ADS)

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

    2007-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

  8. Effective delineation of urban flooded areas based on aerial ortho-photo imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Ying; Guindon, Bert; Raymond, Don; Hong, Gang

    2016-10-01

    The combination of rapid global urban growth and climate change has resulted in increased occurrence of major urban flood events across the globe. The distribution of flooded area is one of the key information layers for applications of emergency planning and response management. While SAR systems and technologies have been widely used for flood area delineation, radar images suffer from range ambiguities arising from corner reflection effects and shadowing in dense urban settings. A new mapping framework is proposed for the extraction and quantification of flood extent based on aerial optical multi-spectral imagery and ancillary data. This involves first mapping of flood areas directly visible to the sensor. Subsequently, the complete area of submergence is estimated from this initial mapping and inference techniques based on baseline data such as land cover and GIS information such as available digital elevation models. The methodology has been tested and proven effective using aerial photography for the case of the 2013 flood in Calgary, Canada.

  9. 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.

  10. 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.

  11. 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...

  12. 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 ...

  13. Registering aerial video images using the projective constraint.

    PubMed

    Jackson, Brian P; Goshtasby, A Ardeshir

    2010-03-01

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

  14. 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.

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

    NASA Astrophysics Data System (ADS)

    Alevizos, E.

    2012-04-01

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

  16. 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

  17. 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.

  18. Spatial Feature Evaluation for Aerial Scene Analysis

    SciTech Connect

    Swearingen, Thomas S; Cheriyadat, Anil M

    2013-01-01

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

  19. Adaptive vision-based control of an unmanned aerial vehicle without linear velocity measurements.

    PubMed

    Jabbari Asl, Hamed; Yoon, Jungwon

    2016-11-01

    In this paper, an image-based visual servo controller is designed for an unmanned aerial vehicle. The main objective is to use flow of image features as the velocity cue to compensate for the low quality of linear velocity information obtained from accelerometers. Nonlinear observers are designed to estimate this flow. The proposed controller is bounded, which can help to keep the target points in the field of view of the camera. The main advantages over the previous full dynamic observer-based methods are that, the controller is robust with respect to unknown image depth, and also no yaw information is required. The complete stability analysis is presented and asymptotic convergence of the error signals is guaranteed. Simulation results show the effectiveness of the proposed approach.

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

    NASA Astrophysics Data System (ADS)

    Sheng, Yongwei

    2000-12-01

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

  1. 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

  2. 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.

  3. Image Dependent Relative Formation Navigation for Autonomous Aerial Refueling

    DTIC Science & Technology

    2011-03-01

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

  4. 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.

  5. 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.

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

    SciTech Connect

    Birch, Gabriel Carlisle; Woo, Bryana Lynn

    2017-01-01

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

  7. 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.

  8. Aerial imaging with manned aircraft for precision agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

    Terletzky, Pat; Ramsey, Robert Douglas

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Chandler, Eric V.; Fish, David E.

    2014-06-01

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

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

    SciTech Connect

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

    1994-11-01

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

  12. 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.

  13. 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.

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

    NASA Astrophysics Data System (ADS)

    Horváth, Gábor; Buchta, Krisztián; Varjú, Dezsö

    2003-06-01

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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-11-01

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

  17. Updating road databases from shape-files using aerial images

    NASA Astrophysics Data System (ADS)

    Häufel, Gisela; Bulatov, Dimitri; Pohl, Melanie

    2015-10-01

    Road databases are an important part of geo data infrastructure. The knowledge about their characteristics and course is essential for urban planning, navigation or evacuation tasks. Starting from OpenStreetMap (OSM) shape-file data for street networks, we introduce an algorithm to enrich these available road maps by new maps which are based on other airborne sensor technology. In our case, these are results of our context-based urban terrain reconstruction process. We wish to enhance the use of road databases by computing additional junctions, narrow passages and other items which may emerge due to changes in the terrain. This is relevant for various military and civil applications.

  18. Vision-Based SLAM System for Unmanned Aerial Vehicles

    PubMed Central

    Munguía, Rodrigo; Urzua, Sarquis; Bolea, Yolanda; Grau, Antoni

    2016-01-01

    The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs). The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The estimator is designed in order to fuse the measurements obtained from: (i) an orientation sensor (AHRS); (ii) a position sensor (GPS); and (iii) a monocular camera. The estimated state consists of the full state of the vehicle: position and orientation and their first derivatives, as well as the location of the landmarks observed by the camera. The position sensor will be used only during the initialization period in order to recover the metric scale of the world. Afterwards, the estimated map of landmarks will be used to perform a fully vision-based navigation when the position sensor is not available. Experimental results obtained with simulations and real data show the benefits of the inclusion of camera measurements into the system. In this sense the estimation of the trajectory of the vehicle is considerably improved, compared with the estimates obtained using only the measurements from the position sensor, which are commonly low-rated and highly noisy. PMID:26999131

  19. Vision-Based SLAM System for Unmanned Aerial Vehicles.

    PubMed

    Munguía, Rodrigo; Urzua, Sarquis; Bolea, Yolanda; Grau, Antoni

    2016-03-15

    The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs). The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The estimator is designed in order to fuse the measurements obtained from: (i) an orientation sensor (AHRS); (ii) a position sensor (GPS); and (iii) a monocular camera. The estimated state consists of the full state of the vehicle: position and orientation and their first derivatives, as well as the location of the landmarks observed by the camera. The position sensor will be used only during the initialization period in order to recover the metric scale of the world. Afterwards, the estimated map of landmarks will be used to perform a fully vision-based navigation when the position sensor is not available. Experimental results obtained with simulations and real data show the benefits of the inclusion of camera measurements into the system. In this sense the estimation of the trajectory of the vehicle is considerably improved, compared with the estimates obtained using only the measurements from the position sensor, which are commonly low-rated and highly noisy.

  20. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  4. 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.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  7. State transformation-based dynamic visual servoing for an unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Xie, Hui; Lynch, Alan F.

    2016-05-01

    In this paper, we propose a visual servoing control for a quadrotor unmanned aerial vehicle (UAV) which is based on a state transformation technique. The UAV is equipped with a single downwards facing camera, and the motion control objective is the regulation of relative displacement and yaw to a stationary visual target located on the ground. The state transformation is defined by a system of partial differential equations (PDEs) which eliminate roll and pitch rate dependence in the transformed image feature kinematics. A method for computing the general solutions of these PDEs is given, and we show a particular solution reduces to an established virtual camera approach. We treat point and line cases and introduce image moment features defined in the virtual camera image plane. Robustness of the control design is improved by accounting for attitude measurement bias, and uncertainty in thrust gain, mass, and image feature depth. The asymptotic stability of the closed-loop is proven. The method is based on a simple proportional-integral-derivative (PID) structure which can be readily implemented on-board. Experimental results show improved performance relative to previous work.

  8. 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.

  9. 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.

  10. A Spreadsheet-based GIS tool for planning aerial photography

    EPA Science Inventory

    The U.S.EPA's Pacific Coastal Ecology Branch has developed a tool which facilitates planning aerial photography missions. This tool is an Excel spreadsheet which accepts various input parameters such as desired photo-scale and boundary coordinates of the study area and compiles ...

  11. 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.

  12. 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.

  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. Obstacle regions extraction method for unmanned aerial vehicles based on space-time tensor descriptor

    NASA Astrophysics Data System (ADS)

    Wu, Zhenglong; Li, Jie; Guan, Zhenyu; Yang, Huan

    2016-09-01

    Obstacle avoidance is an important and challenging task for the autonomous flight of unmanned aerial vehicles. Obstacle regions extraction from image sequences is a critical prerequisite in obstacle avoidance. We propose an obstacle regions extraction method based on space-time tensor descriptor. In our method, first, the space-time tensor descriptor is defined and a criterion function based on the descriptor of extracting space-time interest points (STIPs) is designed. Then a self-adaptive clustering of STIPs approach is presented to locate the possible obstacle regions. Finally, an improved level set algorithm is applied with the result of clustering to extract the obstacle regions. We demonstrate the experiments of obstacle regions extraction by our method on image sequences. Sequences are captured in indoor simulative obstacle avoidance environments and outdoor real flight obstacle avoidance environments. Experimental results validate that our method can effectively complete extraction and segmentation of obstacle region with captured images. Compared with the state-of-the-art methods, our method performs well to extract the contours of obstacle regions on the whole and significantly improves segmentation speed.

  15. Base Map Analysis of Coastal Changes Using Aerial Photography.

    DTIC Science & Technology

    1981-11-01

    should be sufficient for most coastal engineering needs (Everts and Czerniak , 1977). When structures are present and near inlets, river mouths, or...test at Ludlam Beach, New Jersey, the wetted bound was identifiable on 80 percent of aerial photos analyzed (Everts, DeWall, and Czerniak , 1980). c...New Jersey, analyzed by Everts, DeWall, and Czerniak (1980), provided a means to evaluate the effectiveness of the use of the waterline and wetted

  16. Vision-Based Tracking for Unmanned Aerial Vehicles

    DTIC Science & Technology

    2006-01-01

    Unmanned Aerial Vehicles Authors: V. K. Chitrakaran, D. M. Dawson, H. Kannan, and M. Feemster Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including

  17. 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

  18. 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

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

    NASA Astrophysics Data System (ADS)

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

    1987-03-01

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

  20. Decision Level Fusion of LIDAR Data and Aerial Color Imagery Based on Bayesian Theory for Urban Area Classification

    NASA Astrophysics Data System (ADS)

    Rastiveis, H.

    2015-12-01

    Airborne Light Detection and Ranging (LiDAR) generates high-density 3D point clouds to provide a comprehensive information from object surfaces. Combining this data with aerial/satellite imagery is quite promising for improving land cover classification. In this study, fusion of LiDAR data and aerial imagery based on Bayesian theory in a three-level fusion algorithm is presented. In the first level, pixel-level fusion, the proper descriptors for both LiDAR and image data are extracted. In the next level of fusion, feature-level, using extracted features the area are classified into six classes of "Buildings", "Trees", "Asphalt Roads", "Concrete roads", "Grass" and "Cars" using Naïve Bayes classification algorithm. This classification is performed in three different strategies: (1) using merely LiDAR data, (2) using merely image data, and (3) using all extracted features from LiDAR and image. The results of three classifiers are integrated in the last phase, decision level fusion, based on Naïve Bayes algorithm. To evaluate the proposed algorithm, a high resolution color orthophoto and LiDAR data over the urban areas of Zeebruges, Belgium were applied. Obtained results from the decision level fusion phase revealed an improvement in overall accuracy and kappa coefficient.

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

    PubMed

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

    2008-12-01

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

  2. 33 CFR 334.700 - Choctawhatchee Bay, aerial gunnery ranges, Air Armament Center, Eglin Air Force Base, Fla.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... gunnery ranges, Air Armament Center, Eglin Air Force Base, Fla. 334.700 Section 334.700 Navigation and... RESTRICTED AREA REGULATIONS § 334.700 Choctawhatchee Bay, aerial gunnery ranges, Air Armament Center, Eglin Air Force Base, Fla. (a) The danger zones—(1) Aerial gunnery range in west part of Choctawhatchee...

  3. 33 CFR 334.700 - Choctawhatchee Bay, aerial gunnery ranges, Air Armament Center, Eglin Air Force Base, Fla.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... gunnery ranges, Air Armament Center, Eglin Air Force Base, Fla. 334.700 Section 334.700 Navigation and... RESTRICTED AREA REGULATIONS § 334.700 Choctawhatchee Bay, aerial gunnery ranges, Air Armament Center, Eglin Air Force Base, Fla. (a) The danger zones—(1) Aerial gunnery range in west part of Choctawhatchee...

  4. 33 CFR 334.700 - Choctawhatchee Bay, aerial gunnery ranges, Air Armament Center, Eglin Air Force Base, Fla.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... gunnery ranges, Air Armament Center, Eglin Air Force Base, Fla. 334.700 Section 334.700 Navigation and... RESTRICTED AREA REGULATIONS § 334.700 Choctawhatchee Bay, aerial gunnery ranges, Air Armament Center, Eglin Air Force Base, Fla. (a) The danger zones—(1) Aerial gunnery range in west part of Choctawhatchee...

  5. The feasibility of unmanned aerial vehicle-based acoustic atmospheric tomography.

    PubMed

    Finn, Anthony; Rogers, Kevin

    2015-08-01

    A technique for remotely monitoring the near-surface air temperature and wind fields up to altitudes of 1 km is presented and examined. The technique proposes the measurement of sound spectra emitted by the engine of a small unmanned aerial vehicle using sensors located on the aircraft and the ground. By relating projected and observed Doppler shifts in frequency and converting them into effective sound speed values, two- and three-dimensional spatially varying atmospheric temperature and wind velocity fields may be reconstructed using tomography. The feasibility and usefulness of the technique relative to existing unmanned aerial vehicle-based meteorological techniques using simulation and trials is examined.

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

    NASA Astrophysics Data System (ADS)

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

    1996-11-01

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

  7. 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.

  8. Spatial-Temporal Detection of Changes on the Southern Coast of the Baltic Sea Based on Multitemporal Aerial Photographs

    NASA Astrophysics Data System (ADS)

    Michalowska, K.; Glowienka, E.; Pekala, A.

    2016-06-01

    Digital photogrammetry and remote sensing solutions applied under the project and combined with the geographical information system made it possible to utilize data originating from various sources and dating back to different periods. Research works made use of archival and up-to-date aerial images, satellite images, orthophotomaps. Multitemporal data served for mapping and monitoring intermediate conditions of the Baltic Sea shore zone without a need for a direct interference in the environment. The main objective of research was to determine the dynamics and volume of sea shore changes along the selected part of coast in the period of 1951-2004, and to assess the tendencies of shore development in that area. For each of the six annual data sets, the following were determined: front dune base line, water line and the beach width. The location of the dune base line, which reflects the course of the shoreline in a given year was reconstructed based on stereoscopic study of images from each annual set. Unidirectional changes in the period of 1951-2004 occurred only within 10% of the examined shore section length. The examined shore is marked by a high and considerable dynamics of changes. Almost half of the shore, in particular the middle coast shows big changes, in excess of 2 m/year. The limits of shoreline changes ranged from 120 to -90 m, and their velocity from 0 to 11 m/year, save that the middle and west parts of the examined coast section were subjected to definitely more intense shore transformations. Research based on the analysis of multitemporal aerial images made it possible to reconstruct the intermediate conditions of the Baltic Sea shoreline and determine the volume and rate of changes in the location of dune base line in the examined period of 53 years, and to find out tendencies of shore development and dynamics.

  9. Vision-based fast navigation of micro aerial vehicles

    NASA Astrophysics Data System (ADS)

    Loianno, Giuseppe; Kumar, Vijay

    2016-05-01

    We address the key challenges for autonomous fast flight for Micro Aerial Vehicles (MAVs) in 3-D, cluttered environments. For complete autonomy, the system must identify the vehicle's state at high rates, using either absolute or relative asynchronous on-board sensor measurements, use these state estimates for feedback control, and plan trajectories to the destination. State estimation requires information from different sensors to be fused, exploiting information from different, possible asynchronous sensors at different rates. In this work, we present techniques in the area of planning, control and visual-inertial state estimation for fast navigation of MAVs. We demonstrate how to solve on-board, on a small computational unit, the pose estimation, control and planning problems for MAVs, using a minimal sensor suite for autonomous navigation composed of a single camera and IMU. Additionally, we show that a consumer electronic device such as a smartphone can alternatively be employed for both sensing and computation. Experimental results validate the proposed techniques. Any consumer, provided with a smartphone, can autonomously drive a quadrotor platform at high speed, without GPS, and concurrently build 3-D maps, using a suitably designed app.

  10. 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.

  11. Multicopter-based small format aerial photography using free and open source photogrammetry

    NASA Astrophysics Data System (ADS)

    Davis, Robert Matthew

    A process is described to convert aerial photographs from flat images to 3D point clouds and then convert into height maps to be used as pseudo digital elevation models for surface modeling. All software used in the process is either free or open source. The process uses a DJI Phanton multicoper and two Canon Point and Shoot digital cameras. One camera is unaltered, and a second camera is modified to produce infrared images. A DJI Phantom FC-40 multicopter is used as the aerial platform to carry the cameras. Multiple paths are described to convert from still images (or video to still images) to N-view matches, followed by sparse point clouds then dense point clouds. Point clouds are distinct 3D points charted in an XYZ coordinate system. The dense point clouds can be converted into 3D models for viewing and analysis. A height map is extracted from the point cloud and surface images (in raster format) are created and then used in QGIS or ArcMap as pseudo digital elevation models for surface modeling. Finally, the digital elevation models are evaluated in comparison to similar LIDAR images. Keywords: Passive Remote Sensing; LIDAR; Spatial Resolution.

  12. 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

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

    NASA Astrophysics Data System (ADS)

    Yahyanejad, Saeed; Rinner, Bernhard

    2015-06-01

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

  14. Fusion of LiDAR and aerial imagery for the estimation of downed tree volume using Support Vector Machines classification and region based object fitting

    NASA Astrophysics Data System (ADS)

    Selvarajan, Sowmya

    downed tree classification with fused LiDAR and aerial image. The classified tree pixels are utilized in the object based region fitting technique to compute the diameter and height of the downed trees and the volume of the trees are estimated. (Full text of this dissertation may be available via the University of Florida Libraries web site. Please check http://www.uflib.ufl.edu/etd.html)

  15. Defocus compensation system of long focal aerial camera based on auto-collimation

    NASA Astrophysics Data System (ADS)

    Zhang, Yu-ye; Zhao, Yu-liang; Xu, Zhao-lin

    2010-10-01

    Nowadays, novel aerial reconnaissance camera emphasizes on the shooting performance in high altitude or in long distance of oblique photography. In order to obtain the larger scale pictures which are easier for image interpretation, we need the camera has long focal length. But long focal length camera is easier to be influenced by environmental condition and lead to great change of lens' back focus which can result in the lens' resolution decreased greatly. So, we should do precise defocusing compensation to long focal aerial camera system. In order to realize defocusing compensation, a defocusing compensation system based on autocollimation is designed. Firstly, the reason which can lead to long focal camera's defocusing was discussed, then the factors such as changes of atmospheric pressure and temperature and oblique photographic distance were pointed out, and mathematical equation which could compute camera's defocusing amount was presented. Secondly, after camera's defocusing was analyzed, electro-optical autocollimation of higher automation and intelligent was adopted in the system. Before shooting , focal surface was located by electro-optical autocollimation focal detection mechanism, the data of airplane's height was imported through electronic control system. Defocusing amount was corrected by computing defocusing amount and the signal was send to focusing control motor. And an efficient improved mountain climb-searching algorithm was adopted for focal surface locating in the correction process. When confirming the direction of curve, the improved algorithm considered both twice focusing results and four points. If four points continue raised, the curve would be confirmed as rising direction. On the other hand, if four points continue decreased, the curve would be confirmed as decrease direction. In this way, we could avoid the local peak value appeared in two focusing steps. The defocusing compensation system consists of optical component and precise

  16. 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.

  17. Wavelet-based detection of bush encroachment in a savanna using multi-temporal aerial photographs and satellite imagery

    NASA Astrophysics Data System (ADS)

    Shekede, Munyaradzi D.; Murwira, Amon; Masocha, Mhosisi

    2015-03-01

    Although increased woody plant abundance has been reported in tropical savannas worldwide, techniques for detecting the direction and magnitude of change are mostly based on visual interpretation of historical aerial photography or textural analysis of multi-temporal satellite images. These techniques are prone to human error and do not permit integration of remotely sensed data from diverse sources. Here, we integrate aerial photographs with high spatial resolution satellite imagery and use a discrete wavelet transform to objectively detect the dynamics in bush encroachment at two protected Zimbabwean savanna sites. Based on the recently introduced intensity-dominant scale approach, we test the hypotheses that: (1) the encroachment of woody patches into the surrounding grassland matrix causes a shift in the dominant scale. This shift in the dominant scale can be detected using a discrete wavelet transform regardless of whether aerial photography and satellite data are used; and (2) as the woody patch size stabilises, woody cover tends to increase thereby triggering changes in intensity. The results show that at the first site where tree patches were already established (Lake Chivero Game Reserve), between 1972 and 1984 the dominant scale of woody patches initially increased from 8 m before stabilising at 16 m and 32 m between 1984 and 2012 while the intensity fluctuated during the same period. In contrast, at the second site, which was formely grass-dominated site (Kyle Game Reserve), we observed an unclear dominant scale (1972) which later becomes distinct in 1985, 1996 and 2012. Over the same period, the intensity increased. Our results imply that using our approach we can detect and quantify woody/bush patch dynamics in savanna landscapes.

  18. 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).

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Yi, Wenbin; Tang, Hong

    2009-10-01

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

  1. 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

  2. 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.

  3. Onboard and Parts-based Object Detection from Aerial Imagery

    DTIC Science & Technology

    2011-09-01

    reduced operator workload. Additionally, a novel parts- based detection method was developed. A whole-object detector is not well suited for deformable and...reduced operator workload. Additionally, a novel parts- based detection method was developed. A whole-object detector is not well suited for deformable and...Methodology This chapter details the challenges of transitioning from ground station processing to onboard processing, the part- based detection method

  4. Automatic vehicle detection based on automatic histogram-based fuzzy C-means algorithm and perceptual grouping using very high-resolution aerial imagery and road vector data

    NASA Astrophysics Data System (ADS)

    Ghaffarian, Saman; Gökaşar, Ilgın

    2016-01-01

    This study presents an approach for the automatic detection of vehicles using very high-resolution images and road vector data. Initially, road vector data and aerial images are integrated to extract road regions. Then, the extracted road/street region is clustered using an automatic histogram-based fuzzy C-means algorithm, and edge pixels are detected using the Canny edge detector. In order to automatically detect vehicles, we developed a local perceptual grouping approach based on fusion of edge detection and clustering outputs. To provide the locality, an ellipse is generated using characteristics of the candidate clusters individually. Then, ratio of edge pixels to nonedge pixels in the corresponding ellipse is computed to distinguish the vehicles. Finally, a point-merging rule is conducted to merge the points that satisfy a predefined threshold and are supposed to denote the same vehicles. The experimental validation of the proposed method was carried out on six very high-resolution aerial images that illustrate two highways, two shadowed roads, a crowded narrow street, and a street in a dense urban area with crowded parked vehicles. The evaluation of the results shows that our proposed method performed 86% and 83% in overall correctness and completeness, respectively.

  5. Vision-Based Corrosion Detection Assisted by a Micro-Aerial Vehicle in a Vessel Inspection Application

    PubMed Central

    Ortiz, Alberto; Bonnin-Pascual, Francisco; Garcia-Fidalgo, Emilio; Company-Corcoles, Joan P.

    2016-01-01

    Vessel maintenance requires periodic visual inspection of the hull in order to detect typical defective situations of steel structures such as, among others, coating breakdown and corrosion. These inspections are typically performed by well-trained surveyors at great cost because of the need for providing access means (e.g., scaffolding and/or cherry pickers) that allow the inspector to be at arm’s reach from the structure under inspection. This paper describes a defect detection approach comprising a micro-aerial vehicle which is used to collect images from the surfaces under inspection, particularly focusing on remote areas where the surveyor has no visual access, and a coating breakdown/corrosion detector based on a three-layer feed-forward artificial neural network. As it is discussed in the paper, the success of the inspection process depends not only on the defect detection software but also on a number of assistance functions provided by the control architecture of the aerial platform, whose aim is to improve picture quality. Both aspects of the work are described along the different sections of the paper, as well as the classification performance attained. PMID:27983627

  6. Vision-Based Corrosion Detection Assisted by a Micro-Aerial Vehicle in a Vessel Inspection Application.

    PubMed

    Ortiz, Alberto; Bonnin-Pascual, Francisco; Garcia-Fidalgo, Emilio; Company-Corcoles, Joan P

    2016-12-14

    Vessel maintenance requires periodic visual inspection of the hull in order to detect typical defective situations of steel structures such as, among others, coating breakdown and corrosion. These inspections are typically performed by well-trained surveyors at great cost because of the need for providing access means (e.g., scaffolding and/or cherry pickers) that allow the inspector to be at arm's reach from the structure under inspection. This paper describes a defect detection approach comprising a micro-aerial vehicle which is used to collect images from the surfaces under inspection, particularly focusing on remote areas where the surveyor has no visual access, and a coating breakdown/corrosion detector based on a three-layer feed-forward artificial neural network. As it is discussed in the paper, the success of the inspection process depends not only on the defect detection software but also on a number of assistance functions provided by the control architecture of the aerial platform, whose aim is to improve picture quality. Both aspects of the work are described along the different sections of the paper, as well as the classification performance attained.

  7. Estimation of carbon storage based on individual tree detection in Pinus densiflora stands using a fusion of aerial photography and LiDAR data.

    PubMed

    Kim, So-Ra; Kwak, Doo-Ahn; Lee, Woo-Kyun; oLee, Woo-Kyun; Son, Yowhan; Bae, Sang-Won; Kim, Choonsig; Yoo, Seongjin

    2010-07-01

    The objective of this study was to estimate the carbon storage capacity of Pinus densiflora stands using remotely sensed data by combining digital aerial photography with light detection and ranging (LiDAR) data. A digital canopy model (DCM), generated from the LiDAR data, was combined with aerial photography for segmenting crowns of individual trees. To eliminate errors in over and under-segmentation, the combined image was smoothed using a Gaussian filtering method. The processed image was then segmented into individual trees using a marker-controlled watershed segmentation method. After measuring the crown area from the segmented individual trees, the individual tree diameter at breast height (DBH) was estimated using a regression function developed from the relationship observed between the field-measured DBH and crown area. The above ground biomass of individual trees could be calculated by an image-derived DBH using a regression function developed by the Korea Forest Research Institute. The carbon storage, based on individual trees, was estimated by simple multiplication using the carbon conversion index (0.5), as suggested in guidelines from the Intergovernmental Panel on Climate Change. The mean carbon storage per individual tree was estimated and then compared with the field-measured value. This study suggested that the biomass and carbon storage in a large forest area can be effectively estimated using aerial photographs and LiDAR data.

  8. Aerial Surveying Uav Based on Open-Source Hardware and Software

    NASA Astrophysics Data System (ADS)

    Mészáros, J.

    2011-09-01

    In the last years the functionality and type of UAV-systems increased fast, but unfortunately these systems are hardly available for researchers in some cases. A simple and low-cost solution was developed to build an autonomous aerial surveying airplane, which can fulfil the necessities (aerial photographs with very-high resolution) of other departments at the university and very useful and practical for teaching photogrammetry.. The base was a commercial, remote controlled model airplane and an open-source GPS/IMU system (MatrixPilot) was adapted to achieve the semi-automatic or automatic stabilization and navigation of the model airplane along predefined trajectory. The firmware is completely open-source and easily available on the website of the project. The first used camera system was a low-budget, low-quality video camera, which could provide only 1.2 megapixel photographs or low resolution video depending on the light conditions and the desired spatial resolution. A field measurement test was carried out with the described system: the aerial surveying of an undiscovered archaeological site, signed by a crop-mark in mountain Pilis (Hungary).

  9. Image analysis techniques associated with automatic data base generation.

    NASA Technical Reports Server (NTRS)

    Bond, A. D.; Ramapriyan, H. K.; Atkinson, R. J.; Hodges, B. C.; Thomas, D. T.

    1973-01-01

    This paper considers some basic problems relating to automatic data base generation from imagery, the primary emphasis being on fast and efficient automatic extraction of relevant pictorial information. Among the techniques discussed are recursive implementations of some particular types of filters which are much faster than FFT implementations, a 'sequential similarity detection' technique of implementing matched filters, and sequential linear classification of multispectral imagery. Several applications of the above techniques are presented including enhancement of underwater, aerial and radiographic imagery, detection and reconstruction of particular types of features in images, automatic picture registration and classification of multiband aerial photographs to generate thematic land use maps.

  10. 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

  11. Combined aerial and ground technique for assessing structural heat loss

    NASA Astrophysics Data System (ADS)

    Snyder, William C.; Schott, John R.

    1994-03-01

    The results of a combined aerial and ground-based structural heat loss survey are presented. The aerial imagery was collected by a thermal IR line scanner. Enhanced quantitative analysis of the imagery gives the roof heat flow and insulation level. The ground images were collected by a video van and converted to still frames stored on a video disk. A computer based presentation system retrieves the images and other information indexed by street address for screening and dissemination to owners. We conclude that the combined aerial and ground survey effectively discriminates between well insulated and poorly insulated structures, and that such a survey is a cost-effective alternative to site audits.

  12. 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...

  13. 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.

  14. Active-imaging-based underwater navigation

    NASA Astrophysics Data System (ADS)

    Monnin, David; Schmitt, Gwenaël.; Fischer, Colin; Laurenzis, Martin; Christnacher, Frank

    2015-10-01

    Global navigation satellite systems (GNSS) are widely used for the localization and the navigation of unmanned and remotely operated vehicles (ROV). In contrast to ground or aerial vehicles, GNSS cannot be employed for autonomous underwater vehicles (AUV) without the use of a communication link to the water surface, since satellite signals cannot be received underwater. However, underwater autonomous navigation is still possible using self-localization methods which determines the relative location of an AUV with respect to a reference location using inertial measurement units (IMU), depth sensors and even sometimes radar or sonar imaging. As an alternative or a complementary solution to common underwater reckoning techniques, we present the first results of a feasibility study of an active-imaging-based localization method which uses a range-gated active-imaging system and can yield radiometric and odometric information even in turbid water.

  15. Ground-based spectral reflectance measurements for efficacy evaluation of aerially applied glyphosate treatments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aerial application of herbicides is a common tool in agricultural field management. The objective of this study was to evaluate the efficacy of glyphosate herbicide applied aerially with both conventional and emerging aerial nozzle technologies. A Texas A&M University Plantation weed field was set u...

  16. Ground-based spectral reflectance measurements for evaluating the efficacy of aerially-applied glyphosate treatments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aerial application of herbicides is a common tool in agricultural field management. The objective of this study was to evaluate the efficacy of glyphosate herbicide applied aerially with both conventional and emerging aerial nozzle technologies. A Texas A&M University Plantation weed field was set...

  17. Flatness-Based Tracking Control and Nonlinear Observer for a Micro Aerial Quadcopter

    NASA Astrophysics Data System (ADS)

    Rivera, G.; Sawodny, O.

    2010-09-01

    This paper deals with the design of a nonlinear observer and a differential flat based path tracking controller for a mini aerial quadcopter. Taking into account that only the inertial coordinates and the yaw angle are available for measurements, it is shown, that the system is differentially flat, allowing a systematic design of a nonlinear tracking control in open and closed loop. A nonlinear observer is carried out to estimate the roll and pitch angle as well as all the linear and angular velocities. Finally the performance of the feedback controller and observer are illustrated in a computer simulation.

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

    NASA Astrophysics Data System (ADS)

    Tanathong, Supannee; Lee, Impyeong

    2014-11-01

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

  19. Aerial Prefeeding Followed by Ground Based Toxic Baiting for More Efficient and Acceptable Poisoning of Invasive Small Mammalian Pests

    PubMed Central

    Morgan, David; Warburton, Bruce; Nugent, Graham

    2015-01-01

    Introduced brushtail possums (Trichosurus vulpecula) and rat species (Rattus spp.) are major vertebrate pests in New Zealand, with impacts on conservation and agriculture being managed largely through poisoning operations. Aerial distribution of baits containing sodium fluoroacetate (1080) has been refined to maximise cost effectiveness and minimise environmental impact, but this method is strongly opposed by some as it is perceived as being indiscriminate. Although ground based control enables precise placement of baits, operations are often more than twice as costly as aerial control, mainly due to the high labour costs. We investigated a new approach to ground based control that combined aerial distribution of non-toxic ‘prefeed’ baits followed by sparse distribution of toxic baits at regular intervals along the GPS tracked prefeeding flight paths. This approach was tested in two field trials in which both 1080 baits and cholecalciferol baits were used in separate areas. Effectiveness of the approach, assessed primarily using ‘chewcards’, was compared with that of scheduled aerial 1080 operations that were conducted in outlying areas of both trials. Contractors carrying out ground based control were able to follow the GPS tracks of aerial prefeeding flight lines very accurately, and with 1080 baits achieved very high levels of kill of possums and rats similar to those achieved by aerial 1080 baiting. Cholecalciferol was less effective in the first trial, but by doubling the amount of cholecalciferol bait used in the second trial, few possums or rats survived. By measuring the time taken to complete ground baiting from GPS tracks, we predicted that the method (using 1080 baits) would be similarly cost effective to aerial 1080 operations for controlling possums and rats, and considerably less expensive than typical current costs of ground based control. The main limitations to the use of the method will be access to, and size of, the operational site

  20. Aerial Prefeeding Followed by Ground Based Toxic Baiting for More Efficient and Acceptable Poisoning of Invasive Small Mammalian Pests.

    PubMed

    Morgan, David; Warburton, Bruce; Nugent, Graham

    2015-01-01

    Introduced brushtail possums (Trichosurus vulpecula) and rat species (Rattus spp.) are major vertebrate pests in New Zealand, with impacts on conservation and agriculture being managed largely through poisoning operations. Aerial distribution of baits containing sodium fluoroacetate (1080) has been refined to maximise cost effectiveness and minimise environmental impact, but this method is strongly opposed by some as it is perceived as being indiscriminate. Although ground based control enables precise placement of baits, operations are often more than twice as costly as aerial control, mainly due to the high labour costs. We investigated a new approach to ground based control that combined aerial distribution of non-toxic 'prefeed' baits followed by sparse distribution of toxic baits at regular intervals along the GPS tracked prefeeding flight paths. This approach was tested in two field trials in which both 1080 baits and cholecalciferol baits were used in separate areas. Effectiveness of the approach, assessed primarily using 'chewcards', was compared with that of scheduled aerial 1080 operations that were conducted in outlying areas of both trials. Contractors carrying out ground based control were able to follow the GPS tracks of aerial prefeeding flight lines very accurately, and with 1080 baits achieved very high levels of kill of possums and rats similar to those achieved by aerial 1080 baiting. Cholecalciferol was less effective in the first trial, but by doubling the amount of cholecalciferol bait used in the second trial, few possums or rats survived. By measuring the time taken to complete ground baiting from GPS tracks, we predicted that the method (using 1080 baits) would be similarly cost effective to aerial 1080 operations for controlling possums and rats, and considerably less expensive than typical current costs of ground based control. The main limitations to the use of the method will be access to, and size of, the operational site, along with

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

    NASA Astrophysics Data System (ADS)

    Henrique Castelo Branco, Luiz; César Lima Segantine, Paulo

    2015-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2003-07-01

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

  3. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  5. AKSED: adaptive knowledge-based system for event detection using collaborative unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Wang, X. Sean; Lee, Byung Suk; Sadjadi, Firooz

    2006-05-01

    Advances in sensor technology and image processing have made it possible to equip unmanned aerial vehicles (UAVs) with economical, high-resolution, energy-efficient sensors. Despite the improvements, current UAVs lack autonomous and collaborative operation capabilities, due to limited bandwidth and limited on-board image processing abilities. The situation, however, is changing. In the next generation of UAVs, much image processing can be carried out onboard and communication bandwidth problem will improve. More importantly, with more processing power, collaborative operations among a team of autonomous UAVs can provide more intelligent event detection capabilities. In this paper, we present ideas for developing a system enabling target recognitions by collaborative operations of autonomous UAVs. UAVs are configured in three stages: manufacturing, mission planning, and deployment. Different sets of information are needed at different stages, and the resulting outcome is an optimized event detection code deployed onto a UAV. The envisioned system architecture and the contemplated methodology, together with problems to be addressed, are presented.

  6. Random Forest and Objected-Based Classification for Forest Pest Extraction from Uav Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Yuan, Yi; Hu, Xiangyun

    2016-06-01

    Forest pest is one of the most important factors affecting the health of forest. However, since it is difficult to figure out the pest areas and to predict the spreading ways just to partially control and exterminate it has not effective enough so far now. The infected areas by it have continuously spreaded out at present. Thus the introduction of spatial information technology is highly demanded. It is very effective to examine the spatial distribution characteristics that can establish timely proper strategies for control against pests by periodically figuring out the infected situations as soon as possible and by predicting the spreading ways of the infection. Now, with the UAV photography being more and more popular, it has become much cheaper and faster to get UAV images which are very suitable to be used to monitor the health of forest and detect the pest. This paper proposals a new method to effective detect forest pest in UAV aerial imagery. For an image, we segment it to many superpixels at first and then we calculate a 12-dimension statistical texture information for each superpixel which are used to train and classify the data. At last, we refine the classification results by some simple rules. The experiments show that the method is effective for the extraction of forest pest areas in UAV images.

  7. Aerial surveillance based on hierarchical object classification for ground target detection

    NASA Astrophysics Data System (ADS)

    Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

    2015-03-01

    Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

  8. 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.

  9. 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

  10. 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.

  11. Aerial Explorers

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  12. New interpretations of the Fort Clark State Historic Site based on aerial color and thermal infrared imagery

    NASA Astrophysics Data System (ADS)

    Heller, Andrew Roland

    The Fort Clark State Historic Site (32ME2) is a well known site on the upper Missouri River, North Dakota. The site was the location of two Euroamerican trading posts and a large Mandan-Arikara earthlodge village. In 2004, Dr. Kenneth L. Kvamme and Dr. Tommy Hailey surveyed the site using aerial color and thermal infrared imagery collected from a powered parachute. Individual images were stitched together into large image mosaics and registered to Wood's 1993 interpretive map of the site using Adobe Photoshop. The analysis of those image mosaics resulted in the identification of more than 1,500 archaeological features, including as many as 124 earthlodges.

  13. Towards an Autonomous Vision-Based Unmanned Aerial System against Wildlife Poachers

    PubMed Central

    Olivares-Mendez, Miguel A.; Fu, Changhong; Ludivig, Philippe; Bissyandé, Tegawendé F.; Kannan, Somasundar; Zurad, Maciej; Annaiyan, Arun; Voos, Holger; Campoy, Pascual

    2015-01-01

    Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing. PMID:26703597

  14. Accurate group velocity estimation for unmanned aerial vehicle-based acoustic atmospheric tomography.

    PubMed

    Rogers, Kevin J; Finn, Anthony

    2017-02-01

    Acoustic atmospheric tomography calculates temperature and wind velocity fields in a slice or volume of atmosphere based on travel time estimates between strategically located sources and receivers. The technique discussed in this paper uses the natural acoustic signature of an unmanned aerial vehicle as it overflies an array of microphones on the ground. The sound emitted by the aircraft is recorded on-board and by the ground microphones. The group velocities of the intersecting sound rays are then derived by comparing these measurements. Tomographic inversion is used to estimate the temperature and wind fields from the group velocity measurements. This paper describes a technique for deriving travel time (and hence group velocity) with an accuracy of 0.1% using these assets. This is shown to be sufficient to obtain highly plausible tomographic inversion results that correlate well with independent SODAR measurements.

  15. Towards an Autonomous Vision-Based Unmanned Aerial System against Wildlife Poachers.

    PubMed

    Olivares-Mendez, Miguel A; Fu, Changhong; Ludivig, Philippe; Bissyandé, Tegawendé F; Kannan, Somasundar; Zurad, Maciej; Annaiyan, Arun; Voos, Holger; Campoy, Pascual

    2015-12-12

    Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $ 213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing.

  16. Airdata sensor based position estimation and fault diagnosis in aerial refueling

    NASA Astrophysics Data System (ADS)

    Sevil, Hakki Erhan

    Aerial refueling is the process of transferring fuel from one aircraft (the tanker) to another (the receiver) during flight. In aerial refueling operations, the receiver aircraft is exposed to nonuniform wind field induced by tanker aircraft, and this nonuniform wind field leads to differences in readings of airdata sensors placed at different locations on the receiver aircraft. There are advantages and disadvantages of this phenomenon. As an advantage, it is used as a mechanism to estimate relative position of the receiver aircraft inside the nonuniform wind field behind the tanker. Using the difference in the measurements from multiple identical sensors, a model of the nonuniform wind field that is organized as maps of the airspeed, side slip angle and angle of attack as functions of the relative position is prepared. Then, using the developed algorithms, preformed maps and instant sensor readings, the relative position receiver aircraft is determined. The disadvantage of the phenomenon is that the differences in readings of airdata sensors cause false fault detections in a redundant-sensor-based Fault Detection and Isolation (FDI) system developed based on the assumption of identical sensor readings from three airdata sensors. Such FDI algorithm successfully performs detection and isolation of sensor faults when the receiver aircraft flies solo or outside the wake of the tanker aircraft. However, the FDI algorithm yields false fault detection when the receiver aircraft enters the tanker's wake. This problem can be eliminated by modifying the FDI algorithm. For the robustness, the expected values of the sensor measurements are incorporated in the FDI algorithm, instead of the assumption of identical measurements from the sensors. The expected values, which depend on the position of the receiver relative to the tanker, are obtained from the maps of the nonuniform wind field as functions of the relative position. The new robust FDI detects and isolates sensor

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

    DTIC Science & Technology

    2011-01-01

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

  18. Development of an unmanned aerial vehicle-based remote sensing system for site-specific management in precision agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An Unmanned Aerial Vehicle (UAV) can be remotely controlled or fly autonomously based on pre-programmed flight plans or more complex dynamic automation systems. In agriculture, UAVs have been used for pest control and remote sensing. The objective of this research was to develop a UAV system to en...

  19. Monitoring surface geothermal features using time series of aerial and ground-based photographs

    NASA Astrophysics Data System (ADS)

    Bromley, C.; van Manen, S. M.; Graham, D.

    2010-12-01

    Geothermal systems are of high conservation and scientific value and monitoring of these is an important management tool to assess natural variations and changes resulting from development and utilization. This study examines time series of aerial and ground-based photographs of geothermal areas within the Taupo Volcanic Zone, New Zealand. A time series of aerial photographs from 1946-2007 of the Broadlands Road Scenic Reserve (Taupo, New Zealand) highlights large changes to this small area as the result of the start of geothermal fluid production for the nearby Wairakei power plant in 1958 and other causes. Prior to the opening of the plant the area was not geothermally active, but expansion of steam zones due to pressure drawdown has resulted in significant thermal changes in the subsurface. These subsurface thermal changes are evident in the aerial photographs as the appearance of hydrothermal eruption craters and areas of thermal bare ground, which are too hot for vegetation to grown on. In addition, in the late 1960’s thermotolerant vegetation started to establish itself in the adjacent area. Changes in the surface area covered by each of these, reflect changes in the geothermal system as well as changes in management (e.g. exclusion of livestock), and a time series of these changes has been produced using ArcMap™. Monthly photographs of surface geothermal expressions in the Rotorua area show changes in colour and size of chloride springs with time. Colour and size changes are difficult to quantify due to varying exposure settings, weather conditions, and vantage points. However, these qualitative descriptions can be combined with quantitative time series such as temperature measurements, to provide better insight into surface changes that have occurred at this geothermal field. This study highlights the value of both qualitative and quantitative data that can be obtained from time series of photographs, including photographs that were obtained before the

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  1. 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

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

    PubMed

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

    2016-12-14

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

  3. 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.

  4. 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…

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  6. Classification of Urban Aerial Data Based on Pixel Labelling with Deep Convolutional Neural Networks and Logistic Regression

    NASA Astrophysics Data System (ADS)

    Yao, W.; Poleswki, P.; Krzystek, P.

    2016-06-01

    The recent success of deep convolutional neural networks (CNN) on a large number of applications can be attributed to large amounts of available training data and increasing computing power. In this paper, a semantic pixel labelling scheme for urban areas using multi-resolution CNN and hand-crafted spatial-spectral features of airborne remotely sensed data is presented. Both CNN and hand-crafted features are applied to image/DSM patches to produce per-pixel class probabilities with a L1-norm regularized logistical regression classifier. The evidence theory infers a degree of belief for pixel labelling from different sources to smooth regions by handling the conflicts present in the both classifiers while reducing the uncertainty. The aerial data used in this study were provided by ISPRS as benchmark datasets for 2D semantic labelling tasks in urban areas, which consists of two data sources from LiDAR and color infrared camera. The test sites are parts of a city in Germany which is assumed to consist of typical object classes including impervious surfaces, trees, buildings, low vegetation, vehicles and clutter. The evaluation is based on the computation of pixel-based confusion matrices by random sampling. The performance of the strategy with respect to scene characteristics and method combination strategies is analyzed and discussed. The competitive classification accuracy could be not only explained by the nature of input data sources: e.g. the above-ground height of nDSM highlight the vertical dimension of houses, trees even cars and the nearinfrared spectrum indicates vegetation, but also attributed to decision-level fusion of CNN's texture-based approach with multichannel spatial-spectral hand-crafted features based on the evidence combination theory.

  7. Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object-based classification approaches.

    PubMed

    Meneguzzo, Dacia M; Liknes, Greg C; Nelson, Mark D

    2013-08-01

    Discrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics. Despite the significance of ToF, forest and other natural resource inventory programs and geospatial land cover datasets that are available at a national scale do not include comprehensive information regarding ToF in the United States. Additional ground-based data collection and acquisition of specialized imagery to inventory these resources are expensive alternatives. As a potential solution, we identified two remote sensing-based approaches that use free high-resolution aerial imagery from the National Agriculture Imagery Program (NAIP) to map all tree cover in an agriculturally dominant landscape. We compared the results obtained using an unsupervised per-pixel classifier (independent component analysis-[ICA]) and an object-based image analysis (OBIA) procedure in Steele County, Minnesota, USA. Three types of accuracy assessments were used to evaluate how each method performed in terms of: (1) producing a county-level estimate of total tree-covered area, (2) correctly locating tree cover on the ground, and (3) how tree cover patch metrics computed from the classified outputs compared to those delineated by a human photo interpreter. Both approaches were found to be viable for mapping tree cover over a broad spatial extent and could serve to supplement ground-based inventory data. The ICA approach produced an estimate of total tree cover more similar to the photo-interpreted result, but the output from the OBIA method was more realistic in terms of describing the actual observed spatial pattern of tree cover.

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

    DTIC Science & Technology

    2015-11-04

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

  9. Hierarchical flight control system synthesis for rotorcraft-based unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Shim, Hyunchul

    The Berkeley Unmanned Aerial Vehicle (UAV) research aims to design, implement, and analyze a group of autonomous intelligent UAVs and UGVs (Unmanned Ground Vehicles). The goal of this dissertation is to provide a comprehensive procedural methodology to design, implement, and test rotorcraft-based unmanned aerial vehicles (RUAVs). We choose the rotorcraft as the base platform for our aerial agents because it offers ideal maneuverability for our target scenarios such as the pursuit-evasion game. Aided by many enabling technologies such as lightweight and powerful computers, high-accuracy navigation sensors and communication devices, it is now possible to construct RUAVs capable of precise navigation and intelligent behavior by the decentralized onboard control system. Building a fully functioning RUAV requires a deep understanding of aeronautics, control theory and computer science as well as a tremendous effort for implementation. These two aspects are often inseparable and therefore equally highlighted throughout this research. The problem of multiple vehicle coordination is approached through the notion of a hierarchical system. The idea behind the proposed architecture is to build a hierarchical multiple-layer system that gradually decomposes the abstract mission objectives into the physical quantities of control input. Each RUAV incorporated into this system performs the given tasks and reports the results through the hierarchical communication channel back to the higher-level coordinator. In our research, we provide a theoretical and practical approach to build a number of RUAVs based on commercially available navigation sensors, computer systems, and radio-controlled helicopters. For the controller design, the dynamic model of the helicopter is first built. The helicopter exhibits a very complicated multi-input multi-output, nonlinear, time-varying and coupled dynamics, which is exposed to severe exogenous disturbances. This poses considerable difficulties for

  10. Portable ammonia-borane-based H2 power-pack for unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Seo, Jung-Eun; Kim, Yujong; Kim, Yongmin; Kim, Kibeom; Lee, Jin Hee; Lee, Dae Hyung; Kim, Yeongcheon; Shin, Seock Jae; Kim, Dong-Min; Kim, Sung-Yug; Kim, Taegyu; Yoon, Chang Won; Nam, Suk Woo

    2014-05-01

    An advanced ammonia borane (AB)-based H2 power-pack is designed to continually drive an unmanned aerial vehicle (UAV) for 57 min using a 200-We polymer electrolyte membrane fuel cell (PEMFC). In a flight test with the UAV platform integrated with the developed power-pack, pure hydrogen with an average flow rate of 3.8 L(H2) min-1 is generated by autothermal H2-release from AB with tetraethylene glycol dimethylether (T4EGDE) as a promoter. During take-off, a hybridized power management system (PMS) consisting of the fuel cell and an auxiliary lithium-ion battery supplies 500 We at full power simultaneously, while the fuel cell alone provides 150-200 We and further recharges the auxiliary battery upon cruising. Gaseous byproducts identified by in situ Fourier transform infrared (FT-IR) spectroscopy during AB dehydrogenation are sequestrated using a mixed absorbent in an H2 purification system. In addition, a real-time monitoring system is employed to determine the remaining filter capacity of the purifier at a ground control system for rapidly responding unpredictable circumstances during flight. Separate experiments are conducted to screen potential materials and methods for enhancing filter capacity in the current H2 refining system. A prospective reactor concept for long-term fuel cell applications is proposed based on the results.

  11. Quaternion-based nonlinear trajectory tracking control of a quadrotor unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Zha, Changliu; Ding, Xilun; Yu, Yushu; Wang, Xueqiang

    2017-01-01

    At present, most controllers of quadrotor unmanned aerial vehicles(UAVs) use Euler angles to express attitude. These controllers suffer a singularity problem when the pitch angle is near 90°C, which limits the maneuverability of the UAV. To overcome this problem, based on the quaternion attitude representation, a 6 degree of freedom(DOF) nonlinear controller of a quadrotor UAV is designed using the trajectory linearization control(TLC) method. The overall controller contains a position sub-controller and an attitude sub-controller. The two controllers regulate the translational and rotational motion of the UAV, respectively. The controller is improved by using the commanded value instead of the nominal value as the input of the inner control loop. The performance of controller is tested by simulation before and after the improvement, the results show that the improved controller is better. The proposed controller is also tested via numerical simulation and real flights and is compared with the traditional controller based on Euler angles. The test results confirm the feasibility and the robustness of the proposed nonlinear controller. The proposed controller can successfully solve the singularity problem that usually occurs in the current attitude control of UAV and it is easy to be realized.

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

    PubMed

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

    1964-11-06

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

  13. 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.

  14. Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring

    PubMed Central

    Trasviña-Moreno, Carlos A.; Blasco, Rubén; Marco, Álvaro; Casas, Roberto; Trasviña-Castro, Armando

    2017-01-01

    Marine environments are delicate ecosystems which directly influence local climates, flora, fauna, and human activities. Their monitorization plays a key role in their preservation, which is most commonly done through the use of environmental sensing buoy networks. These devices transmit data by means of satellite communications or close-range base stations, which present several limitations and elevated infrastructure costs. Unmanned Aerial Vehicles (UAV) are another alternative for remote environmental monitoring which provide new types of data and ease of use. These aircraft are mainly used in video capture related applications, in its various light spectrums, and do not provide the same data as sensing buoys, nor can they be used for such extended periods of time. The aim of this research is to provide a flexible, easy to deploy and cost-effective Wireless Sensor Network (WSN) for monitoring marine environments. This proposal uses a UAV as a mobile data collector, low-power long-range communications and sensing buoys as part of a single WSN. A complete description of the design, development, and implementation of the various parts of this system is presented, as well as its validation in a real-world scenario. PMID:28245587

  15. Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring.

    PubMed

    Trasviña-Moreno, Carlos A; Blasco, Rubén; Marco, Álvaro; Casas, Roberto; Trasviña-Castro, Armando

    2017-02-24

    Marine environments are delicate ecosystems which directly influence local climates, flora, fauna, and human activities. Their monitorization plays a key role in their preservation, which is most commonly done through the use of environmental sensing buoy networks. These devices transmit data by means of satellite communications or close-range base stations, which present several limitations and elevated infrastructure costs. Unmanned Aerial Vehicles (UAV) are another alternative for remote environmental monitoring which provide new types of data and ease of use. These aircraft are mainly used in video capture related applications, in its various light spectrums, and do not provide the same data as sensing buoys, nor can they be used for such extended periods of time. The aim of this research is to provide a flexible, easy to deploy and cost-effective Wireless Sensor Network (WSN) for monitoring marine environments. This proposal uses a UAV as a mobile data collector, low-power long-range communications and sensing buoys as part of a single WSN. A complete description of the design, development, and implementation of the various parts of this system is presented, as well as its validation in a real-world scenario.

  16. Waste site characterization through digital analysis of historical aerial photographs at Los Alamos National Laboratory and Eglin Air Force Base

    SciTech Connect

    Van Eeckhout, E.; Pope, P.; Wells, B.; Rofer, C.; Martin, B.

    1995-05-01

    Historical aerial photographs are used to provide a physical history and preliminary mapping information for characterizing hazardous waste sites at Los Alamos National Laboratory and Eglin Air Force Base. The examples cited show how imagery was used to accurately locate and identify previous activities at a site, monitor changes that occurred over time, and document the observable of such activities today. The methodology demonstrates how historical imagery (along with any other pertinent data) can be used in the characterization of past environmental damage.

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 2. AERIAL VIEW OF MINUTEMAN SILOS. Low oblique aerial view ...

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

    2. AERIAL VIEW OF MINUTEMAN SILOS. Low oblique aerial view (original in color) of the two launch silos, covered. - Edwards Air Force Base, Air Force Rocket Propulsion Laboratory, Missile Silo Type, Test Area 1-100, northeast end of Test Area 1-100 Road, Boron, Kern County, CA

  3. Rangeland resource assessment, monitoring, and management using unmanned aerial vehicle-based remote sensing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Civilian applications of Unmanned Aerial Vehicles (UAV) have rapidly been expanding recently. Thanks to military development many civil UAVs come via the defense sector. Although numerous UAVs can perform civilian tasks, the regulations imposed by FAA in the national airspace system and military e...

  4. Texture and scale in object-based analysis of subdecimeter resolution unmanned aerial vehicle (UAV) imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Imagery acquired with unmanned aerial vehicles (UAVs) has great potential for incorporation into natural resource monitoring protocols due to their ability to be deployed quickly and repeatedly and to fly at low altitudes. While the imagery may have high spatial resolution, the spectral resolution i...

  5. Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rangeland comprises as much as 70% of the Earth’s land surface area. Much of this vast space is in very remote areas that are expensive and often impossible to access on the ground. Unmanned Aerial Vehicles (UAVs) have great potential for rangeland management. UAVs have several advantages over satel...

  6. Acquisition, orthorectification, and object-based classification of unmanned aerial vehicle (UAV) imagery for rangeland monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this paper, we examine the potential of using a small unmanned aerial vehicle (UAV) for rangeland inventory, assessment and monitoring. Imagery with 8-cm resolution was acquired over 290 ha in southwestern Idaho. We developed a semi-automated orthorectification procedure suitable for handling lar...

  7. Efficient content-based low-altitude images correlated network and strips reconstruction

    NASA Astrophysics Data System (ADS)

    He, Haiqing; You, Qi; Chen, Xiaoyong

    2017-01-01

    The manual intervention method is widely used to reconstruct strips for further aerial triangulation in low-altitude photogrammetry. Clearly the method for fully automatic photogrammetric data processing is not an expected way. In this paper, we explore a content-based approach without manual intervention or external information for strips reconstruction. Feature descriptors in the local spatial patterns are extracted by SIFT to construct vocabulary tree, in which these features are encoded in terms of TF-IDF numerical statistical algorithm to generate new representation for each low-altitude image. Then images correlated network is reconstructed by similarity measure, image matching and geometric graph theory. Finally, strips are reconstructed automatically by tracing straight lines and growing adjacent images gradually. Experimental results show that the proposed approach is highly effective in automatically rearranging strips of lowaltitude images and can provide rough relative orientation for further aerial triangulation.

  8. 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.

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

    DTIC Science & Technology

    2013-01-01

    Handbook of Pattern Recognition and Computer Vision , Chen C, Paul L, Wang P (eds). World Scientific Publishing Co.: Singapore. Vericat D, Brassington J...The machine vision community has developed a number of powerful techniques based on the field of texture analysis (Tuceryan and Jain, 1998) that have... texture segmentation with nonparametric neighborhood statistics. Proceedings of the European Conference on Computer Vision (ECCV). Figure 11. Edge

  10. Feature selection methods for object-based classification of sub-decimeter resolution digital aerial imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Due to the availability of numerous spectral, spatial, and contextual features, the determination of optimal features and class separabilities can be a time consuming process in object-based image analysis (OBIA). While several feature selection methods have been developed to assist OBIA, a robust c...

  11. Spike Neuromorphic VLSI-Based Bat Echolocation for Micro-Aerial Vehicle Guidance

    DTIC Science & Technology

    2007-03-31

    wide dynamic range of image intensities. Most importantly, this project is intended to pave the way towards a new outlook on computation in neurally ...neurobiologically-realistic, conductance-based synaptic integration is better suited for the particular computations we are seeking. In collaborative work with...the effectiveness of conductance-based synaptic computation . The anatomy of the brainstem afferents to the lateral superior olive show the convergence

  12. Design and integration of vision based sensors for unmanned aerial vehicles navigation and guidance

    NASA Astrophysics Data System (ADS)

    Sabatini, Roberto; Bartel, Celia; Kaharkar, Anish; Shaid, Tesheen

    2012-04-01

    In this paper we present a novel Navigation and Guidance System (NGS) for Unmanned Aerial Vehicles (UAVs) based on Vision Based Navigation (VBN) and other avionics sensors. The main objective of our research is to design a lowcost and low-weight/volume NGS capable of providing the required level of performance in all flight phases of modern small- to medium-size UAVs, with a special focus on automated precision approach and landing, where VBN techniques can be fully exploited in a multisensory integrated architecture. Various existing techniques for VBN are compared and the Appearance-based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway and body rates. Additionally, we address the possible synergies between VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors and also the use of Aircraft Dynamics Models (ADMs) to provide additional information suitable to compensate for the shortcomings of VBN sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the platform in real-time. Two different integrated navigation system architectures are implemented. The first uses VBN at 20 Hz and GPS at 1 Hz to augment the MEMS-IMU running at 100 Hz. The second mode also includes the ADM (computations performed at 100 Hz) to provide augmentation of the attitude channel. Simulation of these two modes is performed in a significant portion of the Aerosonde UAV operational flight envelope and performing a variety of representative manoeuvres (i.e., straight climb, level turning, turning descent and climb, straight descent, etc.). Simulation of the first integrated navigation system architecture

  13. A new stratospheric sounding platform based on unmanned aerial vehicle (UAV) droppable from meteorological balloon

    NASA Astrophysics Data System (ADS)

    Efremov, Denis; Khaykin, Sergey; Lykov, Alexey; Berezhko, Yaroslav; Lunin, Aleksey

    High-resolution measurements of climate-relevant trace gases and aerosols in the upper troposphere and stratosphere (UTS) have been and remain technically challenging. The high cost of measurements onboard airborne platforms or heavy stratospheric balloons results in a lack of accurate information on vertical distribution of atmospheric constituents. Whereas light-weight instruments carried by meteorological balloons are becoming progressively available, their usage is constrained by the cost of the equipment or the recovery operations. The evolving need in cost-efficient observations for UTS process studies has led to development of small airborne platforms - unmanned aerial vehicles (UAV), capable of carrying small sensors for in-situ measurements. We present a new UAV-based stratospheric sounding platform capable of carrying scientific payload of up to 2 kg. The airborne platform comprises of a latex meteorological balloon and detachable flying wing type UAV with internal measurement controller. The UAV is launched on a balloon to stratospheric altitudes up to 20 km, where it can be automatically released by autopilot or by a remote command sent from the ground control. Having been released from the balloon the UAV glides down and returns to the launch position. Autopilot using 3-axis gyro, accelerometer, barometer, compas and GPS navigation provides flight stabilization and optimal way back trajectory. Backup manual control is provided for emergencies. During the flight the onboard measurement controller stores the data into internal memory and transmits current flight parameters to the ground station via telemetry. Precise operation of the flight control systems ensures safe landing at the launch point. A series of field tests of the detachable stratospheric UAV has been conducted. The scientific payload included the following instruments involved in different flights: a) stratospheric Lyman-alpha hygrometer (FLASH); b) backscatter sonde; c) electrochemical

  14. 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).

  15. Evidence-Based Cancer Imaging

    PubMed Central

    Khorasani, Ramin

    2017-01-01

    With the advances in the field of oncology, imaging is increasingly used in the follow-up of cancer patients, leading to concerns about over-utilization. Therefore, it has become imperative to make imaging more evidence-based, efficient, cost-effective and equitable. This review explores the strategies and tools to make diagnostic imaging more evidence-based, mainly in the context of follow-up of cancer patients. PMID:28096722

  16. Knowledge-Based Image Analysis.

    DTIC Science & Technology

    1981-04-01

    UNCLASSIF1 ED ETL-025s N IIp ETL-0258 AL Ai01319 S"Knowledge-based image analysis u George C. Stockman Barbara A. Lambird I David Lavine Laveen N. Kanal...extraction, verification, region classification, pattern recognition, image analysis . 3 20. A. CT (Continue on rever.. d. It necessary and Identify by...UNCLgSTFTF n In f SECURITY CLASSIFICATION OF THIS PAGE (When Date Entered) .L1 - I Table of Contents Knowledge Based Image Analysis I Preface

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-04-08

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

  19. Vision-based state estimation for uninhabited aerial vehicles using the coplanarity constraint

    NASA Astrophysics Data System (ADS)

    Webb, Thomas Philip

    2007-12-01

    We developed and evaluated a vision-based state estimation algorithm for uninhabited aerial vehicles (UAVs) using the implicit extended Kalman filter (IEKF) and the coplanarity constraint (also known as the epipolar or essential constraint). The coplanarity constraint, a well-known property in the structure from motion (SFM) field, has advantages for this application in that the feature point locations in three dimensional space do not have to be known and tracked and that feature points can be discarded and acquired as necessary. This reduces the computational load which is important for real time applications such as aircraft control. Advantages of the IEKF are that, in principle, the current estimate uses all previous information, not just the current observations, and that the estimate will propagate forward in an orderly fashion in the case of interrupted or reduced measurements. The dynamics of the aircraft are included in the process model which improves the observability of the states and resolves the SFM scale factor ambiguity. The algorithm was implemented in a numerical simulation and exhibited divergence problems in the presence of measurement noise. These effects were particularly evident in the velocity estimates. The problems were eliminated by zeroing out the small velocity dependent terms in the measurement matrix. The algorithm was exercised in a Monte Carlo fashion and found to be robust to errors in the process model and to measurement noise. Sensitivities to filter and focal plane implementation parameters including camera depression angle, field of view, measurement interval, and feature point location and number were also assessed. The modified estimator was then employed in a closed loop UAV simulation to provide feedback to a simple autopilot. The simulation demonstrated that the state estimates provided were sufficiently accurate to allow control of the UAV through successful waypoint navigation. This simulation used feature points

  20. GPS-aided inertial technology and navigation-based photogrammetry for aerial mapping the San Andreas fault system

    USGS Publications Warehouse

    Sanchez, Richard D.; Hudnut, Kenneth W.

    2004-01-01

    Aerial mapping of the San Andreas Fault System can be realized more efficiently and rapidly without ground control and conventional aerotriangulation. This is achieved by the direct geopositioning of the exterior orientation of a digital imaging sensor by use of an integrated Global Positioning System (GPS) receiver and an Inertial Navigation System (INS). A crucial issue to this particular type of aerial mapping is the accuracy, scale, consistency, and speed achievable by such a system. To address these questions, an Applanix Digital Sensor System (DSS) was used to examine its potential for near real-time mapping. Large segments of vegetation along the San Andreas and Cucamonga faults near the foothills of the San Bernardino and San Gabriel Mountains were burned to the ground in the California wildfires of October-November 2003. A 175 km corridor through what once was a thickly vegetated and hidden fault surface was chosen for this study. Both faults pose a major hazard to the greater Los Angeles metropolitan area and a near real-time mapping system could provide information vital to a post-disaster response.

  1. 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 ...

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

    NASA Astrophysics Data System (ADS)

    Uchida, Keitaro; Ito, Shusei; Yamamoto, Hirotsugu

    2017-02-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  5. Measuring Sunflower Nitrogen Status from AN Unmanned Aerial Vehicle-Based System and AN on the Ground Device

    NASA Astrophysics Data System (ADS)

    Agüera, F.; Carvajal, F.; Pérez, M.

    2011-09-01

    Precision agriculture recognizes the inherent spatial variability associated with soil characteristics, land morphology and crop growth, and uses this information to prescribe the most appropriate management strategy on a site-specific basis. To reach this task, the most important information related with crop growth is nutrient status, weed infestation, disease and pet affectation and water management. The application of fertilizer nitrogen to field crops is of critical importance because it determines plant's gro wth, vigour, colour and yield. Furthermore, nitrogen has been observed as a nutrient with high spatial variability in a single field, related to its high mobility. Some previous works have shown that is possible to measure crop nitrogen status with optical instruments. Since most leaf nitrogen is contained in chlorophyll molecules, there is a strong relationship between leaf nitrogen and leaf chlorophyll content, which is the basis for predicting crop nitrogen status by measuring leaf reflectance. So, sensors that can easily monitor crop nitrogen amount throughout the growing season at a high resolution to allow producers to reach their production goals, will give useful information to prescribe a crop management on a site-specific basis. Sunflower is a crop which is taking importance again because it can be used both for food and biofuel purposes, and it is widely cultivated in the South of Spain and other European countries.The aim of this work was to compare an index related with sunflower nitrogen status, deduced from multispectral images taken from an Unmanned Aerial Vehicle (UAV), with optical data collected with a ground-based platform.An ADC Lite Tetracam digital cam was mounted on a md4-200 Microdrones to take pictures of a sunflower field during the crop season. ADC Lite Tetracam is a single sensor digital camera designed for capture of visible light wavelength longer than 520 nm and near-infrared wavelength up to 920 nm. The md4

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  7. Aerial vehicles collision avoidance using monocular vision

    NASA Astrophysics Data System (ADS)

    Balashov, Oleg; Muraviev, Vadim; Strotov, Valery

    2016-10-01

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

  8. Imaging based refractometers

    DOEpatents

    Baba, Justin S.

    2015-11-24

    Refractometers for simultaneously measuring refractive index of a sample over a range or wavelengths of light include dispersive and focusing optical systems. An optical beam including the rang of wavelengths is spectrally spread along a first axis and focused along a second axis so as to be incident to an interface between the sample and a prism at a range of angles of incidence including a critical angle for at least one wavelength. In some cases, the prism can have a triangle, parallelogram, trapezoid, or other shape. In some cases, the optical beam can be reflected off of multiple interfaces between the prism and the sample. An imaging detector is situated to receive the spectrally spread and focused light from the interface and form an image corresponding to angle of incidence as a function of wavelength. One or more critical angles are indentified and corresponding refractive indices are determined.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  11. Photography-based image generator

    NASA Astrophysics Data System (ADS)

    Dalton, Nicholas M.; Deering, Charles S.

    1989-09-01

    A two-channel Photography Based Image Generator system was developed to drive the Helmet Mounted Laser Projector at the Naval Training System Center at Orlando, Florida. This projector is a two-channel system that displays a wide field-of-view color image with a high-resolution inset to efficiently match the pilot's visual capability. The image generator is a derivative of the LTV-developed visual system installed in the A-7E Weapon System Trainer at NAS Cecil Field. The Photography Based Image Generator is based on patented LTV technology for high resolution, multi-channel, real world visual simulation. Special provisions were developed for driving the NTSC-developed and patented Helmet Mounted Laser Projector. These include a special 1023-line raster format, an electronic image blending technique, spherical lens mapping for dome projection, a special computer interface for head/eye tracking and flight parameters, special software, and a number of data bases. Good gaze angle tracking is critical to the use of the NTSC projector in a flight simulation environment. The Photography Based Image Generator provides superior dynamic response by performing a relatively simple perspective transformation on stored, high-detail photography instead of generating this detail by "brute force" computer image generation methods. With this approach, high detail can be displayed and updated at the television field rate (60 Hz).

  12. Neural-network-based navigation and control of unmanned aerial vehicles for detecting unintended emissions

    NASA Astrophysics Data System (ADS)

    Zargarzadeh, H.; Nodland, David; Thotla, V.; Jagannathan, S.; Agarwal, S.

    2012-06-01

    Unmanned Aerial Vehicles (UAVs) are versatile aircraft with many applications, including the potential for use to detect unintended electromagnetic emissions from electronic devices. A particular area of recent interest has been helicopter unmanned aerial vehicles. Because of the nature of these helicopters' dynamics, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via output feedback control for trajectory tracking of a helicopter UAV using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic, virtual, and dynamic controllers and an observer. Optimal tracking is accomplished with a single NN utilized for cost function approximation. The controller positions the helicopter, which is equipped with an antenna, such that the antenna can detect unintended emissions. The overall closed-loop system stability with the proposed controller is demonstrated by using Lyapunov analysis. Finally, results are provided to demonstrate the effectiveness of the proposed control design for positioning the helicopter for unintended emissions detection.

  13. Image-based occupancy sensor

    SciTech Connect

    Polese, Luigi Gentile; Brackney, Larry

    2015-05-19

    An image-based occupancy sensor includes a motion detection module that receives and processes an image signal to generate a motion detection signal, a people detection module that receives the image signal and processes the image signal to generate a people detection signal, a face detection module that receives the image signal and processes the image signal to generate a face detection signal, and a sensor integration module that receives the motion detection signal from the motion detection module, receives the people detection signal from the people detection module, receives the face detection signal from the face detection module, and generates an occupancy signal using the motion detection signal, the people detection signal, and the face detection signal, with the occupancy signal indicating vacancy or occupancy, with an occupancy indication specifying that one or more people are detected within the monitored volume.

  14. 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.

  15. 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.

  16. Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

    PubMed

    Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

    2015-03-19

    Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

  17. Imaging of skull base lesions.

    PubMed

    Kelly, Hillary R; Curtin, Hugh D

    2016-01-01

    Skull base imaging requires a thorough knowledge of the complex anatomy of this region, including the numerous fissures and foramina and the major neurovascular structures that traverse them. Computed tomography (CT) and magnetic resonance imaging (MRI) play complementary roles in imaging of the skull base. MR is the preferred modality for evaluation of the soft tissues, the cranial nerves, and the medullary spaces of bone, while CT is preferred for demonstrating thin cortical bone structure. The anatomic location and origin of a lesion as well as the specific CT and MR findings can often narrow the differential diagnosis to a short list of possibilities. However, the primary role of the imaging specialist in evaluating the skull base is usually to define the extent of the lesion and determine its relationship to vital neurovascular structures. Technologic advances in imaging and radiation therapy, as well as surgical technique, have allowed for more aggressive approaches and improved outcomes, further emphasizing the importance of precise preoperative mapping of skull base lesions via imaging. Tumors arising from and affecting the cranial nerves at the skull base are considered here.

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

    NASA Astrophysics Data System (ADS)

    Kwak, Eunju

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

  19. Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles

    PubMed Central

    Gökçe, Fatih; Üçoluk, Göktürk; Şahin, Erol; Kalkan, Sinan

    2015-01-01

    Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032×778 resolution) and 150 ms outdoors (1280×720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms. PMID:26393599

  20. Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles.

    PubMed

    Gökçe, Fatih; Üçoluk, Göktürk; Şahin, Erol; Kalkan, Sinan

    2015-09-18

    Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032 × 778 resolution) and 150 ms outdoors (1280 × 720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms.

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  2. 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)

  3. 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.

  4. Edge-based correlation image registration for multispectral imaging

    DOEpatents

    Nandy, Prabal

    2009-11-17

    Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

  5. Creating a large-scale content-based airphoto image digital library.

    PubMed

    Zhu, B; Ramsey, M; Chen, H

    2000-01-01

    This paper describes a content-based image retrieval digital library that supports geographical image retrieval over a testbed of 800 aerial photographs, each 25 megabytes in size. In addition, this paper also introduces a methodology to evaluate the performance of the algorithms in the prototype system. There are two major contributions: we suggest an approach that incorporates various image processing techniques including Gabor filters, image enhancement and image compression, as well as information analysis techniques such as the self-organizing map (SOM) into an effective large-scale geographical image retrieval system. We present two experiments that evaluate the performance of the Gabor-filter-extracted features along with the corresponding similarity measure against that of human perception, addressing the lack of studies in assessing the consistency between an image representation algorithm or an image categorization method and human mental model.

  6. 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.

  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. Scene-Level Geographic Image Classification Based on a Covariance Descriptor Using Supervised Collaborative Kernel Coding.

    PubMed

    Yang, Chunwei; Liu, Huaping; Wang, Shicheng; Liao, Shouyi

    2016-03-18

    Scene-level geographic image classification has been a very challenging problem and has become a research focus in recent years. This paper develops a supervised collaborative kernel coding method based on a covariance descriptor (covd) for scene-level geographic image classification. First, covd is introduced in the feature extraction process and, then, is transformed to a Euclidean feature by a supervised collaborative kernel coding model. Furthermore, we develop an iterative optimization framework to solve this model. Comprehensive evaluations on public high-resolution aerial image dataset and comparisons with state-of-the-art methods show the superiority and effectiveness of our approach.

  9. Scene-Level Geographic Image Classification Based on a Covariance Descriptor Using Supervised Collaborative Kernel Coding

    PubMed Central

    Yang, Chunwei; Liu, Huaping; Wang, Shicheng; Liao, Shouyi

    2016-01-01

    Scene-level geographic image classification has been a very challenging problem and has become a research focus in recent years. This paper develops a supervised collaborative kernel coding method based on a covariance descriptor (covd) for scene-level geographic image classification. First, covd is introduced in the feature extraction process and, then, is transformed to a Euclidean feature by a supervised collaborative kernel coding model. Furthermore, we develop an iterative optimization framework to solve this model. Comprehensive evaluations on public high-resolution aerial image dataset and comparisons with state-of-the-art methods show the superiority and effectiveness of our approach. PMID:26999150

  10. Stereo matching based on census transformation of image gradients

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

    Although multiple-view matching provides certain significant advantages regarding accuracy, occlusion handling and radiometric fidelity, stereo-matching remains indispensable for a variety of applications; these involve cases when image acquisition requires fixed geometry and limited number of images or speed. Such instances include robotics, autonomous navigation, reconstruction from a limited number of aerial/satellite images, industrial inspection and augmented reality through smart-phones. As a consequence, stereo-matching is a continuously evolving research field with growing variety of applicable scenarios. In this work a novel multi-purpose cost for stereo-matching is proposed, based on census transformation on image gradients and evaluated within a local matching scheme. It is demonstrated that when the census transformation is applied on gradients the invariance of the cost function to changes in illumination (non-linear) is significantly strengthened. The calculated cost values are aggregated through adaptive support regions, based both on cross-skeletons and basic rectangular windows. The matching algorithm is tuned for the parameters in each case. The described matching cost has been evaluated on the Middlebury stereo-vision 2006 datasets, which include changes in illumination and exposure. The tests verify that the census transformation on image gradients indeed results in a more robust cost function, regardless of aggregation strategy.

  11. 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

  12. Detection of MAVs (Micro Aerial Vehicles) based on millimeter wave radar

    NASA Astrophysics Data System (ADS)

    Noetel, Denis; Johannes, Winfried; Caris, Michael; Hommes, Alexander; Stanko, Stephan

    2016-10-01

    In this paper we present two system approaches for perimeter surveillance with radar techniques focused on the detection of Micro Aerial Vehicles (MAVs). The main task of such radars is to detect movements of targets such as an individual or a vehicle approaching a facility. The systems typically cover a range of several hundred meters up to several kilometers. In particular, the capability of identifying Remotely Piloted Aircraft Systems (RPAS), which pose a growing threat on critical infrastructure areas, is of great importance nowadays. The low costs, the ease of handling and a considerable payload make them an excellent tool for unwanted surveillance or attacks. Most platforms can be equipped with all kind of sensors or, in the worst case, with destructive devices. A typical MAV is able to take off and land vertically, to hover, and in many cases to fly forward at high speed. Thus, it can reach all kinds of places in short time while the concealed operator of the MAV resides at a remote and riskless place.

  13. Development of unmanned aerial vehicle (UAV) based high altitude balloon (HAB) platform for active aerosol sampling

    NASA Astrophysics Data System (ADS)

    Lateran, S.; Sedan, M. F.; Harithuddin, A. S. M.; Azrad, S.

    2016-10-01

    The knowledge on the abundance and diversity of the minute particles or aerosols in the earth's stratosphere is still in its infancy as aerosol sampling at high-altitude still possess a lot of challenges. Thus far, high-altitude aerosol sampling has been conducted mostly using manned flights, which requires enormous financial and logistical resources. There had been researches for the utilisation of high altitude balloon (HAB) for active and passive aerosol samplings within the stratosphere. However, the gathered samples in the payload were either brought down by controlling the balloon air pressure or were just dropped with a parachute to slow the descend speed in order to reduce the impact upon landing. In most cases, the drop location of the sample are unfavorable such as in the middle of the sea, dense foliage, etc. Hence a system that can actively sample aerosols at high-altitude and improve the delivery method in terms of quality and reliability using unmanned aerial vehicle (UAV) is designed and tested in this study.

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  16. A content-based image retrieval method for optical colonoscopy images based on image recognition techniques

    NASA Astrophysics Data System (ADS)

    Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro

    2015-03-01

    This paper proposes a content-based image retrieval method for optical colonoscopy images that can find images similar to ones being diagnosed. Optical colonoscopy is a method of direct observation for colons and rectums to diagnose bowel diseases. It is the most common procedure for screening, surveillance and treatment. However, diagnostic accuracy for intractable inflammatory bowel diseases, such as ulcerative colitis (UC), is highly dependent on the experience and knowledge of the medical doctor, because there is considerable variety in the appearances of colonic mucosa within inflammations with UC. In order to solve this issue, this paper proposes a content-based image retrieval method based on image recognition techniques. The proposed retrieval method can find similar images from a database of images diagnosed as UC, and can potentially furnish the medical records associated with the retrieved images to assist the UC diagnosis. Within the proposed method, color histogram features and higher order local auto-correlation (HLAC) features are adopted to represent the color information and geometrical information of optical colonoscopy images, respectively. Moreover, considering various characteristics of UC colonoscopy images, such as vascular patterns and the roughness of the colonic mucosa, we also propose an image enhancement method to highlight the appearances of colonic mucosa in UC. In an experiment using 161 UC images from 32 patients, we demonstrate that our method improves the accuracy of retrieving similar UC images.

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

    DTIC Science & Technology

    2005-01-01

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

  18. Image Based Synthesis for Airborne Minefield Data

    DTIC Science & Technology

    2005-12-01

    applications of image synthesis include artificial texture generation [1], image repairing [2], photometric image rendering [3] and ultrasound imaging...1999. 4. M. Song, R. M. Haralick, F.H. Sheehan, " Ultrasound imaging simulation and echocardiographic image synthesis ", Proceedings of the IEEE...Night Vision and Electronic Sensors Directorate AMSRD-CER-NV-TR-246I Image Based Synthesis for Airborne Minefield Data December 2005 Approved for

  19. Unmanned aerial vehicle: A unique platform for low-altitude remote sensing for crop management

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Unmanned aerial vehicles (UAV) provide a unique platform for remote sensing to monitor crop fields that complements remote sensing from satellite, aircraft and ground-based platforms. The UAV-based remote sensing is versatile at ultra-low altitude to be able to provide an ultra-high-resolution imag...

  20. Pheromone-based coordination strategy to static sensors on the ground and unmanned aerial vehicles carried sensors

    NASA Astrophysics Data System (ADS)

    Pignaton de Freitas, Edison; Heimfarth, Tales; Pereira, Carlos Eduardo; Morado Ferreira, Armando; Rech Wagner, Flávio; Larsson, Tony

    2010-04-01

    A current trend that is gaining strength in the wireless sensor network area is the use of heterogeneous sensor nodes in one coordinated overall network, needed to fulfill the requirements of sophisticated emerging applications, such as area surveillance systems. One of the main concerns when developing such sensor networks is how to provide coordination among the heterogeneous nodes, in order to enable them to efficiently respond the user needs. This study presents an investigation of strategies to coordinate a set of static sensor nodes on the ground cooperating with wirelessly connected Unmanned Aerial Vehicles (UAVs) carrying a variety of sensors, in order to provide efficient surveillance over an area of interest. The sensor nodes on the ground are set to issue alarms on the occurrence of a given event of interest, e.g. entrance of a non-authorized vehicle in the area, while the UAVs receive the issued alarms and have to decide which of them is the most suitable to handle the issued alarm. A bio-inspired coordination strategy based on the concept of pheromones is presented. As a complement of this strategy, a utility-based decision making approach is proposed.

  1. 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.

  2. 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

  3. 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.

  4. 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%.

  5. Data Structures and Algorithms for Graph Based Remote Sensed Image Content Storage and Retrieval

    SciTech Connect

    Grant, C W

    2004-06-24

    The Image Content Engine (ICE) project at Lawrence Livermore National Laboratory (LLNL) extracts, stores and allows queries of image content on multiple levels. ICE is designed for multiple application domains. The domain explored in this work is aerial and satellite surveillance imagery. The highest level of semantic information used in ICE is graph based. After objects are detected and classified, they are grouped based in their interrelations. The graph representing a locally related set of objects is called a 'graphlet'. Graphlets are interconnected into a larger graph which covers an entire set of images. Queries based on graph properties are notoriously difficult due the inherent complexity of the graph isomorphism and sub-graph isomorphism problems. ICE exploits limitations in graph and query structure and uses a set of auxiliary data structures to quickly process a useful set of graph based queries. These queries could not be processed using semantically lower level (tile and object based) queries.

  6. Illumination-invariant image matching for autonomous UAV localisation based on optical sensing

    NASA Astrophysics Data System (ADS)

    Wan, Xue; Liu, Jianguo; Yan, Hongshi; Morgan, Gareth L. K.

    2016-09-01

    This paper presents an UAV (Unmanned Aerial Vehicle) localisation algorithm for its autonomous navigation based on matching between on-board UAV image sequences to a pre-installed reference satellite image. As the UAV images and the reference image are not necessarily taken under the same illumination condition, illumination-invariant image matching is essential. Based on the investigation of illumination-invariant property of Phase Correlation (PC) via mathematical derivation and experiments, we propose a PC based fast and robust illumination-invariant localisation algorithm for UAV navigation. The algorithm accurately determines the current UAV position as well as the next UAV position even the illumination condition of UAV on-board images is different from the reference satellite image. A Dirac delta function based registration quality assessment together with a risk alarming criterion is introduced to enable the UAV to perform self-correction in case the UAV deviates from the planned route. UAV navigation experiments using simulated terrain shading images and remote sensing images have demonstrated a robust high performance of the proposed PC based localisation algorithm under very different illumination conditions resulted from solar motion. The superiority of the algorithm, in comparison with two other widely used image matching algorithms, MI (Mutual Information) and NCC (Normalised Correlation Coefficient), is significant for its high matching accuracy and fast processing speed.

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

    DTIC Science & Technology

    2014-11-10

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

  8. Image feature based GPS trace filtering for road network generation and road segmentation

    DOE PAGES

    Yuan, Jiangye; Cheriyadat, Anil M.

    2015-10-19

    We propose a new method to infer road networks from GPS trace data and accurately segment road regions in high-resolution aerial images. Unlike previous efforts that rely on GPS traces alone, we exploit image features to infer road networks from noisy trace data. The inferred road network is used to guide road segmentation. We show that the number of image segments spanned by the traces and the trace orientation validated with image features are important attributes for identifying GPS traces on road regions. Based on filtered traces , we construct road networks and integrate them with image features to segmentmore » road regions. Lastly, our experiments show that the proposed method produces more accurate road networks than the leading method that uses GPS traces alone, and also achieves high accuracy in segmenting road regions even with very noisy GPS data.« less

  9. Image feature based GPS trace filtering for road network generation and road segmentation

    SciTech Connect

    Yuan, Jiangye; Cheriyadat, Anil M.

    2015-10-19

    We propose a new method to infer road networks from GPS trace data and accurately segment road regions in high-resolution aerial images. Unlike previous efforts that rely on GPS traces alone, we exploit image features to infer road networks from noisy trace data. The inferred road network is used to guide road segmentation. We show that the number of image segments spanned by the traces and the trace orientation validated with image features are important attributes for identifying GPS traces on road regions. Based on filtered traces , we construct road networks and integrate them with image features to segment road regions. Lastly, our experiments show that the proposed method produces more accurate road networks than the leading method that uses GPS traces alone, and also achieves high accuracy in segmenting road regions even with very noisy GPS data.

  10. 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.

  11. Pose Estimation of Unmanned Aerial Vehicles Based on a Vision-Aided Multi-Sensor Fusion

    NASA Astrophysics Data System (ADS)

    Abdi, G.; Samadzadegan, F.; Kurz, F.

    2016-06-01

    GNSS/IMU navigation systems offer low-cost and robust solution to navigate UAVs. Since redundant measurements greatly improve the reliability of navigation systems, extensive researches have been made to enhance the efficiency and robustness of GNSS/IMU by additional sensors. This paper presents a method for integrating reference data, images taken from UAVs, barometric height data and GNSS/IMU data to estimate accurate and reliable pose parameters of UAVs. We provide improved pose estimations by integrating multi-sensor observations in an EKF algorithm with IMU motion model. The implemented methodology has demonstrated to be very efficient and reliable for automatic pose estimation. The calculated position and attitude of the UAV especially when we removed the GNSS from the working cycle clearly indicate the ability of the purposed methodology.

  12. Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and epidemiological application.

    PubMed

    Maxwell, Susan K

    2010-12-01

    Satellite imagery and aerial photography represent a vast resource to significantly enhance environmental mapping and modeling applications for use in understanding spatio-temporal relationships between environment and health. Deriving boundaries of land cover objects, such as trees, buildings, and crop fields, from image data has traditionally been performed manually using a very time consuming process of hand digitizing. Boundary detection algorithms are increasingly being applied using object-based image analysis (OBIA) technology to automate the process. The purpose of this paper is to present an overview and demonstrate the application of OBIA for delineating land cover features at multiple scales using a high resolution aerial photograph (1 m) and a medium resolution Landsat image (30 m) time series in the context of a pesticide spray drift exposure application.

  13. Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and epidemiological application

    PubMed Central

    Maxwell, Susan K.

    2010-01-01

    Satellite imagery and aerial photography represent a vast resource to significantly enhance environmental mapping and modeling applications for use in understanding spatio-temporal relationships between environment and health. Deriving boundaries of land cover objects, such as trees, buildings, and crop fields, from image data has traditionally been performed manually using a very time consuming process of hand digitizing. Boundary detection algorithms are increasingly being applied using object-based image analysis (OBIA) technology to automate the process. The purpose of this paper is to present an overview and demonstrate the application of OBIA for delineating land cover features at multiple scales using a high resolution aerial photograph (1 m) and a medium resolution Landsat image (30 m) time series in the context of a pesticide spray drift exposure application. PMID:21135917

  14. 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.

  15. 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.

  16. Group-Based Image Retrieval Method for Video Image Annotation

    NASA Astrophysics Data System (ADS)

    Murabayashi, Noboru; Kurahashi, Setsuya; Yoshida, Kenichi

    This paper proposes a group-based image retrieval method for video image annotation systems. Although the wide spread use of video camera recorders has increased the demand for an automated annotation system for personal videos, conventional image retrieval methods cannot achieve enough accuracy to be used as an annotation engine. Recording conditions, such as change of the brightness by weather condition, shadow by the surroundings, and etc, affect the qualities of images recorded by the personal video camera recorders. The degraded image of personal video makes the retrieval task difficult. Furthermore, it is difficult to discriminate similar images without any auxiliary information. To cope with these difficulties, this paper proposes a group-based image retrieval method. Its characteristics are 1) the use of image similarity based on the wavelet transformation based features and the scale invariant feature transform based features, and 2) the pre-grouping of related images and screening using group information. Experimental results show that the proposed method can improve image retrieval accuracy to 90% up from the conventional method of 40%.

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

    USGS Publications Warehouse

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

    2016-01-01

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

  18. Unmanned Carrier-Based Aircraft System: Debate over Systems Role Led to Focus on Aerial Refueling

    DTIC Science & Technology

    2016-03-24

    this performance audit from June 2015 to March 2016 in accordance with generally accepted government auditing standards. Those standards require that...we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on...our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives

  19. Physical controls and patterns of recruitment on the Drôme River (SE France): An analysis based on a chronosequence of high resolution aerial imagery

    NASA Astrophysics Data System (ADS)

    Piegay, H.; Stella, J. C.; Raepple, B.

    2014-12-01

    Along with the recent recognition of the role of vegetation in influencing channel hydraulics, and thus fluvial morphology comes the need for scientific research on vegetation recruitment and its control factors. Flood disturbance is known to create a suitable physical template for the establishment of woody pioneers. Sapling recruitment patterns and underlying physical controls were investigated on a 5 km braided reach of the Drôme River in South-eastern France, following the 2003 50-year flood event. The approach was based on the analysis of a chronosequence of high resolution aerial images acquired yearly between 2005 and 2011, complemented by airborne LiDAR data and field observations. The study highlights how physical complexity induced by natural variations in hydro-climatic and consequently hydro-geomorphic conditions facilitates variable patterns of recruitment. The initial post-flood vegetative units, which covered up to 10% of the total active channel area in 2005, was seen to double within six years. The variability of hydro-climatic conditions was reflected in the temporal and spatial patterns of recruitment, with a pronounced peak of vegetation expansion in 2007 and a decreasing trend following higher flows in 2009. Recruitment was further seen to be sustained in a variety of geomorphic units, which showed different probabilities and patterns of recruitment. Active channels were the prominent geomorphic unit in terms of total biomass development, while in-channel wood units showed the highest probability for recruitment. Vegetation recruitment understanding is becoming crucial for predicting fluvial system evolution in different hydroclimatic contexts. Applied, these findings may contribute to improve efforts made in the field of flood risk management, as well as restoration planning.

  20. Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

    NASA Astrophysics Data System (ADS)

    Hua, Tianxiang; Chen, Jiamin; Pei, Dongju; Zhang, Wenquan; Zhou, Nanrun

    2015-02-01

    A novel quantum gray-level image encryption and decryption algorithm based on image correlation decomposition is proposed. The correlation among image pixels is established by utilizing the superposition and measurement principle of quantum states. And a whole quantum image is divided into a series of sub-images. These sub-images are stored into a complete binary tree array constructed previously and then randomly performed by one of the operations of quantum random-phase gate, quantum revolving gate and Hadamard transform. The encrypted image can be obtained by superimposing the resulting sub-images with the superposition principle of quantum states. For the encryption algorithm, the keys are the parameters of random phase gate, rotation angle, binary sequence and orthonormal basis states. The security and the computational complexity of the proposed algorithm are analyzed. The proposed encryption algorithm can resist brute force attack due to its very large key space and has lower computational complexity than its classical counterparts.

  1. Multispectral Image Road Extraction Based Upon Automated Map Conflation

    NASA Astrophysics Data System (ADS)

    Chen, Bin

    Road network extraction from remotely sensed imagery enables many important and diverse applications such as vehicle tracking, drone navigation, and intelligent transportation studies. There are, however, a number of challenges to road detection from an image. Road pavement material, width, direction, and topology vary across a scene. Complete or partial occlusions caused by nearby buildings, trees, and the shadows cast by them, make maintaining road connectivity difficult. The problems posed by occlusions are exacerbated with the increasing use of oblique imagery from aerial and satellite platforms. Further, common objects such as rooftops and parking lots are made of materials similar or identical to road pavements. This problem of common materials is a classic case of a single land cover material existing for different land use scenarios. This work addresses these problems in road extraction from geo-referenced imagery by leveraging the OpenStreetMap digital road map to guide image-based road extraction. The crowd-sourced cartography has the advantages of worldwide coverage that is constantly updated. The derived road vectors follow only roads and so can serve to guide image-based road extraction with minimal confusion from occlusions and changes in road material. On the other hand, the vector road map has no information on road widths and misalignments between the vector map and the geo-referenced image are small but nonsystematic. Properly correcting misalignment between two geospatial datasets, also known as map conflation, is an essential step. A generic framework requiring minimal human intervention is described for multispectral image road extraction and automatic road map conflation. The approach relies on the road feature generation of a binary mask and a corresponding curvilinear image. A method for generating the binary road mask from the image by applying a spectral measure is presented. The spectral measure, called anisotropy-tunable distance (ATD

  2. Control of a Quadcopter Aerial Robot Using Optic Flow Sensing

    NASA Astrophysics Data System (ADS)

    Hurd, Michael Brandon

    This thesis focuses on the motion control of a custom-built quadcopter aerial robot using optic flow sensing. Optic flow sensing is a vision-based approach that can provide a robot the ability to fly in global positioning system (GPS) denied environments, such as indoor environments. In this work, optic flow sensors are used to stabilize the motion of quadcopter robot, where an optic flow algorithm is applied to provide odometry measurements to the quadcopter's central processing unit to monitor the flight heading. The optic-flow sensor and algorithm are capable of gathering and processing the images at 250 frames/sec, and the sensor package weighs 2.5 g and has a footprint of 6 cm2 in area. The odometry value from the optic flow sensor is then used a feedback information in a simple proportional-integral-derivative (PID) controller on the quadcopter. Experimental results are presented to demonstrate the effectiveness of using optic flow for controlling the motion of the quadcopter aerial robot. The technique presented herein can be applied to different types of aerial robotic systems or unmanned aerial vehicles (UAVs), as well as unmanned ground vehicles (UGV).

  3. Quantum Image Encryption Algorithm Based on Quantum Image XOR Operations

    NASA Astrophysics Data System (ADS)

    Gong, Li-Hua; He, Xiang-Tao; Cheng, Shan; Hua, Tian-Xiang; Zhou, Nan-Run

    2016-07-01

    A novel encryption algorithm for quantum images based on quantum image XOR operations is designed. The quantum image XOR operations are designed by using the hyper-chaotic sequences generated with the Chen's hyper-chaotic system to control the control-NOT operation, which is used to encode gray-level information. The initial conditions of the Chen's hyper-chaotic system are the keys, which guarantee the security of the proposed quantum image encryption algorithm. Numerical simulations and theoretical analyses demonstrate that the proposed quantum image encryption algorithm has larger key space, higher key sensitivity, stronger resistance of statistical analysis and lower computational complexity than its classical counterparts.

  4. Evaluation of Methods for Coregistration and Fusion of Rpas-Based 3d Point Clouds and Thermal Infrared Images

    NASA Astrophysics Data System (ADS)

    Hoegner, L.; Tuttas, S.; Xu, Y.; Eder, K.; Stilla, U.

    2016-06-01

    This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR) images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i) coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii) coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii) coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv) coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v) coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

  5. Object-based representations of spatial images

    NASA Astrophysics Data System (ADS)

    Newsam, Shawn; Bhagavathy, Sitaram; Kenney, Charles; Manjunath, B. S.; Fonseca, Leila

    2001-03-01

    Object based representations of image data enable new content-related functionalities while facilitating management of large image databases. Developing such representations for multi-date and multi-spectral images is one of the objectives of the second phase of the Alexandria Digital Library (ADL) project at UCSB. Image segmentation and image registration are two of the main issues that are to be addressed in creating localized image representations. We present in this paper some of the recent and current work by the ADL's image processing group on robust image segmentation, registration, and the use of image texture for content representation. Built upon these technologies are techniques for managing large repositories of data. A texture thesaurus assists in creating a semantic classification of image regions. An object-based representation is proposed to facilitate data storage, retrieval, analysis, and navigation.

  6. Wavelet based image visibility enhancement of IR images

    NASA Astrophysics Data System (ADS)

    Jiang, Qin; Owechko, Yuri; Blanton, Brendan

    2016-05-01

    Enhancing the visibility of infrared images obtained in a degraded visibility environment is very important for many applications such as surveillance, visual navigation in bad weather, and helicopter landing in brownout conditions. In this paper, we present an IR image visibility enhancement system based on adaptively modifying the wavelet coefficients of the images. In our proposed system, input images are first filtered by a histogram-based dynamic range filter in order to remove sensor noise and convert the input images into 8-bit dynamic range for efficient processing and display. By utilizing a wavelet transformation, we modify the image intensity distribution and enhance image edges simultaneously. In the wavelet domain, low frequency wavelet coefficients contain original image intensity distribution while high frequency wavelet coefficients contain edge information for the original images. To modify the image intensity distribution, an adaptive histogram equalization technique is applied to the low frequency wavelet coefficients while to enhance image edges, an adaptive edge enhancement technique is applied to the high frequency wavelet coefficients. An inverse wavelet transformation is applied to the modified wavelet coefficients to obtain intensity images with enhanced visibility. Finally, a Gaussian filter is used to remove blocking artifacts introduced by the adaptive techniques. Since wavelet transformation uses down-sampling to obtain low frequency wavelet coefficients, histogram equalization of low-frequency coefficients is computationally more efficient than histogram equalization of the original images. We tested the proposed system with degraded IR images obtained from a helicopter landing in brownout conditions. Our experimental results show that the proposed system is effective for enhancing the visibility of degraded IR images.

  7. An Improved Vision-based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

    NASA Astrophysics Data System (ADS)

    Zhao, Yunji; Pei, Hailong

    In vision-based autonomous landing system of UAV, the efficiency of target detecting and tracking will directly affect the control system. The improved algorithm of SURF(Speed Up Robust Features) will resolve the problem which is the inefficiency of the SURF algorithm in the autonomous landing system. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiment and theoretical analysis testify the efficiency of the algorithm.

  8. Flexible Wing Base Micro Aerial Vehicles: Micro Air Vehicles (MAVs) for Surveillance and Remote Sensor Delivery

    NASA Technical Reports Server (NTRS)

    Ifju, Peter

    2002-01-01

    Micro Air Vehicles (MAVs) will be developed for tracking individuals, locating terrorist threats, and delivering remote sensors, for surveillance and chemical/biological agent detection. The tasks are: (1) Develop robust MAV platform capable of carrying sensor payload. (2) Develop fully autonomous capabilities for delivery of sensors to remote and distant locations. The current capabilities and accomplishments are: (1) Operational electric (inaudible) 6-inch MAVs with novel flexible wing, providing superior aerodynamic efficiency and control. (2) Vision-based flight stability and control (from on-board cameras).

  9. Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

    PubMed Central

    Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

    2009-01-01

    The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

  10. A performance study of unmanned aerial vehicle-based sensor networks under cyber attack

    NASA Astrophysics Data System (ADS)

    Puchaty, Ethan M.

    In UAV-based sensor networks, an emerging area of interest is the performance of these networks under cyber attack. This study seeks to evaluate the performance trade-offs from a System-of-Systems (SoS) perspective between various UAV communications architecture options in the context two missions: tracking ballistic missiles and tracking insurgents. An agent-based discrete event simulation is used to model a sensor communication network consisting of UAVs, military communications satellites, ground relay stations, and a mission control center. Network susceptibility to cyber attack is modeled with probabilistic failures and induced data variability, with performance metrics focusing on information availability, latency, and trustworthiness. Results demonstrated that using UAVs as routers increased network availability with a minimal latency penalty and communications satellite networks were best for long distance operations. Redundancy in the number of links between communication nodes helped mitigate cyber-caused link failures and add robustness in cases of induced data variability by an adversary. However, when failures were not independent, redundancy and UAV routing were detrimental in some cases to network performance. Sensitivity studies indicated that long cyber-caused downtimes and increasing failure dependencies resulted in build-ups of failures and caused significant degradations in network performance.

  11. Quaternion-based backstepping control of a fixed-wing unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Oland, E.; Kristiansen, R.

    In this paper the problem of controlling a fixed-wing UAV is studied. With basis in Newton's second law and Euler's moment equation the translational and rotational dynamics is derived. Using the rotational dynamics a quaternion-based backstepping controller is designed which is able to track a trajectory and is shown to be uniformly asymptotically stable. Since a fixed-wing UAV contains six states and only four actuators, the velocity component in yb and zb directions are underactuated. A velocity controller is designed to make the velocity component in the thrust direction go to zero, while the underactuated states are shown to go to their desired values using a line-of-sight guidance scheme.

  12. Optical image hiding based on computational ghost imaging

    NASA Astrophysics Data System (ADS)

    Wang, Le; Zhao, Shengmei; Cheng, Weiwen; Gong, Longyan; Chen, Hanwu

    2016-05-01

    Imaging hiding schemes play important roles in now big data times. They provide copyright protections of digital images. In the paper, we propose a novel image hiding scheme based on computational ghost imaging to have strong robustness and high security. The watermark is encrypted with the configuration of a computational ghost imaging system, and the random speckle patterns compose a secret key. Least significant bit algorithm is adopted to embed the watermark and both the second-order correlation algorithm and the compressed sensing (CS) algorithm are used to extract the watermark. The experimental and simulation results show that the authorized users can get the watermark with the secret key. The watermark image could not be retrieved when the eavesdropping ratio is less than 45% with the second-order correlation algorithm, whereas it is less than 20% with the TVAL3 CS reconstructed algorithm. In addition, the proposed scheme is robust against the 'salt and pepper' noise and image cropping degradations.

  13. Multi-temporal image analysis of historical aerial photographs and recent satellite imagery reveals evolution of water body surface area and polygonal terrain morphology in Kobuk Valley National Park, Alaska

    NASA Astrophysics Data System (ADS)

    Necsoiu, Marius; Dinwiddie, Cynthia L.; Walter, Gary R.; Larsen, Amy; Stothoff, Stuart A.

    2013-06-01

    Multi-temporal image analysis of very-high-resolution historical aerial and recent satellite imagery of the Ahnewetut Wetlands in Kobuk Valley National Park, Alaska, revealed the nature of thaw lake and polygonal terrain evolution over a 54-year period of record comprising two 27-year intervals (1951-1978, 1978-2005). Using active-contouring-based change detection, high-precision orthorectification and co-registration and the normalized difference index, surface area expansion and contraction of 22 shallow water bodies, ranging in size from 0.09 to 179 ha, and the transition of ice-wedge polygons from a low- to a high-centered morphology were quantified. Total surface area decreased by only 0.4% during the first time interval, but decreased by 5.5% during the second time interval. Twelve water bodies (ten lakes and two ponds) were relatively stable with net surface area decreases of ≤10%, including four lakes that gained area during both time intervals, whereas ten water bodies (five lakes and five ponds) had surface area losses in excess of 10%, including two ponds that drained completely. Polygonal terrain remained relatively stable during the first time interval, but transformation of polygons from low- to high-centered was significant during the second time interval.

  14. Flexible Wing Base Micro Aerial Vehicles: Composite Materials for Micro Air Vehicles

    NASA Technical Reports Server (NTRS)

    Ifju, Peter G.; Ettinger, Scott; Jenkins, David; Martinez, Luis

    2002-01-01

    This paper will discuss the development of the University of Florida's Micro Air Vehicle concept. A series of flexible wing based aircraft that possess highly desirable flight characteristics were developed. Since computational methods to accurately model flight at the low Reynolds numbers associated with this scale are still under development, our effort has relied heavily on trial and error. Hence a time efficient method was developed to rapidly produce prototype designs. The airframe and wings are fabricated using a unique process that incorporates carbon fiber composite construction. Prototypes can be fabricated in around five man-hours, allowing many design revisions to be tested in a short period of time. The resulting aircraft are far more durable, yet lighter, than their conventional counterparts. This process allows for thorough testing of each design in order to determine what changes were required on the next prototype. The use of carbon fiber allows for wing flexibility without sacrificing durability. The construction methods developed for this project were the enabling technology that allowed us to implement our designs. The resulting aircraft were the winning entries in the International Micro Air Vehicle Competition for the past two years. Details of the construction method are provided in this paper along with a background on our flexible wing concept.

  15. Perceptual Based Image Fusion with Applications to Hyperspectral Image Data.

    DTIC Science & Technology

    1994-12-01

    spectral bands from the AVIRIS hyperspectral sensor will be evaluated. 1.4 Approach/ Thesis Organization Chapter one described data processing problems...Based Image Fusion with Applications to Hyperspectral Image Data THESIS A o .:or \\Terry Allen Wilson NTS _ Captain, USAF DTIC Tf-, LI Unannou!c<ej LI...Applications to Hyperspectral Image Data THESIS Presented to the Faculty of the Graduate School of Engineering of the Air Force Institute of

  16. 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.

  17. Converting aerial imagery to application maps

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

    NASA Astrophysics Data System (ADS)

    Saur, Günter; Krüger, Wolfgang

    2016-06-01

    Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

  19. One Channel Image Texture Based Interpretation

    NASA Astrophysics Data System (ADS)

    Rodinova, N. V.

    2011-03-01

    In single band and single polarized synthetic aperture radar (SAR) images, in individual channels of polarimetric SAR and multispectral images, in panchromatic images, magnetic resonance imaging, etc., the information is limited to the intensity and texture, and it is very difficult to interpret such images without any a priori information.This paper proposes to use the textural features (contrast, entropy and inverse moment), obtained from grey level co-occurrence matrix (GLCM), to segment one channel images. The interpretation of received texture merged color images are performed based on calculated texture feature values for various surface objects (forest, town, water, and so on) in initial image.SIR-C/X-SAR SLC L-band images, SPOT 4 multispectral and panchromatic images are used for illustration.

  20. The lucky image-motion prediction for simple scene observation based soft-sensor technology

    NASA Astrophysics Data System (ADS)

    Li, Yan; Su, Yun; Hu, Bin

    2015-08-01

    High resolution is important to earth remote sensors, while the vibration of the platforms of the remote sensors is a major factor restricting high resolution imaging. The image-motion prediction and real-time compensation are key technologies to solve this problem. For the reason that the traditional autocorrelation image algorithm cannot meet the demand for the simple scene image stabilization, this paper proposes to utilize soft-sensor technology in image-motion prediction, and focus on the research of algorithm optimization in imaging image-motion prediction. Simulations results indicate that the improving lucky image-motion stabilization algorithm combining the Back Propagation Network (BP NN) and support vector machine (SVM) is the most suitable for the simple scene image stabilization. The relative error of the image-motion prediction based the soft-sensor technology is below 5%, the training computing speed of the mathematical predication model is as fast as the real-time image stabilization in aerial photography.

  1. UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

    NASA Astrophysics Data System (ADS)

    Fernandez Galarreta, J.; Kerle, N.; Gerke, M.

    2014-09-01

    Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

  2. UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

    NASA Astrophysics Data System (ADS)

    Fernandez Galarreta, J.; Kerle, N.; Gerke, M.

    2015-06-01

    Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  5. Two-Step System Identification and Primitive-Based Motion Planning for Control of Small Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Grymin, David J.

    This dissertation addresses motion planning, modeling, and feedback control for autonomous vehicle systems. A hierarchical approach for motion planning and control of nonlinear systems operating in obstacle environments is presented. To reduce computation time during the motion planning process, dynamically feasible trajectories are generated in real-time through concatenation of pre-specified motion primitives. The motion planning task is posed as a search over a directed graph, and the applicability of informed graph search techniques is investigated. Specifically, a locally greedy algorithm with effective backtracking ability is developed and compared to weighted A* search. The greedy algorithm shows an advantage with respect to solution cost and computation time when larger motion primitive libraries that do not operate on a regular state lattice are utilized. Linearization of the nonlinear system equations about the motion primitive library results in a hybrid linear time-varying model, and an optimal control algorithm using the l 2-induced norm as the performance measure is applied to ensure that the system tracks the desired trajectory. The ability of the resulting controller to closely track the trajectory obtained from the motion planner, despite various disturbances and uncertainties, is demonstrated through simulation. Additionally, an approach for obtaining dynamically feasible reference trajectories and feedback controllers for a small unmanned aerial vehicle (UAV) based on an aerodynamic model derived from flight tests is presented. The modeling approach utilizes the two step method (TSM) with stepwise multiple regression to determine relevant explanatory terms for the aerodynamic models. Dynamically feasible trajectories are then obtained through the solution of an optimal control problem using pseudospectral optimal control software. Discretetime feedback controllers are then obtained to regulate the vehicle along the desired reference trajectory

  6. Obtaining biophysical measurements of woody vegetation from high resolution digital aerial photography in tropical and arid environments: Northern Territory, Australia

    NASA Astrophysics Data System (ADS)

    Staben, G. W.; Lucieer, A.; Evans, K. G.; Scarth, P.; Cook, G. D.

    2016-10-01

    Biophysical parameters obtained from woody vegetation are commonly measured using field based techniques which require significant investment in resources. Quantitative measurements of woody vegetation provide important information for ecological studies investigating landscape change. The fine spatial resolution of aerial photography enables identification of features such as trees and shrubs. Improvements in spatial and spectral resolution of digital aerial photographic sensors have increased the possibility of using these data in quantitative remote sensing. Obtaining biophysical measurements from aerial photography has the potential to enable it to be used as a surrogate for the collection of field data. In this study quantitative measurements obtained from digital aerial photography captured at ground sampling distance (GSD) of 15 cm (n = 50) and 30 cm (n = 52) were compared to woody biophysical parameters measured from 1 ha field plots. Supervised classification of the aerial photography using object based image analysis was used to quantify woody and non-woody vegetation components in the imagery. There was a high correlation (r ≥ 0.92) between all field measured woody canopy parameters and aerial derived green woody cover measurements, however only foliage projective cover (FPC) was found to be statistically significant (paired t-test; α = 0.01). There was no significant difference between measurements derived from imagery captured at either GSD of 15 cm and 30 cm over the same field site (n = 20). Live stand basal area (SBA) (m2 ha-1) was predicted from the aerial photographs by applying an allometric equation developed between field-measured live SBA and woody FPC. The results show that there was very little difference between live SBA predicted from FPC measured in the field or from aerial photography. The results of this study show that accurate woody biophysical parameters can be obtained from aerial photography from a range of woody vegetation

  7. Pc-Based Floating Point Imaging Workstation

    NASA Astrophysics Data System (ADS)

    Guzak, Chris J.; Pier, Richard M.; Chinn, Patty; Kim, Yongmin

    1989-07-01

    The medical, military, scientific and industrial communities have come to rely on imaging and computer graphics for solutions to many types of problems. Systems based on imaging technology are used to acquire and process images, and analyze and extract data from images that would otherwise be of little use. Images can be transformed and enhanced to reveal detail and meaning that would go undetected without imaging techniques. The success of imaging has increased the demand for faster and less expensive imaging systems and as these systems become available, more and more applications are discovered and more demands are made. From the designer's perspective the challenge to meet these demands forces him to attack the problem of imaging from a different perspective. The computing demands of imaging algorithms must be balanced against the desire for affordability and flexibility. Systems must be flexible and easy to use, ready for current applications but at the same time anticipating new, unthought of uses. Here at the University of Washington Image Processing Systems Lab (IPSL) we are focusing our attention on imaging and graphics systems that implement imaging algorithms for use in an interactive environment. We have developed a PC-based imaging workstation with the goal to provide powerful and flexible, floating point processing capabilities, along with graphics functions in an affordable package suitable for diverse environments and many applications.

  8. Motion based X-ray imaging modality.

    PubMed

    Szigeti, Krisztián; Máthé, Domokos; Osváth, Szabolcs

    2014-10-01

    A new X-ray imaging method (patent pending) was developed to visualize function-related motion information. We modify existing X-ray imaging methods to provide four images without increasing the necessary measurement time or radiation dose. The most important of these images is a new "kinetic" image that represents motions inside the object or living body. The motion-based contrast of the kinetic image can help visualize details that were not accessible before. The broad range of the movements and high sensitivity of the method are illustrated by imaging the mechanics of a working clock and the chest of a living African clawed frog (Xenopus laevis). The heart, valves, aorta, and lungs of the frog are clearly visualized in spite of the low soft tissue contrast of the animal. The new technology also reconstructs a "static" image similar to the existing conventional X-ray image. The static image shows practically the same information as the conventional image. The new technology presents two more images which show the point-wise errors of the static and kinetic images. This technique gives a better estimation of errors than present methods because it is based entirely on measured data. The new technology could be used in imaging cardiopulmonary movements, nondestructive testing, or port security screening.

  9. Stereo imaging based particle velocimeter

    NASA Technical Reports Server (NTRS)

    Batur, Celal

    1994-01-01

    Three dimensional coordinates of an object are determined from it's two dimensional images for a class of points on the object. Two dimensional images are first filtered by a Laplacian of Gaussian (LOG) filter in order to detect a set of feature points on the object. The feature points on the left and the right images are then matched using a Hopfield type optimization network. The performance index of the Hopfield network contains both local and global properties of the images. Parallel computing in stereo matching can be achieved by the proposed methodology.

  10. Cooperative Surveillance and Pursuit Using Unmanned Aerial Vehicles and Unattended Ground Sensors

    PubMed Central

    Las Fargeas, Jonathan; Kabamba, Pierre; Girard, Anouck

    2015-01-01

    This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors placed on roads to detect and image potential intruders. The problem is motivated by persistent intelligence, surveillance, reconnaissance and base defense missions. The problem is formulated and shown to be intractable. A heuristic algorithm to coordinate the unmanned aerial vehicles during surveillance and pursuit is presented. Revisit deadlines are used to schedule the vehicles' paths nominally. The algorithm uses detections from the sensors to predict intruders' locations and selects the vehicles' paths by minimizing a linear combination of missed deadlines and the probability of not intercepting intruders. An analysis of the algorithm's completeness and complexity is then provided. The effectiveness of the heuristic is illustrated through simulations in a variety of scenarios. PMID:25591168

  11. Cooperative surveillance and pursuit using unmanned aerial vehicles and unattended ground sensors.

    PubMed

    Las Fargeas, Jonathan; Kabamba, Pierre; Girard, Anouck

    2015-01-13

    This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors placed on roads to detect and image potential intruders. The problem is motivated by persistent intelligence, surveillance, reconnaissance and base defense missions. The problem is formulated and shown to be intractable. A heuristic algorithm to coordinate the unmanned aerial vehicles during surveillance and pursuit is presented. Revisit deadlines are used to schedule the vehicles' paths nominally. The algorithm uses detections from the sensors to predict intruders' locations and selects the vehicles' paths by minimizing a linear combination of missed deadlines and the probability of not intercepting intruders. An analysis of the algorithm's completeness and complexity is then provided. The effectiveness of the heuristic is illustrated through simulations in a variety of scenarios.

  12. Developing stereo image based robot control system

    SciTech Connect

    Suprijadi,; Pambudi, I. R.; Woran, M.; Naa, C. F; Srigutomo, W.

    2015-04-16

    Application of image processing is developed in various field and purposes. In the last decade, image based system increase rapidly with the increasing of hardware and microprocessor performance. Many fields of science and technology were used this methods especially in medicine and instrumentation. New technique on stereovision to give a 3-dimension image or movie is very interesting, but not many applications in control system. Stereo image has pixel disparity information that is not existed in single image. In this research, we proposed a new method in wheel robot control system using stereovision. The result shows robot automatically moves based on stereovision captures.

  13. Developing stereo image based robot control system

    NASA Astrophysics Data System (ADS)

    Suprijadi, Pambudi, I. R.; Woran, M.; Naa, C. F.; Srigutomo, W.

    2015-04-01

    Application of image processing is developed in various field and purposes. In the last decade, image based system increase rapidly with the increasing of hardware and microprocessor performance. Many fields of science and technology were used this methods especially in medicine and instrumentation. New technique on stereovision to give a 3-dimension image or movie is very interesting, but not many applications in control system. Stereo image has pixel disparity information that is not existed in single image. In this research, we proposed a new method in wheel robot control system using stereovision. The result shows robot automatically moves based on stereovision captures.

  14. Computer-Aided Content-Based Cueing of Remotely Sensed Images with the Image Content Engine (ICE)

    SciTech Connect

    Weinert, G F; Brase, J M; Paglieroni, D W

    2004-06-22

    Human analysts are often unable to meet time constraints on analysis and interpretation of large volumes of remotely sensed imagery. To address this problem, the Image Content Engine (ICE) system currently under development is organized into an off-line component for automated extraction of image features followed by user-interactive components for content detection and content-based query processing. The extracted features are vectors that represent attributes of three entities, namely image tiles, image regions and shapes, or suspected matches to models of objects. ICE allows users to interactively specify decision thresholds so that content (consisting of entities whose features satisfy decision criteria) can be detected. ICE presents detected content to users as a prioritized series of thumbnail images. Users can either accept the detection results or specify a new set of decision thresholds. Once accepted, ICE stores the detected content in database tables and semantic graphs. Users can interactively query the tables and graphs for locations at which prescribed relationships between detected content exist. New queries can be submitted repeatedly until a satisfactory series of prioritized thumbnail image cues is produced. Examples are provided to demonstrate how ICE can be used to assist users in quickly finding prescribed collections of entities (both natural and man-made) in a set of large USGS aerial photos retrieved from TerraserverUSA.

  15. Optically-induced-potential-based image encryption.

    PubMed

    Chen, Bing-Chu; Wang, He-Zhou

    2011-11-07

    We present a technique of nonlinear image encryption by use of virtual optics. The image to be encrypted is superposed on a random intensity image. And this superposed image propagates through a nonlinear medium and a 4-f system with single phase key. The image is encrypted to a stationary white noise. The decryption process is sensitive to the parameters of the encryption system and the phase key in 4-f system. This sensitivity makes attackers hard to access the phase key. In nonlinear medium, optically-induced potentials, which depend on intensity of optical wave, make the superposition principle frustrated. This nonlinearity based on optically induced potentials highly improves the secrecy level of image encryption. Resistance against attacks based on the phase retrieval technique proves that it has the high secrecy level. This nonlinear image encryption based on optically induced potentials is proposed and demonstrated for the first time.

  16. Aerial video mosaicking using binary feature tracking

    NASA Astrophysics Data System (ADS)

    Minnehan, Breton; Savakis, Andreas

    2015-05-01

    Unmanned Aerial Vehicles are becoming an increasingly attractive platform for many applications, as their cost decreases and their capabilities increase. Creating detailed maps from aerial data requires fast and accurate video mosaicking methods. Traditional mosaicking techniques rely on inter-frame homography estimations that are cascaded through the video sequence. Computationally expensive keypoint matching algorithms are often used to determine the correspondence of keypoints between frames. This paper presents a video mosaicking method that uses an object tracking approach for matching keypoints between frames to improve both efficiency and robustness. The proposed tracking method matches local binary descriptors between frames and leverages the spatial locality of the keypoints to simplify the matching process. Our method is robust to cascaded errors by determining the homography between each frame and the ground plane rather than the prior frame. The frame-to-ground homography is calculated based on the relationship of each point's image coordinates and its estimated location on the ground plane. Robustness to moving objects is integrated into the homography estimation step through detecting anomalies in the motion of keypoints and eliminating the influence of outliers. The resulting mosaics are of high accuracy and can be computed in real time.

  17. Quality assessment of digitized aerial photographs

    NASA Astrophysics Data System (ADS)

    Koelbl, O.

    1998-09-01

    Manufacturer of photogrammetric instruments have developed specific scanners for aerial photographs, in parallel to printing industry. Main objective of this specific scanners is to guarantee a high geometric precision of plus or minus 0.001 to 0.002 mm for a standard format of original film documents of 23 X 23 cm and to scope with the high image resolution of the original images. Within a study of OEEPE (European Organisation for Experimental Photogrammetric Research) the most important photogrammetric scanners used in practice have been tested. Standard procedures are in development to analyze the dynamic range of the scanners, the image noise, the image sharpness and the color fidelity. Practical all photogrammetric scanners are based on CCD technology. The article presents the techniques applied for the testing of the scanners concerning the determination of the MTF of the scanners, the image noise, the dynamic range and the color fidelity and gives typical results for various scanners. The scanners tested are manufactured by Intergraph, Zeiss, Agfa, Helava and Wehrli.

  18. Dental archives based on images

    NASA Astrophysics Data System (ADS)

    Dostalova, Tatjana; Smutny, Vladimir

    1997-05-01

    This paper describes the Orthoscope, an equipment for acquisition, processing, and archiving of images of patients mouth or skin. The equipment can capture and process images of single tooth, group of teeth or the whole dental arc. A dentist can easily observe the situation in mouth, demonstrate intended plan of treatment to patient and document its results. A dermatologist can evaluate treatment progress. Unlike other methods, our device shows geometrically undistorted calibrated image.The presented equipment is intended for daily practice. The image processing module is connected to an insurance office system and medical archives. This eliminates time consuming literal description of the patient dental/dermatological status. The images can be used later checking of the diagnosis and treatment.

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

    DTIC Science & Technology

    1983-09-01

    trary file names to be passed to the processing routines. An intelligent sys- .0" tem for constructing default file names could also be helpful. 17 P...eft enc. Vol. PAMT-I. No. 2, pp. 173-184, April 1979. [HaralickO0] R.M. Haralick. J.C. Mohammed , and S.W. Zucker. "Compatibilities and the Fixed PoLnts

  20. Research on autofocusing method with automatic calibration for aerial camera based on imaging resolution

    NASA Astrophysics Data System (ADS)

    Zhao, Yu-liang; Zhao, Hong-qiang; Li, Shu-jun; Zhang, Yu-ye

    2014-09-01

    Air materiel depot is a warehouse which store consumed all the parts and equipment vault of the plane. In order to ensure the various aviation equipment integrity of the backup piece rate, the inside temperature of depot must be controlled within a certain range. Therefore, the depot must be equipped a self-contained temperature real-time monitoring system. This paper presents a distributed temperature sensing alarm system to apply to real-time measure spatial distribution of temperature field. In order to eliminate influence to the scattering strength from the light source instability and the fiber bending splice loss and to improve temperature measurement accuracy, the system design used dual-channel dual-wavelength comparison method which make Anti-Stokes as signal channel and Stokes as a reference channel to collect signals of two channel respectively and detect the ratio of the two channels' signals. The light of LD directional coupling to the sensing optical fiber in the temperature field to test, domain reflect light from the sensing optical fiber directional coupling to receive channel again, Rayleigh domain reflect light is filtered after optical filter, the Anti-Stokes and Stokes are both taken out, converted and magnified, the two signals is digitalized by A/D Converter, and written to the storage machine , which linear cumulative to the content of the storage unit, The distributed measurement of the temperature field to test is finished. The collected 2900 measuring points real-time on 2km of optical fiber. The spatial resolution of the system was 0.7m, measurement range was -20-370 °C, and measurement error was +/- 2 °C. All index of the system achieved the desired objective. To get an accurate temperature field spatial distribution and the information of temporal variation, the system enabled real-time temperature of aviation depot monitoring and early warning. As a new sensing technology, the distributed fiber optic sensor has the functions of self- calibration, self-calibration and self-test. Even when the fiber damaged, the distributed fiber optic sensor also can continue work and can detect the breakpoint location. The system can be applied to many engineering fields and has significant application value.

  1. Evaluation of the National Archives program to convert nitrate aerial photographs of the United States to a stable-base safety film.

    USGS Publications Warehouse

    Williams, R.S.; Lyons, T.R.; Ferrigno, J.G.; Quinn, M.C.

    1984-01-01

    Discusses the programme on reproducing the 1930's and early 1940's nitrate aerial photographs of large areas of the US onto stable-base safety film, and the proceedings of a February 1981 meeting at the National Archives and Records Service, General Services Administration, which discussed the programme and inspected the results of the new full-size (1:1), roll-to-roll conversions. The latter process was found to be acceptable to all current and envisaged future users of this photography.-R.House

  2. Three-Dimensional Imaging Methods Based on Multiview Images

    NASA Astrophysics Data System (ADS)

    Son, Jung-Young; Javidi, Bahram

    2005-09-01

    Three-dimensional imaging methods, based on parallaxes as their depth cues, can be classified into the stereoscopic providing binocular parallax only, and multiview providing both binocular and motion parallaxes. In these methods, the parallaxes are provided by creating a viewing zone with use of either a special optical eyeglasses or a special optical plate as their viewing zone-forming optics. For the stereoscopic image generations, either the eyeglasses or the optical plate can be employed, but for the multiview the optical plate or the eyeglasses with a tracking device. The stereoscopic image pair and the multiview images are presented either simultaneously or as a time sequence with use of projectors or display panels. For the case of multiview images,they can also be presented as two images at a time according to the viewer's movements. The presence of the viewing zone-forming optics often causes undesirable problems, such as appearance of moiré fringes, image quality deterioration,depth reversion, limiting viewing regions, low image brightness, image burring,and inconveniences of wearing.

  3. 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.

  4. Image2000: A Free, Innovative, Java Based Imaging Package

    NASA Technical Reports Server (NTRS)

    Pell, Nicholas; Wheeler, Phil; Cornwell, Carl; Matusow, David; Obenschain, Arthur F. (Technical Monitor)

    2001-01-01

    The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center's (GSFC) Scientific and Educational Endeavors (SEE) and the Center for Image Processing in Education (CIPE) use satellite image processing as part of their science lessons developed for students and educators. The image processing products that they use, as part of these lessons, no longer fulfill the needs of SEE and CIPE because these products are either dependent on a particular computing platform, hard to customize and extend, or do not have enough functionality. SEE and CIPE began looking for what they considered the "perfect" image processing tool that was platform independent, rich in functionality and could easily be extended and customized for their purposes. At the request of SEE, NASA's GSFC, code 588 the Advanced Architectures and Automation Branch developed a powerful new Java based image processing endeavors.

  5. Web-based medical image archive system

    NASA Astrophysics Data System (ADS)

    Suh, Edward B.; Warach, Steven; Cheung, Huey; Wang, Shaohua A.; Tangiral, Phanidral; Luby, Marie; Martino, Robert L.

    2002-05-01

    This paper presents a Web-based medical image archive system in three-tier, client-server architecture for the storage and retrieval of medical image data, as well as patient information and clinical data. The Web-based medical image archive system was designed to meet the need of the National Institute of Neurological Disorders and Stroke for a central image repository to address questions of stroke pathophysiology and imaging biomarkers in stroke clinical trials by analyzing images obtained from a large number of clinical trials conducted by government, academic and pharmaceutical industry researchers. In the database management-tier, we designed the image storage hierarchy to accommodate large binary image data files that the database software can access in parallel. In the middle-tier, a commercial Enterprise Java Bean server and secure Web server manages user access to the image database system. User-friendly Web-interfaces and applet tools are provided in the client-tier for easy access to the image archive system over the Internet. Benchmark test results show that our three-tier image archive system yields fast system response time for uploading, downloading, and querying the image database.

  6. 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

  7. 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…

  8. Blind forensics in medical imaging based on Tchebichef image moments.

    PubMed

    Huang, H; Coatrieux, G; Shu, H Z; Luo, L M; Roux, Ch

    2011-01-01

    In this paper, we present a blind forensic approach for the detection of global image modifications like filtering, lossy compression, scaling and so on. It is based on a new set of image features we proposed, called Histogram statistics of Reorganized Block-based Tchebichef moments (HRBT) features, and which are used as input of a set of classifiers we learned to discriminate tampered images from original ones. In this article, we compare the performances of our features with others proposed schemes from the literature in application to different medical image modalities (MRI, X-Ray …). Experimental results show that our HRBT features perform well and in some cases better than other features.

  9. A temporal and ecological analysis of the Huntington Beach Wetlands through an unmanned aerial system remote sensing perspective

    NASA Astrophysics Data System (ADS)

    Rafiq, Talha

    Wetland monitoring and preservation efforts have the potential to be enhanced with advanced remote sensing acquisition and digital image analysis approaches. Progress in the development and utilization of Unmanned Aerial Systems (UAS) and Unmanned Aerial Vehicles (UAV) as remote sensing platforms has offered significant spatial and temporal advantages over traditional aerial and orbital remote sensing platforms. Photogrammetric approaches to generate high spatial resolution orthophotos of UAV acquired imagery along with the UAV's low-cost and temporally flexible characteristics are explored. A comparative analysis of different spectral based land cover maps derived from imagery captured using UAV, satellite, and airplane platforms provide an assessment of the Huntington Beach Wetlands. This research presents a UAS remote sensing methodology encompassing data collection, image processing, and analysis in constructing spectral based land cover maps to augment the efforts of the Huntington Beach Wetlands Conservancy by assessing ecological and temporal changes at the Huntington Beach Wetlands.

  10. Novel Image Encryption based on Quantum Walks

    PubMed Central

    Yang, Yu-Guang; Pan, Qing-Xiang; Sun, Si-Jia; Xu, Peng

    2015-01-01

    Quantum computation has achieved a tremendous success during the last decades. In this paper, we investigate the potential application of a famous quantum computation model, i.e., quantum walks (QW) in image encryption. It is found that QW can serve as an excellent key generator thanks to its inherent nonlinear chaotic dynamic behavior. Furthermore, we construct a novel QW-based image encryption algorithm. Simulations and performance comparisons show that the proposal is secure enough for image encryption and outperforms prior works. It also opens the door towards introducing quantum computation into image encryption and promotes the convergence between quantum computation and image processing. PMID:25586889

  11. Novel image encryption based on quantum walks.

    PubMed

    Yang, Yu-Guang; Pan, Qing-Xiang; Sun, Si-Jia; Xu, Peng

    2015-01-14

    Quantum computation has achieved a tremendous success during the last decades. In this paper, we investigate the potential application of a famous quantum computation model, i.e., quantum walks (QW) in image encryption. It is found that QW can serve as an excellent key generator thanks to its inherent nonlinear chaotic dynamic behavior. Furthermore, we construct a novel QW-based image encryption algorithm. Simulations and performance comparisons show that the proposal is secure enough for image encryption and outperforms prior works. It also opens the door towards introducing quantum computation into image encryption and promotes the convergence between quantum computation and image processing.

  12. Novel Image Encryption based on Quantum Walks

    NASA Astrophysics Data System (ADS)

    Yang, Yu-Guang; Pan, Qing-Xiang; Sun, Si-Jia; Xu, Peng

    2015-01-01

    Quantum computation has achieved a tremendous success during the last decades. In this paper, we investigate the potential application of a famous quantum computation model, i.e., quantum walks (QW) in image encryption. It is found that QW can serve as an excellent key generator thanks to its inherent nonlinear chaotic dynamic behavior. Furthermore, we construct a novel QW-based image encryption algorithm. Simulations and performance comparisons show that the proposal is secure enough for image encryption and outperforms prior works. It also opens the door towards introducing quantum computation into image encryption and promotes the convergence between quantum computation and image processing.

  13. Scalable still image coding based on wavelet

    NASA Astrophysics Data System (ADS)

    Yan, Yang; Zhang, Zhengbing

    2005-02-01

    The scalable image coding is an important objective of the future image coding technologies. In this paper, we present a kind of scalable image coding scheme based on wavelet transform. This method uses the famous EZW (Embedded Zero tree Wavelet) algorithm; we give a high-quality encoding to the ROI (region of interest) of the original image and a rough encoding to the rest. This method is applied well in limited memory space condition, and we encode the region of background according to the memory capacity. In this way, we can store the encoded image in limited memory space easily without losing its main information. Simulation results show it is effective.

  14. Retinal image quality assessment based on image clarity and content

    NASA Astrophysics Data System (ADS)

    Abdel-Hamid, Lamiaa; El-Rafei, Ahmed; El-Ramly, Salwa; Michelson, Georg; Hornegger, Joachim

    2016-09-01

    Retinal image quality assessment (RIQA) is an essential step in automated screening systems to avoid misdiagnosis caused by processing poor quality retinal images. A no-reference transform-based RIQA algorithm is introduced that assesses images based on five clarity and content quality issues: sharpness, illumination, homogeneity, field definition, and content. Transform-based RIQA algorithms have the advantage of considering retinal structures while being computationally inexpensive. Wavelet-based features are proposed to evaluate the sharpness and overall illumination of the images. A retinal saturation channel is designed and used along with wavelet-based features for homogeneity assessment. The presented sharpness and illumination features are utilized to assure adequate field definition, whereas color information is used to exclude nonretinal images. Several publicly available datasets of varying quality grades are utilized to evaluate the feature sets resulting in area under the receiver operating characteristic curve above 0.99 for each of the individual feature sets. The overall quality is assessed by a classifier that uses the collective features as an input vector. The classification results show superior performance of the algorithm in comparison to other methods from literature. Moreover, the algorithm addresses efficiently and comprehensively various quality issues and is suitable for automatic screening systems.

  15. Simulating cardiac ultrasound image based on MR diffusion tensor imaging

    PubMed Central

    Qin, Xulei; Wang, Silun; Shen, Ming; Lu, Guolan; Zhang, Xiaodong; Wagner, Mary B.; Fei, Baowei

    2015-01-01

    Purpose: Cardiac ultrasound simulation can have important applications in the design of ultrasound systems, understanding the interaction effect between ultrasound and tissue and setting the ground truth for validating quantification methods. Current ultrasound simulation methods fail to simulate the myocardial intensity anisotropies. New simulation methods are needed in order to simulate realistic ultrasound images of the heart. Methods: The proposed cardiac ultrasound image simulation method is based on diffusion tensor imaging (DTI) data of the heart. The method utilizes both the cardiac geometry and the fiber orientation information to simulate the anisotropic intensities in B-mode ultrasound images. Before the simulation procedure, the geometry and fiber orientations of the heart are obtained from high-resolution structural MRI and DTI data, respectively. The simulation includes two important steps. First, the backscatter coefficients of the point scatterers inside the myocardium are processed according to the fiber orientations using an anisotropic model. Second, the cardiac ultrasound images are simulated with anisotropic myocardial intensities. The proposed method was also compared with two other nonanisotropic intensity methods using 50 B-mode ultrasound image volumes of five different rat hearts. The simulated images were also compared with the ultrasound images of a diseased rat heart in vivo. A new segmental evaluation method is proposed to validate the simulation results. The average relative errors (AREs) of five parameters, i.e., mean intensity, Rayleigh distribution parameter σ, and first, second, and third quartiles, were utilized as the evaluation metrics. The simulated images were quantitatively compared with real ultrasound images in both ex vivo and in vivo experiments. Results: The proposed ultrasound image simulation method can realistically simulate cardiac ultrasound images of the heart using high-resolution MR-DTI data. The AREs of their

  16. GPU-based rectification of high-resolution remote sensing stereo images

    NASA Astrophysics Data System (ADS)

    Lukač, Niko; Žalik, Borut

    2014-10-01

    One of the major challenges in the topographic mapping and fast generation of digital terrain or surface models from stereo optical aerial or satellite imagery is the stereo rectification preprocessing step. The general case is the use of extrinsic and intrinsic parameters from each calibrated camera, in order to establish epipolar geometry. Stereo rectification consists of geometric transformation and image sub-pixel resampling. Such a task is computationally demanding when dealing with high-resolution optical imagery. This presents an increasingly evident problem as the remote sensing technologies are becoming more accurate, causing even higher computational demands. This paper proposes a novel method for fast rectification of stereo images pairs to epipolar geometry by using General Purpose computing on Graphics Processing Units (GPGPU). The method is capable of resampling large high-resolution imagery on-the-fly, due to efficient out-of-core processing. In the experiments a runtime comparison was made between the proposed GPU-based and multi-core CPU methods over a dataset consisting of 420 stereo aerial images, where the proposed method achieved a significant speedup.

  17. 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.

  18. Reliable aerial thermography for energy conservation

    NASA Technical Reports Server (NTRS)

    Jack, J. R.; Bowman, R. L.

    1981-01-01

    A method for energy conservation, the aerial thermography survey, is discussed. It locates sources of energy losses and wasteful energy management practices. An operational map is presented for clear sky conditions. The map outlines the key environmental conditions conductive to obtaining reliable aerial thermography. The map is developed from defined visual and heat loss discrimination criteria which are quantized based on flat roof heat transfer calculations.

  19. Image coding compression based on DCT

    NASA Astrophysics Data System (ADS)

    Feng, Fei; Liu, Peixue; Jiang, Baohua

    2012-04-01

    With the development of computer science and communications, the digital image processing develops more and more fast. High quality images are loved by people, but it will waste more stored space in our computer and it will waste more bandwidth when it is transferred by Internet. Therefore, it's necessary to have an study on technology of image compression. At present, many algorithms about image compression is applied to network and the image compression standard is established. In this dissertation, some analysis on DCT will be written. Firstly, the principle of DCT will be shown. It's necessary to realize image compression, because of the widely using about this technology; Secondly, we will have a deep understanding of DCT by the using of Matlab, the process of image compression based on DCT, and the analysis on Huffman coding; Thirdly, image compression based on DCT will be shown by using Matlab and we can have an analysis on the quality of the picture compressed. It is true that DCT is not the only algorithm to realize image compression. I am sure there will be more algorithms to make the image compressed have a high quality. I believe the technology about image compression will be widely used in the network or communications in the future.

  20. Thermal light ghost imaging based on morphology

    NASA Astrophysics Data System (ADS)

    Chen, Zhipeng; Shi, Jianhong; Zeng, Guihua

    2016-12-01

    The quality of thermal light ghost imaging could be degraded by undersampling noise. This kind of noise is generated because of finite sampling, which could reduce the signal-to-noise ratio (SNR) of ghost imaging and submerge object information. In order to reduce the undersampling noise, we propose a thermal light ghost imaging scheme based on the morphology (GIM). In this scheme, the average size of the undersampling noise can be obtained by computing the second-order correlation function of the ghost imaging system. According to the average size of the undersampling noise, the corresponding structure element can be designed and used in the morphological filter; then, the GIM reconstructed image can be obtained. The experiment results show that the peak signal-to-noise ratio of the GIM reconstructed image can increased by 80% than that of conventional ghost imaging for the same number of measurements.

  1. Adaptive SVD-Based Digital Image Watermarking

    NASA Astrophysics Data System (ADS)

    Shirvanian, Maliheh; Torkamani Azar, Farah

    Digital data utilization along with the increase popularity of the Internet has facilitated information sharing and distribution. However, such applications have also raised concern about copyright issues and unauthorized modification and distribution of digital data. Digital watermarking techniques which are proposed to solve these problems hide some information in digital media and extract it whenever needed to indicate the data owner. In this paper a new method of image watermarking based on singular value decomposition (SVD) of images is proposed which considers human visual system prior to embedding watermark by segmenting the original image into several blocks of different sizes, with more density in the edges of the image. In this way the original image quality is preserved in the watermarked image. Additional advantages of the proposed technique are large capacity of watermark embedding and robustness of the method against different types of image manipulation techniques.

  2. a New Framework for Object-Based Image Analysis Based on Segmentation Scale Space and Random Forest Classifier

    NASA Astrophysics Data System (ADS)

    Hadavand, A.; Saadatseresht, M.; Homayouni, S.

    2015-12-01

    In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses. Due to the strong dependency of segmentation results to the scale parameter, choosing the best value for this parameter, for each class, becomes a main challenge in object-based image analysis. We propose a new framework which employs pixel-based land cover map to estimate the initial scale dedicated to each class. These scales are used to build segmentation scale space (SSS), a hierarchy of image objects. Optimization of SSS, respect to NDVI and DSM values in each super object is used to get the best scale in local regions of image scene. Optimized SSS segmentations are finally classified to produce the final land cover map. Very high resolution aerial image and digital surface model provided by ISPRS 2D semantic labelling dataset is used in our experiments. The result of our proposed method is comparable to those of ESP tool, a well-known method to estimate the scale of segmentation, and marginally improved the overall accuracy of classification from 79% to 80%.

  3. Use of Remote Imagery and Object-based Image Methods to Count Plants in an Open-field Container Nursery

    NASA Astrophysics Data System (ADS)

    Leiva Lopez, Josue Nahun

    In general, the nursery industry lacks an automated inventory control system. Object-based image analysis (OBIA) software and aerial images could be used to count plants in nurseries. The objectives of this research were: 1) to evaluate the effect of an unmanned aerial vehicle (UAV) flight altitude and plant canopy separation of container-grown plants on count accuracy using aerial images and 2) to evaluate the effect of plant canopy shape, presence of flowers, and plant status (living and dead) on counting accuracy of container-grown plants using remote sensing images. Images were analyzed using Feature AnalystRTM (FA) and an algorithm trained using MATLABRTM. Total count error, false positives and unidentified plants were recorded from output images using FA; only total count error was reported for the MATLAB algorithm. For objective 1, images were taken at 6, 12 and 22 m above the ground using a UAV. Plants were placed on black fabric and gravel, and spaced as follows: 5 cm between canopy edges, canopy edges touching, and 5 cm of canopy edge overlap. In general, when both methods were considered, total count error was smaller [ranging from -5 (undercount) to 4 (over count)] when plants were fully separated with the exception of images taken at 22 m. FA showed a smaller total count error (-2) than MATLAB (-5) when plants were placed on black fabric than those placed on gravel. For objective 2, the plan was to continue using the UAV, however, due to the unexpected disruption of the GPS-based navigation by heightened solar flare activity in 2013, a boom lift that could provide images on a more reliable basis was used. When images obtained using a boom lift were analyzed using FA there was no difference between variables measured when an algorithm trained with an image displaying regular or irregular plant canopy shape was applied to images displaying both plant canopy shapes even though the canopy shape of 'Sea Green' juniper is less compact than 'Plumosa Compacta

  4. Computational polarization difference underwater imaging based on image fusion

    NASA Astrophysics Data System (ADS)

    Han, Hongwei; Zhang, Xiaohui; Guan, Feng

    2016-01-01

    Polarization difference imaging can improve the quality of images acquired underwater, whether the background and veiling light are unpolarized or partial polarized. Computational polarization difference imaging technique which replaces the mechanical rotation of polarization analyzer and shortens the time spent to select the optimum orthogonal ǁ and ⊥axes is the improvement of the conventional PDI. But it originally gets the output image by setting the weight coefficient manually to an identical constant for all pixels. In this paper, a kind of algorithm is proposed to combine the Q and U parameters of the Stokes vector through pixel-level image fusion theory based on non-subsample contourlet transform. The experimental system built by the green LED array with polarizer to illuminate a piece of flat target merged in water and the CCD with polarization analyzer to obtain target image under different angle is used to verify the effect of the proposed algorithm. The results showed that the output processed by our algorithm could show more details of the flat target and had higher contrast compared to original computational polarization difference imaging.

  5. Light Field Imaging Based Accurate Image Specular Highlight Removal

    PubMed Central

    Wang, Haoqian; Xu, Chenxue; Wang, Xingzheng; Zhang, Yongbing; Peng, Bo

    2016-01-01

    Specular reflection removal is indispensable to many computer vision tasks. However, most existing methods fail or degrade in complex real scenarios for their individual drawbacks. Benefiting from the light field imaging technology, this paper proposes a novel and accurate approach to remove specularity and improve image quality. We first capture images with specularity by the light field camera (Lytro ILLUM). After accurately estimating the image depth, a simple and concise threshold strategy is adopted to cluster the specular pixels into “unsaturated” and “saturated” category. Finally, a color variance analysis of multiple views and a local color refinement are individually conducted on the two categories to recover diffuse color information. Experimental evaluation by comparison with existed methods based on our light field dataset together with Stanford light field archive verifies the effectiveness of our proposed algorithm. PMID:27253083

  6. Contourlet based image watermarking using QR decomposition

    NASA Astrophysics Data System (ADS)

    Mitra, Priyanka; Gunjan, Reena; Gaur, M. S.

    2013-01-01

    The paper presents an image watermarking algorithm based on Contourlet Transform (CT) and QR factorization method. Contourlet Transform is used to transform both the cover and watermark image into subbands. The watermarking is applied to the Contourlet Transform as the human visual system is comparatively less sensitive to edges of the image. The low frequency coefficients of an image contain the highest energy. Thus the lowest frequency coefficients of the contourlet transformed original and watermark image are selected for watermarking. The selected coefficients are then decomposed using QR factorization method. The QR factorized coefficients of watermark image is embedded into the QR factorized original image values. Inverse QR and inverse CT is then applied on the watermark embedded coefficients of image to obtain the watermarked image. Experimental results show that the proposed algorithm is a better technique as compared to other watermarking schemes based on Contourlet Transform. The proposed watermarking scheme is imperceptible and robust against image processing attacks such as Gaussian noise, scaling, compression, salt and pepper noise.

  7. Landscape-scale geospatial research utilizing low elevation aerial photography generated with commercial unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Lipo, C. P.; Lee, C.; Wechsler, S.

    2012-12-01

    With the ability to generate on demand high-resolution imagery across landscapes, unmanned aerial systems (UAS) are increasingly become the tools of choice for geospatial researchers. At CSULB, we have implemented a number of aerial systems in order to conduct archaeological, vegetation and terrain analyses. The platforms include the commercially available X100 by Gatewing, a hobby based aircraft, kites, and tethered blimps. From our experience, each platform has advantages and disadvantages n applicability int eh field and derived imagery. The X100, though comparatively more costly, produces images with excellent coverage of areas of interest and can fly in a wide range of weather conditions. The hobby plane solutions are low-cost and flexible in their configuration but their relative lightweight makes them difficult to fly in windy conditions and the sets of images produced can widely vary. The tethered blimp has a large payload and can fly under many conditions but its ability to systematically cover large areas is very limited. Kites are extremely low-cost but have similar limitations to blimps for area coverage and limited payload capabilities. Overall, we have found the greatest return for our investment from the Gatewing X100, despite its relatively higher cost, due to the quality of the images produced. Developments in autopilots, however, may improve the hobby aircraft solution and allow X100 like products to be produced in the near future. Results of imagery and derived products from these UAS missions will be presented and evaluated. Assessment of the viability of these UAS-products will inform the research community of their applicability to a range of applications, and if viable, could provide a lower cost alternative to other image acquisition methods.

  8. Adaptive discrete cosine transform based image coding

    NASA Astrophysics Data System (ADS)

    Hu, Neng-Chung; Luoh, Shyan-Wen

    1996-04-01

    In this discrete cosine transform (DCT) based image coding, the DCT kernel matrix is decomposed into a product of two matrices. The first matrix is called the discrete cosine preprocessing transform (DCPT), whose kernels are plus or minus 1 or plus or minus one- half. The second matrix is the postprocessing stage treated as a correction stage that converts the DCPT to the DCT. On applying the DCPT to image coding, image blocks are processed by the DCPT, then a decision is made to determine whether the processed image blocks are inactive or active in the DCPT domain. If the processed image blocks are inactive, then the compactness of the processed image blocks is the same as that of the image blocks processed by the DCT. However, if the processed image blocks are active, a correction process is required; this is achieved by multiplying the processed image block by the postprocessing stage. As a result, this adaptive image coding achieves the same performance as the DCT image coding, and both the overall computation and the round-off error are reduced, because both the DCPT and the postprocessing stage can be implemented by distributed arithmetic or fast computation algorithms.

  9. Infrared Imaging for Inquiry-Based Learning

    ERIC Educational Resources Information Center

    Xie, Charles; Hazzard, Edmund

    2011-01-01

    Based on detecting long-wavelength infrared (IR) radiation emitted by the subject, IR imaging shows temperature distribution instantaneously and heat flow dynamically. As a picture is worth a thousand words, an IR camera has great potential in teaching heat transfer, which is otherwise invisible. The idea of using IR imaging in teaching was first…

  10. 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.

  11. "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…

  12. AERIAL METHODS OF EXPLORATION

    DTIC Science & Technology

    The development of photointerpretation techniques for identifying kimberlite pipes on aerial photographs is discussed. The geographic area considered is the Daldyn region, which lies in the zone of Northern Taiga of Yakutiya.

  13. Flexible Wing Base Micro Aerial Vehicles: Towards Flight Autonomy: Vision-Based Horizon Detection for Micro Air Vehicles

    NASA Technical Reports Server (NTRS)

    Nechyba, Michael C.; Ettinger, Scott M.; Ifju, Peter G.; Wazak, Martin

    2002-01-01

    Recently substantial progress has been made towards design building and testifying remotely piloted Micro Air Vehicles (MAVs). This progress in overcoming the aerodynamic obstacles to flight at very small scales has, unfortunately, not been matched by similar progress in autonomous MAV flight. Thus, we propose a robust, vision-based horizon detection algorithm as the first step towards autonomous MAVs. In this paper, we first motivate the use of computer vision for the horizon detection task by examining the flight of birds (biological MAVs) and considering other practical factors. We then describe our vision-based horizon detection algorithm, which has been demonstrated at 30 Hz with over 99.9% correct horizon identification, over terrain that includes roads, buildings large and small, meadows, wooded areas, and a lake. We conclude with some sample horizon detection results and preview a companion paper, where the work discussed here forms the core of a complete autonomous flight stability system.

  14. 11. COPY OF 1970 AERIAL PHOTOGRAPH OF LORING AIR FORCE ...

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

    11. COPY OF 1970 AERIAL PHOTOGRAPH OF LORING AIR FORCE BASE. PHOTOGRAPH LOCATED AT AIR FORCE BASE CONVERSION AGENCY, LORING AIR FORCE BASE, MAINE. - Loring Air Force Base, Airfield, Central portion of base, Limestone, Aroostook County, ME

  15. Comic image understanding based on polygon detection

    NASA Astrophysics Data System (ADS)

    Li, Luyuan; Wang, Yongtao; Tang, Zhi; Liu, Dong

    2013-01-01

    Comic image understanding aims to automatically decompose scanned comic page images into storyboards and then identify the reading order of them, which is the key technique to produce digital comic documents that are suitable for reading on mobile devices. In this paper, we propose a novel comic image understanding method based on polygon detection. First, we segment a comic page images into storyboards by finding the polygonal enclosing box of each storyboard. Then, each storyboard can be represented by a polygon, and the reading order of them is determined by analyzing the relative geometric relationship between each pair of polygons. The proposed method is tested on 2000 comic images from ten printed comic series, and the experimental results demonstrate that it works well on different types of comic images.

  16. 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

  17. 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

  18. Liver fibrosis identification based on ultrasound images.

    PubMed

    Cao, Guitao; Shi, Pengfei; Hu, Bing

    2005-01-01

    Diagnostic ultrasound is one of useful and noninvasive tools for clinical medicine. However, due to its qualitative, subjective and experience-based nature, ultrasound images can be influenced by image conditions such as scanning frequency and machine settings. In this paper, a novel method is proposed to extract the liver features using the joint features of fractal dimension and the entropies of texture edge co-occurrence matrix based on ultrasound images, which is not sensitive to changes in emission frequency and gain. Then, Fisher linear classifier and Support Vector Machine are employed to test on a group of 99 liver fibrosis images from 18 patients, as well as other 273 healthy liver images from 18 specimens.

  19. Robust Aerial Object Tracking in High Dynamic Flight Maneuvers

    NASA Astrophysics Data System (ADS)

    Nussberger, A.; Grabner, H.; van Gool, L.

    2015-08-01

    Integrating drones into the civil airspace is one of the biggest challenges for civil aviation, responsible authorities and involved com- panies around the world in the upcoming years. For a full integration into non-segregated airspace such a system has to provide the capability to automatically detect and avoid other airspace users. Electro-optical cameras have proven to be an adequate sensor to detect all types of aerial objects, especially for smaller ones such as gliders or paragliders. Robust detection and tracking of approaching traffic on a potential collision course is the key component for a successful avoidance maneuver. In this paper we focus on the aerial object tracking during dynamic flight maneuvers of the own-ship where accurate attitude information corresponding to the camera images is essential. Because the 'detect and avoid' functionality typically extends existing autopilot systems the received attitude measurements have unknown delays and dynamics. We present an efficient method to calculate the angular rates from a multi camera rig which we fuse with the delayed attitude measurements. This allows for estimating accurate absolute attitude angles for every camera frame. The proposed method is further integrated into an aerial object tracking framework. A detailed evaluation of the pipeline on real collision encounter scenarios shows that the multi camera rig based attitude estimation enables the correct tracking of approaching traffic during dynamic flight, at which the tracking framework previously failed.

  20. Dual-rate-loop control based on disturbance observer of angular acceleration for a three-axis aerial inertially stabilized platform.

    PubMed

    Zhou, Xiangyang; Jia, Yuan; Zhao, Qiang; Cai, Tongtong

    2016-07-01

    This paper presents a dual-rate-loop control method based on disturbance observer (DOB) of angular acceleration for a three-axis ISP for aerial remote sensing applications, by which the control accuracy and stabilization of ISP are improved obviously. In stabilization loop of ISP, a dual-rate-loop strategy is designed through constituting inner rate loop and the outer rate loop, by which the capability of disturbance rejection is advanced. Further, a DOB-based on angular acceleration is proposed to attenuate the influences of the main disturbances on stabilization accuracy. Particularly, an information fusion method is suggested to obtain accurate angular acceleration in DOB design, which is the key for the disturbance compensation. The proposed methods are theoretically analyzed and experimentally validated to illustrate the effectiveness.

  1. Variety-based research on the phenolic content in the aerial parts of organically and conventionally grown buckwheat.

    PubMed

    Žvikas, V; Pukelevičienė, V; Ivanauskas, L; Pukalskas, A; Ražukas, A; Jakštas, V

    2016-12-15

    The aim of this study was to evaluate the impact of different farming types-organic and conventional-on phenolic content in buckwheat varieties grown in Lithuania. Rutin was identified as the dominant phenolic compound in contrast to both phenolic acids (chlorogenic and neochlorogenic acids) and other flavonoids (quercetin and quercitrin). It was determined that variety had the highest impact (p<0.05) on the phenolic content of various aerial parts of buckwheat. In most cases, farming practice significantly (p<0.05) affected the accumulation of phenolics in buckwheat. Organically grown plants usually contained higher amounts of phenolics than those grown under conventional farming conditions. According to a cluster analysis, varieties Panda, Zaleika, and VB Nojai were found to accumulate the highest amounts of phenolics.

  2. An Improved Artificial Bee Colony Algorithm Based on Balance-Evolution Strategy for Unmanned Combat Aerial Vehicle Path Planning

    PubMed Central

    Gong, Li-gang; Yang, Wen-lun

    2014-01-01

    Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms. PMID:24790555

  3. An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

    PubMed

    Li, Bai; Gong, Li-gang; Yang, Wen-lun

    2014-01-01

    Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

  4. Development of a Dynamic Barrier Island (Sylt, Eastern North Sea) Based on High-Resolution Aerial Photographs and GIS

    NASA Astrophysics Data System (ADS)

    Dolch, T.; Hass, H. C.

    2004-12-01

    Wind and currents are the driving forces for the morphological development of coastlines and islands by giving them their shape, run and structure. This is especially true in highly dynamic areas such as the Wadden Sea in North-Western Europe. In this unique environment changes are continuous and distinct developments can be noticed within decades. The Island of Sylt, located in the Wadden Sea near the German-Danish border, is a sandy barrier island that protects the mainland against storm floods and waves. Thus, it experiences strong erosion (about 1 m coastal retreat per year). The North Atlantic Oscillation (NAO), that controls the atmospheric circulation over the North Sea, and northerly currents are the driving forces for the morphological development. Rising sea-level due to global change amplifies the erosion processes and forces people to protect the coastline (in this case beach nourishment). The Koenigshafen, a protected, semi-enclosed bay in the north of the Island of Sylt, can be regarded as representative for the study of many coastal processes that affect the island. In this case study, a long-term series of high resolution aerial photographs of the Koenigshafen (starting in 1936) shows the development of the survey area. Wind and currents affect not only the run of the coastline but also sediment composition and biodynamics in the bay. Looking at the hydrodynamics governing the bay, it should have mostly muddy sediments. Strong westerly winds, however, supply the bay with large amounts of sand from inland dunes and create sandy tidal flats. The long-term development of seagrass and mussel beds can also be retrieved from aerial photographs. In both cases a distinct decline in size can be noticed. Remote sensing and GIS techniques allow monitoring the conditions as well as to reconstruct the past development and to predict future developments.

  5. Image-based brachytherapy for cervical cancer

    PubMed Central

    Vargo, John A; Beriwal, Sushil

    2014-01-01

    Cervical cancer is the third most common cancer in women worldwide; definitive radiation therapy and concurrent chemotherapy is the accepted standard of care for patients with node positive or locally advanced tumors > 4 cm. Brachytherapy is an important part of definitive radiotherapy shown to improve overall survival. While results for two-dimensional X-ray based brachytherapy have been good in terms of local control especially for early stage disease, unexplained toxicities and treatment failures remain. Improvements in brachytherapy planning have more recently paved the way for three-dimensional image-based brachytherapy with volumetric optimization which increases tumor control, reduces toxicity, and helps predict outcomes. Advantages of image-based brachytherapy include: improved tumor coverage (especially for large volume disease), decreased dose to critical organs (especially for small cervix), confirmation of applicator placement, and accounting for sigmoid colon dose. A number of modalities for image-based brachytherapy have emerged including: magnetic resonance imaging (MRI), computed tomography (CT), CT-MRI hybrid, and ultrasound with respective benefits and outcomes data. For practical application of image-based brachytherapy the Groupe Europeen de Curietherapie-European Society for Therapeutic Radiology and Oncology Working Group and American Brachytherapy Society working group guideline serve as invaluable tools, additionally here-in we outline our institutional clinical integration of these guidelines. While the body of literature supporting image-based brachytherapy continues to evolve a number of uncertainties and challenges remain including: applicator reconstruction, increasing resource/cost demands, mobile four-dimensional targets and organs-at-risk, and accurate contouring of “grey zones” to avoid marginal miss. Ongoing studies, including the prospective EMBRACE (an international study of MRI-guided brachytherapy in locally advanced

  6. Image-based brachytherapy for cervical cancer.

    PubMed

    Vargo, John A; Beriwal, Sushil

    2014-12-10

    Cervical cancer is the third most common cancer in women worldwide; definitive radiation therapy and concurrent chemotherapy is the accepted standard of care for patients with node positive or locally advanced tumors > 4 cm. Brachytherapy is an important part of definitive radiotherapy shown to improve overall survival. While results for two-dimensional X-ray based brachytherapy have been good in terms of local control especially for early stage disease, unexplained toxicities and treatment failures remain. Improvements in brachytherapy planning have more recently paved the way for three-dimensional image-based brachytherapy with volumetric optimization which increases tumor control, reduces toxicity, and helps predict outcomes. Advantages of image-based brachytherapy include: improved tumor coverage (especially for large volume disease), decreased dose to critical organs (especially for small cervix), confirmation of applicator placement, and accounting for sigmoid colon dose. A number of modalities for image-based brachytherapy have emerged including: magnetic resonance imaging (MRI), computed tomography (CT), CT-MRI hybrid, and ultrasound with respective benefits and outcomes data. For practical application of image-based brachytherapy the Groupe Europeen de Curietherapie-European Society for Therapeutic Radiology and Oncology Working Group and American Brachytherapy Society working group guideline serve as invaluable tools, additionally here-in we outline our institutional clinical integration of these guidelines. While the body of literature supporting image-based brachytherapy continues to evolve a number of uncertainties and challenges remain including: applicator reconstruction, increasing resource/cost demands, mobile four-dimensional targets and organs-at-risk, and accurate contouring of "grey zones" to avoid marginal miss. Ongoing studies, including the prospective EMBRACE (an international study of MRI-guided brachytherapy in locally advanced cervical

  7. A MULTICORE BASED PARALLEL IMAGE REGISTRATION METHOD

    PubMed Central

    Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L.; Foran, David J.

    2012-01-01

    Image registration is a crucial step for many image-assisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform. PMID:19964921

  8. Short-wave infrared (SWIR) spectral imager based on Fabry-Perot interferometer for remote sensing

    NASA Astrophysics Data System (ADS)

    Mannila, Rami; Holmlund, Christer; Ojanen, Harri J.; Näsilä, Antti; Saari, Heikki

    2014-10-01

    VTT Technical Research Centre of Finland has developed a spectral imager for short-wave infrared (SWIR) wavelength range. The spectral imager is based on a tunable Fabry-Perot interferometer (FPI) accompanied by a commercial InGaAs Camera. The FPI consists of two dielectric coated mirrors separated by a tunable air gap. Tuning of the air gap tunes also transmitted wavelength and therefore FPI acts as a tunable band bass filter. The FPI is piezo-actuated and it uses three piezo-actuators in a closed capacitive feedback loop for air gap tuning. The FPI has multiple order transmission bands, which limit free spectral range. Therefore spectral imager contains two FPI in a stack, to make possible to cover spectral range of 1000 - 1700 nm. However, in the first tests imager was used with one FPI and spectral range was limited to 1100-1600 nm. The spectral resolution of the imager is approximately 15 nm (FWHM). Field of view (FOV) across the flight direction is 30 deg. Imaging resolution of the spectral imager is 256 x 320 pixels. The focal length of the optics is 12 mm and F-number is 3.2. This imager was tested in summer 2014 in an unmanned aerial vehicle (UAV) and therefore a size and a mass of the imager were critical. Total mass of the imager is approximately 1200 grams. In test campaign the spectral imager will be used for forest and agricultural imaging. In future, because results of the UAV test flights are promising, this technology can be applied to satellite applications also.

  9. Study on High Accuracy Topographic Mapping via UAV-based Images

    NASA Astrophysics Data System (ADS)

    Chi, Yun-Yao; Lee, Ya-Fen; Tsai, Shang-En

    2016-10-01

    Unmanned aerial vehicle (UAV) provides a promising tool for the acquisition of such multi-temporal aerial stereo photos and high-resolution digital surface models. Recently, the flight of UAVs operates with high degrees of autonomy by the global position system and onboard digit camera and computer. The UAV-based mapping can be obtained faster and cheaper, but its accuracy is anxious. This paper aims to identify the integration ability of high accuracy topographic map via the image of quad-rotors UAV and ground control points (GCPs). The living survey data is collected in the Errn river basins area in Tainan, Taiwan. The high accuracy UAV-based topographic in the study area is calibrated by the local coordinate of GCPs using the total station with the accuracy less than 1/2000. The comparison results show the accuracy of UAV-based topographic is accepted by overlapping. The results can be a reference for the practice works of mapping survey in earth.

  10. 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.

  11. EEG based image encryption via quantum walks.

    PubMed

    Rawat, N; Shin, Y; Balasingham, I

    2016-08-01

    An electroencephalogram (EEG) based image encryption combined with Quantum walks (QW) is encoded in Fresnel domain. The computational version of EEG randomizes the original plaintext whereas QW can serve as an excellent key generator due to its inherent nonlinear chaotic dynamic behavior. First, a spatially coherent monochromatic laser beam passes through an SLM, which introduces an arbitrary EEG phase-only mask. The modified beam is collected by a CCD. Further, the intensity is multiply with the QW digitally. EEG shows high sensitivity to system parameters and capable of encrypting and transmitting the data whereas QW has unpredictability, stability and non-periodicity. Only applying the correct keys, the original image can be retrieved successfully. Simulations and comparisons show the proposed method to be secure enough for image encryption and outperforms prior works. The proposed method opens the door towards introducing EEG and quantum computation into image encryption and promotes the convergence between our approach and image processing.

  12. Balanced Multiwavelets Based Digital Image Watermarking

    NASA Astrophysics Data System (ADS)

    Zhang, Na; Huang, Hua; Zhou, Quan; Qi, Chun

    In this paper, an adaptive blind watermarking algorithm based on balanced multiwavelets transform is proposed. According to the properties of balanced multiwavelets and human vision system, a modified version of the well-established Lewis perceptual model is given. Therefore, the strength of embedded watermark is controlled by the local properties of the host image .The subbands of balanced multiwavelets transformation are similar to each other in the same scale, so the most similar subbands are chosen to embed the watermark by modifying the relation of the two subbands adaptively under the model, the watermark extraction can be performed without original image. Experimental results show that the watermarked images look visually identical to the original ones, and the watermark also successfully survives after image processing operations such as image cropping, scaling, filtering and JPEG compression.

  13. Nontarget effects of aerial mosquito adulticiding with water-based unsynergized pyrethroids on honey bees and other beneficial insects in an agricultural ecosystem of north Greece.

    PubMed

    Chaskopoulou, Alexandra; Thrasyvoulou, Andreas; Goras, Georgios; Tananaki, Chrysoula; Latham, Mark D; Kashefi, Javid; Pereira, Roberto M; Koehler, Philip G

    2014-05-01

    We assessed the nontarget effects of ultra-low-volume (ULV) aerial adulticiding with two new water-based, unsynergized pyrethroid formulations, Aqua-K-Othrine (FFAST antievaporant technology, 2% deltamethrin) and Pesguard S102 (10% d-phenothrin). A helicopter with GPS navigation technology was used. One application rate was tested per formulation that corresponded to 1.00 g (AI)/ha of deltamethrin and 7.50 g (AI)/ha of d-phenothrin. Three beneficial nontarget organisms were used: honey bees (domesticated hives), family Apidae (Apis mellifera L.); mealybug destroyers, family Coccinellidae (Cryptolaemus montrouzieri Mulsant); and green lacewings, family Chrysopidae (Chrysoperla carnea (Stephens)). No significant nontarget mortalities were observed. No bees exhibited signs of sublethal exposure to insecticides. Beehives exposed to the insecticidal applications remained healthy and productive, performed as well as the control hives and increased in weight (25-30%), in adult bee population (14-18%), and in brood population (15-19%).

  14. The evaluation of unmanned aerial system-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds

    NASA Astrophysics Data System (ADS)

    Ouédraogo, Mohamar Moussa; Degré, Aurore; Debouche, Charles; Lisein, Jonathan

    2014-06-01

    Agricultural watersheds tend to be places of intensive farming activities that permanently modify their microtopography. The surface characteristics of the soil vary depending on the crops that are cultivated in these areas. Agricultural soil microtopography plays an important role in the quantification of runoff and sediment transport because the presence of crops, crop residues, furrows and ridges may impact the direction of water flow. To better assess such phenomena, 3-D reconstructions of high-resolution agricultural watershed topography are essential. Fine-resolution topographic data collection technologies can be used to discern highly detailed elevation variability in these areas. Knowledge of the strengths and weaknesses of existing technologies used for data collection on agricultural watersheds may be helpful in choosing an appropriate technology. This study assesses the suitability of terrestrial laser scanning (TLS) and unmanned aerial system (UAS) photogrammetry for collecting the fine-resolution topographic data required to generate accurate, high-resolution digital elevation models (DEMs) in a small watershed area (12 ha). Because of farming activity, 14 TLS scans (≈ 25 points m- 2) were collected without using high-definition surveying (HDS) targets, which are generally used to mesh adjacent scans. To evaluate the accuracy of the DEMs created from the TLS scan data, 1098 ground control points (GCPs) were surveyed using a real time kinematic global positioning system (RTK-GPS). Linear regressions were then applied to each DEM to remove vertical errors from the TLS point elevations, errors caused by the non-perpendicularity of the scanner's vertical axis to the local horizontal plane, and errors correlated with the distance to the scanner's position. The scans were then meshed to generate a DEMTLS with a 1 × 1 m spatial resolution. The Agisoft PhotoScan and MicMac software packages were used to process the aerial photographs and generate a DEMPSC

  15. Content-Based Medical Image Retrieval

    NASA Astrophysics Data System (ADS)

    Müller, Henning; Deserno, Thomas M.

    This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval. This need is partly due to the large amount of visual data produced, the increasing variety of medical imaging data and changing user patterns. The stored visual data contain large amounts of unused information that, if well exploited, can help diagnosis, teaching and research. The chapter briefly reviews the history of image retrieval and its general methods before technologies that have been developed in the medical domain are focussed. We also discuss evaluation of medical content-based image retrieval (CBIR) systems and conclude with pointing out their strengths, gaps, and further developments. As examples, the MedGIFT project and the Image Retrieval in Medical Applications (IRMA) framework are presented.

  16. Space-based optical image encryption.

    PubMed

    Chen, Wen; Chen, Xudong

    2010-12-20

    In this paper, we propose a new method based on a three-dimensional (3D) space-based strategy for the optical image encryption. The two-dimensional (2D) processing of a plaintext in the conventional optical encryption methods is extended to a 3D space-based processing. Each pixel of the plaintext is considered as one particle in the proposed space-based optical image encryption, and the diffraction of all particles forms an object wave in the phase-shifting digital holography. The effectiveness and advantages of the proposed method are demonstrated by numerical results. The proposed method can provide a new optical encryption strategy instead of the conventional 2D processing, and may open up a new research perspective for the optical image encryption.

  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. Identifying image preferences based on demographic attributes

    NASA Astrophysics Data System (ADS)

    Fedorovskaya, Elena A.; Lawrence, Daniel R.

    2014-02-01

    The intent of this study is to determine what sorts of images are considered more interesting by which demographic groups. Specifically, we attempt to identify images whose interestingness ratings are influenced by the demographic attribute of the viewer's gender. To that end, we use the data from an experiment where 18 participants (9 women and 9 men) rated several hundred images based on "visual interest" or preferences in viewing images. The images were selected to represent the consumer "photo-space" - typical categories of subject matter found in consumer photo collections. They were annotated using perceptual and semantic descriptors. In analyzing the image interestingness ratings, we apply a multivariate procedure known as forced classification, a feature of dual scaling, a discrete analogue of principal components analysis (similar to correspondence analysis). This particular analysis of ratings (i.e., ordered-choice or Likert) data enables the investigator to emphasize the effect of a specific item or collection of items. We focus on the influence of the demographic item of gender on the analysis, so that the solutions are essentially confined to subspaces spanned by the emphasized item. Using this technique, we can know definitively which images' ratings have been influenced by the demographic item of choice. Subsequently, images can be evaluated and linked, on one hand, to their perceptual and semantic descriptors, and, on the other hand, to the preferences associated with viewers' demographic attributes.

  19. Automatic registration of aerial photographs and digitized maps

    NASA Astrophysics Data System (ADS)

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

    1993-06-01

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

  20. Managing and distributing remote sensing images based on metadata and microimage

    NASA Astrophysics Data System (ADS)

    Su, Lihong; Deng, Xiaolian; Wang, Jindi; Li, Xiaowen

    2003-06-01

    Remote sensing images acquired by the sensors at platforms near land surface, airplane and satellite, usually have large volume and miscellaneous data formats. So it is not feasible for the users to browse remote sensing images and evaluate the quality of images and select the suitable images on Internet. Moreover, it is inefficient to read and transfer remote sensing images real-timely in a standard image viewer due to their miscellaneous data formats. In order to clear up the problems, the metadata and microimage are extracted from various remote sensing images, managed by the database management system software, and browsed and evaluated on Internet to decide which images are the real wanted. The process of working includes the 4 steps (1) Create metadata for the remote sensing images. The metadata consist of image data format, longitude and latitude of image range, data and time, spatial resolution, sensor attributes (field of view, bands, performance and precision etc), platform attributes (stand near land surface, airplane or satellite), flight path or orbit attributes of aerial and space observation etc. (2) Create microimage for remote sensing image. Firstly, the remote sensing images are projected to the same coordinate system by the geometric correction, so all images can be matched correctly. Then the microimages are built through 1:10 or 1:5 cubic convolution sampling the corrected images. (3) Build a database to store and manage the metadata and microimages, and create pointers to hyperlink the remote sensing images self. (4) Develop the browse interface, publish the remote sensing image base on Internet, and receive the users' order forms. The wanted images will be sent on CDROM if the orders are accepted. The interface is visualized. Here, a color spectrum is used to express the bands. A clock is for time and landscape is for days in one year. And place is located by moving your mouse on the map. The pixel sizes are shown through levels on a pyramid

  1. 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

  2. PROSTATE SPECIFIC MEMBRANE ANTIGEN-BASED IMAGING

    PubMed Central

    Osborne, Joseph R.; Akhtar, Naveed H.; Vallabhajosula, Shankar; Anand, Alok; Deh, Kofi; Tagawa, Scott T.

    2012-01-01

    SUMMARY Prostate cancer (PC) is the most common non-cutaneous malignancy affecting men in North America. Despite significant efforts, conventional imaging of PC does not contribute to patient management as much as imaging performed for other common cancers. Given the lack of specificity in conventional imaging techniques, one possible solution is to screen for PC specific antigenic targets and generate agents able to specifically bind. Prostate specific membrane antigen (PSMA) is over-expressed in PC tissue, with low levels of expression in the small intestine, renal tubular cells and salivary gland. The first clinical agent for targeting PSMA was 111In-capromab, involving an antibody recognizing the internal domain of PSMA. The second- and third-generation humanized PSMA binding antibodies have the potential to overcome some of the limitations inherent to capromab pendetide i.e. inability to bind to live PC cells. One example is the humanized monoclonal antibody J591 (Hu mAb J591) that was developed primarily for therapeutic purposes but also has interesting imaging characteristics including the identification of bone metastases in PC. The major disadvantage of use of mAb for imaging is slow target recognition and background clearance in an appropriate timeframe for diagnostic imaging. Urea-based compounds such as small molecule inhibitors may also present promising agents for PC imaging with SPECT and PET. Two such small-molecule inhibitors targeting PSMA, MIP-1072 and MIP-1095, have exhibited high affinity for PSMA. The uptake of 123I-MIP-1072 and 123I-MIP-1095 in PC xenografts have imaged successfully with favorable properties amenable to human trials. While advances in conventional imaging will continue, Ab and small molecule imaging exemplified by PSMA targeting have the greatest potential to improve diagnostic sensitivity and specificity. PMID:22658884

  3. Nonlaser-based 3D surface imaging

    SciTech Connect

    Lu, Shin-yee; Johnson, R.K.; Sherwood, R.J.

    1994-11-15

    3D surface imaging refers to methods that generate a 3D surface representation of objects of a scene under viewing. Laser-based 3D surface imaging systems are commonly used in manufacturing, robotics and biomedical research. Although laser-based systems provide satisfactory solutions for most applications, there are situations where non laser-based approaches are preferred. The issues that make alternative methods sometimes more attractive are: (1) real-time data capturing, (2) eye-safety, (3) portability, and (4) work distance. The focus of this presentation is on generating a 3D surface from multiple 2D projected images using CCD cameras, without a laser light source. Two methods are presented: stereo vision and depth-from-focus. Their applications are described.

  4. Image-based color ink diffusion rendering.

    PubMed

    Wang, Chung-Ming; Wang, Ren-Jie

    2007-01-01

    This paper proposes an image-based painterly rendering algorithm for automatically synthesizing an image with color ink diffusion. We suggest a mathematical model with a physical base to simulate the phenomenon of color colloidal ink diffusing into absorbent paper. Our algorithm contains three main parts: a feature extraction phase, a Kubelka-Munk (KM) color mixing phase, and a color ink diffusion synthesis phase. In the feature extraction phase, the information of the reference image is simplified by luminance division and color segmentation. In the color mixing phase, the KM theory is employed to approximate the result when one pigment is painted upon another pigment layer. Then, in the color ink diffusion synthesis phase, the physically-based model that we propose is employed to simulate the result of color ink diffusion in absorbent paper using a texture synthesis technique. Our image-based ink diffusing rendering (IBCIDR) algorithm eliminates the drawback of conventional Chinese ink simulations, which are limited to the black ink domain, and our approach demonstrates that, without using any strokes, a color image can be automatically converted to the diffused ink style with a visually pleasing appearance.

  5. Comparison Between Two Generic 3d Building Reconstruction Approaches - Point Cloud Based VS. Image Processing Based

    NASA Astrophysics Data System (ADS)

    Dahlke, D.; Linkiewicz, M.

    2016-06-01

    This paper compares two generic approaches for the reconstruction of buildings. Synthesized and real oblique and vertical aerial imagery is transformed on the one hand into a dense photogrammetric 3D point cloud and on the other hand into photogrammetric 2.5D surface models depicting a scene from different cardinal directions. One approach evaluates the 3D point cloud statistically in order to extract the hull of structures, while the other approach makes use of salient line segments in 2.5D surface models, so that the hull of 3D structures can be recovered. With orders of magnitudes more analyzed 3D points, the point cloud based approach is an order of magnitude more accurate for the synthetic dataset compared to the lower dimensioned, but therefor orders of magnitude faster, image processing based approach. For real world data the difference in accuracy between both approaches is not significant anymore. In both cases the reconstructed polyhedra supply information about their inherent semantic and can be used for subsequent and more differentiated semantic annotations through exploitation of texture information.

  6. 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.

  7. Protein-based tumor molecular imaging probes

    PubMed Central

    Lin, Xin; Xie, Jin

    2013-01-01

    Molecular imaging is an emerging discipline which plays critical roles in diagnosis and therapeutics. It visualizes and quantifies markers that are aberrantly expressed during the disease origin and development. Protein molecules remain to be one major class of imaging probes, and the option has been widely diversified due to the recent advances in protein engineering techniques. Antibodies are part of the immunosystem which interact with target antigens with high specificity and affinity. They have long been investigated as imaging probes and were coupled with imaging motifs such as radioisotopes for that purpose. However, the relatively large size of antibodies leads to a half-life that is too long for common imaging purposes. Besides, it may also cause a poor tissue penetration rate and thus compromise some medical applications. It is under this context that various engineered protein probes, essentially antibody fragments, protein scaffolds, and natural ligands have been developed. Compared to intact antibodies, they possess more compact size, shorter clearance time, and better tumor penetration. One major challenge of using protein probes in molecular imaging is the affected biological activity resulted from random labeling. Site-specific modification, however, allows conjugation happening in a stoichiometric fashion with little perturbation of protein activity. The present review will discuss protein-based probes with focus on their application and related site-specific conjugation strategies in tumor imaging. PMID:20232092

  8. On image matrix based feature extraction algorithms.

    PubMed

    Wang, Liwei; Wang, Xiao; Feng, Jufu

    2006-02-01

    Principal component analysis (PCA) and linear discriminant analysis (LDA) are two important feature extraction methods and have been widely applied in a variety of areas. A limitation of PCA and LDA is that when dealing with image data, the image matrices must be first transformed into vectors, which are usually of very high dimensionality. This causes expensive computational cost and sometimes the singularity problem. Recently two methods called two-dimensional PCA (2DPCA) and two-dimensional LDA (2DLDA) were proposed to overcome this disadvantage by working directly on 2-D image matrices without a vectorization procedure. The 2DPCA and 2DLDA significantly reduce the computational effort and the possibility of singularity in feature extraction. In this paper, we show that these matrices based 2-D algorithms are equivalent to special cases of image block based feature extraction, i.e., partition each image into several blocks and perform standard PCA or LDA on the aggregate of all image blocks. These results thus provide a better understanding of the 2-D feature extraction approaches.

  9. 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.

  10. 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

  11. Particle Pollution Estimation Based on Image Analysis

    PubMed Central

    Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian

    2016-01-01

    Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction. PMID:26828757

  12. SAR image registration based on Susan algorithm

    NASA Astrophysics Data System (ADS)

    Wang, Chun-bo; Fu, Shao-hua; Wei, Zhong-yi

    2011-10-01

    Synthetic Aperture Radar (SAR) is an active remote sensing system which can be installed on aircraft, satellite and other carriers with the advantages of all day and night and all-weather ability. It is the important problem that how to deal with SAR and extract information reasonably and efficiently. Particularly SAR image geometric correction is the bottleneck to impede the application of SAR. In this paper we introduces image registration and the Susan algorithm knowledge firstly, then introduces the process of SAR image registration based on Susan algorithm and finally presents experimental results of SAR image registration. The Experiment shows that this method is effective and applicable, no matter from calculating the time or from the calculation accuracy.

  13. Particle Pollution Estimation Based on Image Analysis.

    PubMed

    Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian

    2016-01-01

    Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction.

  14. Wave front distortion based fluid flow imaging

    NASA Astrophysics Data System (ADS)

    Iffa, Emishaw; Heidrich, Wolfgang

    2013-03-01

    In this paper, a transparent flow surface reconstruction based on wave front distortion is investigated. A camera lens is used to focus the image formed by the micro-lens array to the camera imaging plane. The irradiance of the captured image is transformed to frequency spectrum and then the x and y spatial components are separated. A rigid spatial translation followed by low pass filtering yields a single frequency component of the image intensity. Index of refraction is estimated from the inverse Fourier transform of the spatial frequency spectrum of the irradiance. The proposed method is evaluated with synthetic data of a randomly generated index of refraction value and used to visualize a fuel injection volumetric data.

  15. Seasonal associations and atmospheric transport distances of Fusarium collected with unmanned aerial vehicles and ground-based sampling devices

    NASA Astrophysics Data System (ADS)

    Schmale, David; Ross, Shane; Lin, Binbin

    2014-05-01

    Spores of fungi in the genus Fusarium may be transported through the atmosphere over long distances. Members of this genus are important pathogens and mycotoxin producers. New information is needed to characterize seasonal trends in atmospheric loads of Fusarium and to pinpoint the source(s) of inoculum at both local (farm) and regional (state or country) scales. Spores of Fusarium were collected from the atmosphere in an agricultural ecosystem in Blacksburg, VA, USA using a Burkard volumetric sampler (BVS) 1 m above ground level and autonomous unmanned aerial vehicles (UAVs) 100 m above ground level. More than 2,200 colony forming units (CFUs) of Fusarium were collected during 104 BVS sampling periods and 180 UAV sampling periods over four calendar years (2009-2012). Spore concentrations ranged from 0 to 13 and 0 to 23 spores m-3 for the BVS and the UAVs, respectively. Spore concentrations were generally higher in the fall, spring, and summer, and lower in the winter. Spore concentrations from the BVS were generally higher than those from the UAVs for both seasonal and hourly collections. Some of the species of Fusarium identified from our collections have not been previously reported in the state of Virginia. A Gaussian plume transport model was used to estimate distances to the potential inoculum source(s) by season. This work extends previous studies showing an association between atmospheric transport barriers (Lagrangian coherent structures or LCSs) and the movement of Fusarium in the lower atmosphere. An increased understanding of the aerobiology of Fusarium may contribute to new and improved control strategies for diseases causes by fusaria in the future.

  16. 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.

  17. Aerial photographic reproductions

    USGS Publications Warehouse

    ,

    1971-01-01

    Geological Survey vertical aerial photography is obtained primarily for topographic and geologic mapping. Reproductions from this photography are usually satisfactory for general use. Because reproductions are not stocked, but are custom processed for each order, they cannot be returned for credit or refund.

  18. Discrete directional wavelet bases for image compression

    NASA Astrophysics Data System (ADS)

    Dragotti, Pier L.; Velisavljevic, Vladan; Vetterli, Martin; Beferull-Lozano, Baltasar

    2003-06-01

    The application of the wavelet transform in image processing is most frequently based on a separable construction. Lines and columns in an image are treated independently and the basis functions are simply products of the corresponding one dimensional functions. Such method keeps simplicity in design and computation, but is not capable of capturing properly all the properties of an image. In this paper, a new truly separable discrete multi-directional transform is proposed with a subsampling method based on lattice theory. Alternatively, the subsampling can be omitted and this leads to a multi-directional frame. This transform can be applied in many areas like denoising, non-linear approximation and compression. The results on non-linear approximation and denoising show very interesting gains compared to the standard two-dimensional analysis.

  19. Video-based noncooperative iris image segmentation.

    PubMed

    Du, Yingzi; Arslanturk, Emrah; Zhou, Zhi; Belcher, Craig

    2011-02-01

    In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.

  20. LSB Based Quantum Image Steganography Algorithm

    NASA Astrophysics Data System (ADS)

    Jiang, Nan; Zhao, Na; Wang, Luo

    2016-01-01

    Quantum steganography is the technique which hides a secret message into quantum covers such as quantum images. In this paper, two blind LSB steganography algorithms in the form of quantum circuits are proposed based on the novel enhanced quantum representation (NEQR) for quantum images. One algorithm is plain LSB which uses the message bits to substitute for the pixels' LSB directly. The other is block LSB which embeds a message bit into a number of pixels that belong to one image block. The extracting circuits can regain the secret message only according to the stego cover. Analysis and simulation-based experimental results demonstrate that the invisibility is good, and the balance between the capacity and the robustness can be adjusted according to the needs of applications.

  1. Hyperspectral image data compression based on DSP

    NASA Astrophysics Data System (ADS)

    Fan, Jiming; Zhou, Jiankang; Chen, Xinhua; Shen, Weimin

    2010-11-01

    The huge data volume of hyperspectral image challenges its transportation and store. It is necessary to find an effective method to compress the hyperspectral image. Through analysis and comparison of current various algorithms, a mixed compression algorithm based on prediction, integer wavelet transform and embedded zero-tree wavelet (EZW) is proposed in this paper. We adopt a high-powered Digital Signal Processor (DSP) of TMS320DM642 to realize the proposed algorithm. Through modifying the mixed algorithm and optimizing its algorithmic language, the processing efficiency of the program was significantly improved, compared the non-optimized one. Our experiment show that the mixed algorithm based on DSP runs much faster than the algorithm on personal computer. The proposed method can achieve the nearly real-time compression with excellent image quality and compression performance.

  2. Comparison of point clouds derived from aerial image matching with data from airborne laser scanning. (Polish Title: Porównanie wóaściwości chmury punktów wygenerowanej metodą dopasowania obrazów zdjęć lotniczych z danymi z lotniczego skanowania)

    NASA Astrophysics Data System (ADS)

    Dominik, W.

    2014-12-01

    The aim of this study was to investigate the properties of point clouds derived from aerial image matching and to compare them with point clouds from airborne laser scanning. A set of aerial images acquired in years 2010-2013 over the city of Elblag were used for the analysis. Images were acquired with the use of three digital cameras: DMC II 230, DMC I and DigiCAM60 with a GSD varying from 4.5 cm to 15 cm. Eight sets of images that were used in the study were acquired at different stages of the growing season - from March to December. Two LiDAR point clouds were used for the comparison - one with a density of 1.3 p/m2 and a second with a density of 10 p/m2. Based on the input images point clouds were created with the use of the semi-global matching method. The properties of the obtained point clouds were analyzed in three ways: - by the comparison of the vertical accuracy of point clouds with reference to a terrain profile surveyed on bare ground with GPS-RTK method - by visual assessment of point cloud profiles generated both from SGM and LiDAR point clouds - by visual assessment of a digital surface model generated from a SGM point cloud with reference to a digital surface model generated from a LiDAR point cloud. The conducted studies allowed a number of observations about the quality of SGM point clouds to be formulated with respect to different factors. The main factors having influence on the quality of SGM point clouds are GSD and base/height ratio. The essential problem related to SGM point clouds are areas covered with vegetation where SGM point clouds are visibly worse in terms of both accuracy and the representation of terrain surface. It is difficult to expect that in these areas SGM point clouds could replace LiDAR point clouds. This leads to a general conclusion that SGM point clouds are less reliable, more unpredictable and are dependent on more factors than LiDAR point clouds. Nevertheless, SGM point clouds generated with appropriate parameters can

  3. Pasadena, California Anaglyph with Aerial Photo Overlay

    NASA Technical Reports Server (NTRS)

    2000-01-01

    This anaglyph shows NASA's Jet Propulsion Laboratory (JPL) in Pasadena, California. Red-blue glasses are required to see the 3-D effect. The surrounding residential areas of La Canada-Flintridge (to the left) and Altadena/Pasadena (to the right) are also shown. JPL is located at the base of the San Gabriel Mountains, an actively growing mountain range, seen towards the top of the image. The large canyon coming out of the mountains (top to bottom of image) is the Arroyo Seco, which is a major drainage channel for the mountains. Sand and gravel removal operations in the lower part of the arroyo (bottom of image) are removing debris brought down by flood and mudflow events. Old landslide scars (lobe-shaped features) are seen in the arroyo, evidence that living near steep canyon slopes in tectonically active areas can be hazardous. The data can also be utilized by recreational users such as hikers enjoying the natural beauty of these rugged mountains.

    This anaglyph was generated using topographic data from the Shuttle Radar Topography Mission to create two differing perspectives of a single image, one perspective for each eye. The detailed aerial image was provided by U. S. Geological Survey digital orthophotography. Each point in the image is shifted slightly, depending on its elevation. When viewed through special glasses, the result is a vertically exaggerated view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter.

    The Shuttle Radar Topography Mission (SRTM), launched on February 11,2000, uses the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. The mission is designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, an additional C-band imaging antenna

  4. Spatiotemporal-atlas-based dynamic speech imaging

    NASA Astrophysics Data System (ADS)

    Fu, Maojing; Woo, Jonghye; Liang, Zhi-Pei; Sutton, Bradley P.

    2016-03-01

    Dynamic magnetic resonance imaging (DS-MRI) has been recognized as a promising method for visualizing articulatory motion of speech in scientific research and clinical applications. However, characterization of the gestural and acoustical properties of the vocal tract remains a challenging task for DS-MRI because it requires: 1) reconstructing high-quality spatiotemporal images by incorporating stronger prior knowledge; and 2) quantitatively interpreting the reconstructed images that contain great motion variability. This work presents a novel imaging method that simultaneously meets both requirements by integrating a spatiotemporal atlas into a Partial Separability (PS) model-based imaging framework. Through the use of an atlas-driven sparsity constraint, this method is capable of capturing high-quality articulatory dynamics at an imaging speed of 102 frames per second and a spatial resolution of 2.2 × 2.2 mm2. Moreover, the proposed method enables quantitative characterization of variability of speech motion, compared to the generic motion pattern across all subjects, through the spatial residual components.

  5. Comparative Assessment of Very High Resolution Satellite and Aerial Orthoimagery

    NASA Astrophysics Data System (ADS)

    Agrafiotis, P.; Georgopoulos, A.

    2015-03-01

    This paper aims to assess the accuracy and radiometric quality of orthorectified high resolution satellite imagery from Pleiades-1B satellites through a comparative evaluation of their quantitative and qualitative properties. A Pleiades-B1 stereopair of high resolution images taken in 2013, two adjacent GeoEye-1 stereopairs from 2011 and aerial orthomosaic (LSO) provided by NCMA S.A (Hellenic Cadastre) from 2007 have been used for the comparison tests. As control dataset orthomosaic from aerial imagery provided also by NCMA S.A (0.25m GSD) from 2012 was selected. The process for DSM and orthoimage production was performed using commercial digital photogrammetric workstations. The two resulting orthoimages and the aerial orthomosaic (LSO) were relatively and absolutely evaluated for their quantitative and qualitative properties. Test measurements were performed using the same check points in order to establish their accuracy both as far as the single point coordinates as well as their distances are concerned. Check points were distributed according to JRC Guidelines for Best Practice and Quality Checking of Ortho Imagery and NSSDA standards while areas with different terrain relief and land cover were also included. The tests performed were based also on JRC and NSSDA accuracy standards. Finally, tests were carried out in order to assess the radiometric quality of the orthoimagery. The results are presented with a statistical analysis and they are evaluated in order to present the merits and demerits of the imaging sensors involved for orthoimage production. The results also serve for a critical approach for the usability and cost efficiency of satellite imagery for the production of Large Scale Orthophotos.

  6. Learning-based imaging through scattering media.

    PubMed

    Horisaki, Ryoichi; Takagi, Ryosuke; Tanida, Jun

    2016-06-27

    We present a machine-learning-based method for single-shot imaging through scattering media. The inverse scattering process was calculated based on a nonlinear regression algorithm by learning a number of training object-speckle pairs. In the experimental demonstration, multilayer phase objects between scattering plates were reconstructed from intensity measurements. Our approach enables model-free sensing, where it is not necessary to know the sensing processes/models.

  7. Wireless Command-and-Control of UAV-Based Imaging LANs

    NASA Technical Reports Server (NTRS)

    Herwitz, Stanley; Dunagan, S. E.; Sullivan, D. V.; Slye, R. E.; Leung, J. G.; Johnson, L. F.

    2006-01-01

    Dual airborne imaging system networks were operated using a wireless line-of-sight telemetry system developed as part of a 2002 unmanned aerial vehicle (UAV) imaging mission over the USA s largest coffee plantation on the Hawaiian island of Kauai. A primary mission objective was the evaluation of commercial-off-the-shelf (COTS) 802.11b wireless technology for reduction of payload telemetry costs associated with UAV remote sensing missions. Predeployment tests with a conventional aircraft demonstrated successful wireless broadband connectivity between a rapidly moving airborne imaging local area network (LAN) and a fixed ground station LAN. Subsequently, two separate LANs with imaging payloads, packaged in exterior-mounted pressure pods attached to the underwing of NASA's Pathfinder-Plus UAV, were operated wirelessly by ground-based LANs over independent Ethernet bridges. Digital images were downlinked from the solar-powered aircraft at data rates of 2-6 megabits per second (Mbps) over a range of 6.5 9.5 km. An integrated wide area network enabled payload monitoring and control through the Internet from a range of ca. 4000 km during parts of the mission. The recent advent of 802.11g technology is expected to boost the system data rate by about a factor of five.

  8. Unmanned aerial vehicles for rangeland mapping and monitoring: a comparison of two systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aerial photography from unmanned aerial vehicles (UAVs) bridges the gap between ground-based observations and remotely sensed imagery from aerial and satellite platforms. UAVs can be deployed quickly and repeatedly, are less costly and safer than piloted aircraft, and can obtain very high-resolution...

  9. 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.

  10. Shutter/aperture settings for aerial photography

    NASA Technical Reports Server (NTRS)

    Lockwood, H. E.; Perry, L.

    1976-01-01

    Determination of aerial camera shutter and aperture settings to produce consistently high-quality aerial photographs is a task complicated by numerous variables. Presented in this article are brief discussions of each variable and specific data which may be used for the systematic control of each. The variables discussed include sunlight, aircraft altitude, subject and season, film speed, and optical system. Data which may be used as a base reference are included, and encompass two sets of sensitometric specifications for two film-chemistry processes along with camera-aircraft parameters, which have been established and used to produce good exposures. Information contained here may be used to design and implement an exposure-determination system for aerial photography.

  11. 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.

  12. Metrically preserving the USGS aerial film archive

    USGS Publications Warehouse

    Moe, Donald; Longhenry, Ryan

    2013-01-01

    Since 1972, the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, has provided fi lm-based products to the public. EROS is home to an archive of 12 million frames of analog photography ranging from 1937 to the present. The archive contains collections from both aerial and satellite platforms including programs such as the National High Altitude Program (NHAP), National Aerial Photography Program (NAPP), U.S. Antarctic Resource Center (USARC), Declass 1(CORONA, ARGON, and LANYARD), Declass 2 (KH-7 and KH-9), and Landsat (1972 – 1992, Landsat 1–5).

  13. Laser Doppler velocimeter aerial spray measurements

    NASA Technical Reports Server (NTRS)

    Zalay, A. D.; Eberle, W. R.; Howle, R. E.; Shrider, K. R.

    1978-01-01

    An experimental research program for measuring the location, spatial extent, and relative concentration of airborne spray clouds generated by agricultural aircraft is described. The measurements were conducted with a ground-based laser Doppler velocimeter. The remote sensing instrumentation, experimental tests, and the results of the flight tests are discussed. The cross section of the aerial spray cloud and the observed location, extent, and relative concentration of the airborne particulates are presented. It is feasible to use a mobile laser Doppler velocimeter to track and monitor the transport and dispersion of aerial spray generated by an agricultural aircraft.

  14. 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.

  15. Performance of laser based optical imaging system

    NASA Astrophysics Data System (ADS)

    Shah, Dhrupesh S.; Banerjee, Arup; Vora, Anup; Biswas, Amiya; Patel, Naimesh; Kurulkar, Amit; Dutt, Ashutosh

    2016-05-01

    Day night imaging application requires high dynamic range optical imaging system to detect targets of interest covering mid-day (>32000 Lux)[1], and moonless night ( 1mLux)[1] under clear sky- (visibility of >10km, atmospheric loss of <1dB/km) and hazy (visibility of >500m, atmospheric loss of >15dB/Km) conditions. Major governing factors for development of such camera systems are (i) covert imaging with ability to identify the target, (ii) imaging irrespective to the scene background, (iii) reliable operation , (iv) imaging capabilities in inclement weather conditions, (v) resource requirement vs availability power & mass, (vi) real-time data processing, (vii) self-calibration, and (viii) cost. Identification of optimum spectral band of interest is most important to meet these requirements. Conventional detection systems sensing in MWIR and LWIR band has certain draw backs in terms of target detection capabilities, susceptibility to background and huge thermo-mechanical resource requirement. Alternatively, range gated imaging camera system sensing in NIR/SWIR spectrum has shown significant potential to detect wide dynamic range targets. ToF Camera configured in NIR band has certain advantages in terms of Focal Plane Assembly (FPA) development with large format detectors and thermo-mechanical resource requirement compared to SWIR band camera configuration. In past, ToF camera systems were successfully configured in NIR spectrum using silicon based Electron Multiplying CCD (EMCCD), Intensifier CCD (ICCD) along with Gating device and pulsed laser source having emission in between 800nm to 900nm. However, these systems have a very low dynamic range and not suitable for clear sky mid-day conditions. Recently silicon based scientific grade CMOS image sensors have shown significant improvement in terms of high NIR responsivity and available in bigger formats (5MP or more), adequate Full well capacity for day time imaging (>30Ke), very low readout noise (<2e) required for

  16. 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.

  17. Information Theoretic Similarity Measures for Content Based Image Retrieval.

    ERIC Educational Resources Information Center

    Zachary, John; Iyengar, S. S.

    2001-01-01

    Content-based image retrieval is based on the idea of extracting visual features from images and using them to index images in a database. Proposes similarity measures and an indexing algorithm based on information theory that permits an image to be represented as a single number. When used in conjunction with vectors, this method displays…

  18. Bureau of Aeronautics, October 16, 1943, Photograph #4875. AERIAL OF ...

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

    Bureau of Aeronautics, October 16, 1943, Photograph #4875. AERIAL OF ROOSEVELT BASE LOOKING EAST - Roosevelt Base, Bounded by Ocean Boulevard, Pennsylvania Avenue, Richardson Avenue, & Idaho Street, Long Beach, Los Angeles County, CA

  19. Web-based document image processing

    NASA Astrophysics Data System (ADS)

    Walker, Frank L.; Thoma, George R.

    1999-12-01

    Increasing numbers of research libraries are turning to the Internet for electron interlibrary loan and for document delivery to patrons. This has been made possible through the widespread adoption of software such as Ariel and DocView. Ariel, a product of the Research Libraries Group, converts paper-based documents to monochrome bitmapped images, and delivers them over the Internet. The National Library of Medicine's DocView is primarily designed for library patrons are beginning to reap the benefits of this new technology, barriers exist, e.g., differences in image file format, that lead to difficulties in the use of library document information. To research how to overcome such barriers, the Communications Engineering Branch of the Lister Hill National Center for Biomedical Communications, an R and D division of NLM, has developed a web site called the DocMorph Server. This is part of an ongoing intramural R and D program in document imaging that has spanned many aspects of electronic document conversion and preservation, Internet document transmission and document usage. The DocMorph Server Web site is designed to fill two roles. First, in a role that will benefit both libraries and their patrons, it allows Internet users to upload scanned image files for conversion to alternative formats, thereby enabling wider delivery and easier usage of library document information. Second, the DocMorph Server provides the design team an active test bed for evaluating the effectiveness and utility of new document image processing algorithms and functions, so that they may be evaluated for possible inclusion in other image processing software products being developed at NLM or elsewhere. This paper describes the design of the prototype DocMorph Server and the image processing functions being implemented on it.

  20. Image Coding Based on Address Vector Quantization.

    NASA Astrophysics Data System (ADS)

    Feng, Yushu

    Image coding is finding increased application in teleconferencing, archiving, and remote sensing. This thesis investigates the potential of Vector Quantization (VQ), a relatively new source coding technique, for compression of monochromatic and color images. Extensions of the Vector Quantization technique to the Address Vector Quantization method have been investigated. In Vector Quantization, the image data to be encoded are first processed to yield a set of vectors. A codeword from the codebook which best matches the input image vector is then selected. Compression is achieved by replacing the image vector with the index of the code-word which produced the best match, the index is sent to the channel. Reconstruction of the image is done by using a table lookup technique, where the label is simply used as an address for a table containing the representative vectors. A code-book of representative vectors (codewords) is generated using an iterative clustering algorithm such as K-means, or the generalized Lloyd algorithm. A review of different Vector Quantization techniques are given in chapter 1. Chapter 2 gives an overview of codebook design methods including the Kohonen neural network to design codebook. During the encoding process, the correlation of the address is considered and Address Vector Quantization is developed for color image and monochrome image coding. Address VQ which includes static and dynamic processes is introduced in chapter 3. In order to overcome the problems in Hierarchical VQ, Multi-layer Address Vector Quantization is proposed in chapter 4. This approach gives the same performance as that of the normal VQ scheme but the bit rate is about 1/2 to 1/3 as that of the normal VQ method. In chapter 5, a Dynamic Finite State VQ based on a probability transition matrix to select the best subcodebook to encode the image is developed. In chapter 6, a new adaptive vector quantization scheme, suitable for color video coding, called "A Self -Organizing

  1. MEMS FPI-based smartphone hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Rissanen, Anna; Saari, Heikki; Rainio, Kari; Stuns, Ingmar; Viherkanto, Kai; Holmlund, Christer; Näkki, Ismo; Ojanen, Harri

    2016-05-01

    This paper demonstrates a mobile phone- compatible hyperspectral imager based on a tunable MEMS Fabry-Perot interferometer. The realized iPhone 5s hyperspectral imager (HSI) demonstrator utilizes MEMS FPI tunable filter for visible-range, which consist of atomic layer deposited (ALD) Al2O3/TiO2-thin film Bragg reflectors. Characterization results for the mobile phone hyperspectral imager utilizing MEMS FPI chip optimized for 500 nm is presented; the operation range is λ = 450 - 550 nm with FWHM between 8 - 15 nm. Also a configuration of two cascaded FPIs (λ = 500 nm and λ = 650 nm) combined with an RGB colour camera is presented. With this tandem configuration, the overall wavelength tuning range of MEMS hyperspectral imagers can be extended to cover a larger range than with a single FPI chip. The potential applications of mobile hyperspectral imagers in the vis-NIR range include authentication, counterfeit detection and potential health/wellness and food sensing applications.

  2. Curvelet Based Offline Analysis of SEM Images

    PubMed Central

    Shirazi, Syed Hamad; Haq, Nuhman ul; Hayat, Khizar; Naz, Saeeda; Haque, Ihsan ul

    2014-01-01

    Manual offline analysis, of a scanning electron microscopy (SEM) image, is a time consuming process and requires continuous human intervention and efforts. This paper presents an image processing based method for automated offline analyses of SEM images. To this end, our strategy relies on a two-stage process, viz. texture analysis and quantification. The method involves a preprocessing step, aimed at the noise removal, in order to avoid false edges. For texture analysis, the proposed method employs a state of the art Curvelet transform followed by segmentation through a combination of entropy filtering, thresholding and mathematical morphology (MM). The quantification is carried out by the application of a box-counting algorithm, for fractal dimension (FD) calculations, with the ultimate goal of measuring the parameters, like surface area and perimeter. The perimeter is estimated indirectly by counting the boundary boxes of the filled shapes. The proposed method, when applied to a representative set of SEM images, not only showed better results in image segmentation but also exhibited a good accuracy in the calculation of surface area and perimeter. The proposed method outperforms the well-known Watershed segmentation algorithm. PMID:25089617

  3. Using IKONOS and Aerial Videography to Validate Landsat Land Cover Maps of Central African Tropical Rain Forests

    NASA Astrophysics Data System (ADS)

    Lin, T.; Laporte, N. T.

    2003-12-01

    Compared to the traditional validation methods, aerial videography is a relatively inexpensive and time-efficient approach to collect "field" data for validating satellite-derived land cover map over large areas. In particular, this approach is valuable in remote and inaccessible locations. In the Sangha Tri-National Park region of Central Africa, where road access is limited to industrial logging sites, we are using IKONOS imagery and aerial videography to assess the accuracy of Landsat-derived land cover maps. As part of a NASA Land Cover Land Use Change project (INFORMS) and in collaboration with the Wildlife Conservation Society in the Republic of Congo, over 1500km of aerial video transects were collected in the Spring of 2001. The use of MediaMapper software combined with a VMS 200 video mapping system enabled the collection of aerial transects to be registered with geographic locations from a Geographic Positioning System. Video frame were extracted, visually interpreted, and compared to land cover types mapped by Landsat. We addressed the limitations of accuracy assessment using aerial-base data and its potential for improving vegetation mapping in tropical rain forests. The results of the videography and IKONOS image analysis demonstrate the utility of very high resolution imagery for map validation and forest resource assessment.

  4. 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

  5. PET Imaging of Skull Base Neoplasms.

    PubMed

    Mittra, Erik S; Iagaru, Andrei; Quon, Andrew; Fischbein, Nancy

    2007-10-01

    The utility of 18-F-fluorodeoxyglucose-positron emission tomography (PET) and PET/CT for the evaluation of skull base tumors is incompletely investigated, as a limited number of studies specifically focus on this region with regard to PET imaging. Several patterns can be ascertained, however, by synthesizing the data from various published reports and cases of primary skull base malignancies, as well as head and neck malignancies that extend secondarily to the skull base, including nasopharyngeal carcinoma, nasal cavity and paranasal sinus tumors, parotid cancers, and orbital tumors.

  6. Aerial and ground-based inspections of mine sites in the Western U.S.-implications for on-site inspection overflights, under the CTBT

    SciTech Connect

    Heuze, F.E.

    1997-07-01

    The verification regime of the Comprehensive Test Ban Treaty (CTBT) provides for the possibility of On-Site Inspections (OSI`s) to resolve questions concerning suspicious events which may have been clandestine nuclear tests. Overflights by fixed-wing or rotary-wing aircraft, as part of an OSI, are permitted by the Treaty. These flights are intended to facilitate the narrowing of the inspection area, from an initial permissible 1000 km{sup 2}, and to help select the locations to deploy observers and ground-based sensors (seismic, radionuclides, . . .) Because of the substantial amount of seismicity generated by mining operations worldwide, it is expected that mine sites and mine districts would be prime candidates for OSI`S. To gain experience in this context, a number of aerial and ground-based mine site inspections have been performed in the Western U.S. by Lawrence Livermore National Laboratory since 1994. These inspections are part of a broad range of CTBT mining-related projects conducted by the U.S. Department of Energy and its National Laboratories. The various sites are described next, and inferences are made concerning CTBT OSI`S. All the mines are legitimate operations, with no implication whatsoever of any clandestine tests.

  7. Canny edge-based deformable image registration

    NASA Astrophysics Data System (ADS)

    Kearney, Vasant; Huang, Yihui; Mao, Weihua; Yuan, Baohong; Tang, Liping

    2017-02-01

    This work focuses on developing a 2D Canny edge-based deformable image registration (Canny DIR) algorithm to register in vivo white light images taken at various time points. This method uses a sparse interpolation deformation algorithm to sparsely register regions of the image with strong edge information. A stability criterion is enforced which removes regions of edges that do not deform in a smooth uniform manner. Using a synthetic mouse surface ground truth model, the accuracy of the Canny DIR algorithm was evaluated under axial rotation in the presence of deformation. The accuracy was also tested using fluorescent dye injections, which were then used for gamma analysis to establish a second ground truth. The results indicate that the Canny DIR algorithm performs better than rigid registration, intensity corrected Demons, and distinctive features for all evaluation matrices and ground truth scenarios. In conclusion Canny DIR performs well in the presence of the unique lighting and shading variations associated with white-light-based image registration.

  8. Processing of Uav Based Range Imaging Data to Generate Detailed Elevation Models of Complex Natural Structures

    NASA Astrophysics Data System (ADS)

    Kohoutek, T. K.; Eisenbeiss, H.

    2012-07-01

    Unmanned Aerial Vehicles (UAVs) are more and more used in civil areas like geomatics. Autonomous navigated platforms have a great flexibility in flying and manoeuvring in complex environments to collect remote sensing data. In contrast to standard technologies such as aerial manned platforms (airplanes and helicopters) UAVs are able to fly closer to the object and in small-scale areas of high-risk situations such as landslides, volcano and earthquake areas and floodplains. Thus, UAVs are sometimes the only practical alternative in areas where access is difficult and where no manned aircraft is available or even no flight permission is given. Furthermore, compared to terrestrial platforms, UAVs are not limited to specific view directions and could overcome occlusions from trees, houses and terrain structures. Equipped with image sensors and/or laser scanners they are able to provide elevation models, rectified images, textured 3D-models and maps. In this paper we will describe a UAV platform, which can carry a range imaging (RIM) camera including power supply and data storage for the detailed mapping and monitoring of complex structures, such as alpine riverbed areas. The UAV platform NEO from Swiss UAV was equipped with the RIM camera CamCube 2.0 by PMD Technologies GmbH to capture the surface structures. Its navigation system includes an autopilot. To validate the UAV-trajectory a 360° prism was installed and tracked by a total station. Within the paper a workflow for the processing of UAV-RIM data is proposed, which is based on the processing of differential GNSS data in combination with the acquired range images. Subsequently, the obtained results for the trajectory are compared and verified with a track of a UAV (Falcon 8, Ascending Technologies) carried out with a total station simultaneously to the GNSS data acquisition. The results showed that the UAV's position using differential GNSS could be determined in the centimetre to the decimetre level. The RIM

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  10. 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

  11. Content-Based Image Retrieval in Medicine

    PubMed Central

    Long, L. Rodney; Antani, Sameer; Deserno, Thomas M.; Thoma, George R.

    2009-01-01

    Content-based image retrieval (CBIR) technology has been proposed to benefit not only the management of increasingly large image collections, but also to aid clinical care, biomedical research, and education. Based on a literature review, we conclude that there is widespread enthusiasm for CBIR in the engineering research community, but the application of this technology to solve practical medical problems is a goal yet to be realized. Furthermore, we highlight “gaps” between desired CBIR system functionality and what has been achieved to date, present for illustration a comparative analysis of four state-of-the-art CBIR implementations using the gap approach, and suggest that high-priority gaps to be overcome lie in CBIR interfaces and functionality that better serve the clinical and biomedical research communities. PMID:20523757

  12. Success with Web-based image access.

    PubMed

    Harrison, Sean W

    2003-01-01

    The University of Mississippi Medical Center in Jackson, Miss., is the only medical school in the state. We performed 235,000 procedures in the 2001-02 fiscal year. All imaging services within the radiology department are networked to a PACS and are filmless. The elimination of film required that we decentralize our traditional file room to allow easy access to our radiology network across the campus. In our facility, there are three levels of image access: Diagnostic Quality, Review Quality and Web Access. Diagnostic Quality requires top-of-the-line workstations and monitors and is the most expensive. Review Quality workstations represent some savings over Diagnostic and are used in the ICU, orthopedics and surgery. Web Access appears to satisfy most areas outside the main diagnostic department. The account set-up procedure is simple because it uses our intranet email system. Images are easily pasted into presentation applications for articles and conferences. However, the main advantage of Web Access is the low cost. The downside of Web Access is that the images are for review only and are limited by the quality of the monitor in use. It is also somewhat cumbersome to retrieve old or comparison images via this method. The Web only holds approximately 45 days of the most recent images, therefore older studies may not be available. The deployment of this Web-based service has aided in our efforts to reduce the amount of film we print and has also been beneficial in improving patient care through faster service.

  13. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

    PubMed

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-08-19

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

  14. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

    PubMed Central

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-01-01

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

  15. Image as Insight: Visual Images in Practice-Based Research

    ERIC Educational Resources Information Center

    Marshall, Julia

    2007-01-01

    "Art practice as research" casts artmaking as inquiry--as a particularly experiential and constructivist process of learning in which imaginative synthesis and creative image making are ways of constructing knowledge. This article explores how artmaking functions as research through the creation of visual images, especially images that picture…

  16. Efficacy of aerial ultra-low volume applications of two novel water-based formulations of unsynergized pyrethroids against riceland mosquitoes in Greece.

    PubMed

    Chaskopoulou, Alexandra; Latham, Mark D; Pereira, Roberto M; Connelly, Roxanne; Bonds, Jane A S; Koehler, Philip G

    2011-12-01

    We assessed the efficacy of ultra-low volume aerial adulticiding with 2 new water-based, unsynergized formulations of Aqua-K-Othrin (2% deltamethrin) and Pesguard S102 (10% d-phenothrin) against the riceland mosquitoes of Greece. A helicopter with Global Positioning System (GPS) navigation, real-time weather recording, and spray dispersal modeling (AgDISP) was utilized to accurately treat the experimental blocks by adjusting spray line positions to changing meteorological conditions. Two application rates were applied per formulation that corresponded to 0.75 and 1.00 g AI/ha of deltamethrin and 7.50 and 10.00 g AI/ha of d-phenothrin. The mosquitoes used for the trials were the main nuisance species found in rice field areas of Thessaloniki, which were primarily Aedes caspius, followed by Culex modestus and Anopheles sacharovi. Overall mean mortality of caged mosquitoes was 69.2% and 64.8% for deltamethrin and d-phenothrin, respectively. Mean population decrease in wild mosquito populations within the treatment areas was 76.5% and 78% for deltamethrin and d-phenothrin, respectively. The AgDISP dispersal model, coupled with GPS navigation and real-time weather recording, enabled accurate placement of the spray cloud such that the majority of the treatment area received sufficiently high droplet densities to result in uniform caged-mosquito mortality across all sampling sites.

  17. Differential auxin transport and accumulation in the stem base lead to profuse adventitious root primordia formation in the aerial roots (aer) mutant of tomato (Solanum lycopersicum L.).

    PubMed

    Mignolli, F; Mariotti, L; Picciarelli, P; Vidoz, M L

    2017-02-27

    The aerial roots (aer) mutant of tomato is characterized by a profuse and precocious formation of adventitious root primordia along the stem. We demonstrated that auxin is involved in the aer phenotype but ruled out higher auxin sensitivity of mutant plants. Interestingly, polar auxin transport was altered in aer, as young seedlings showed a reduced response to an auxin transport inhibitor and higher expression of auxin export carriers SlPIN1 and SlPIN3. An abrupt reduction in transcripts of auxin efflux and influx genes in older aer hypocotyls caused a marked deceleration of auxin transport in more mature tissues. Indeed, in 20days old aer plants, the transport of labeled IAA was faster in apices than in hypocotyls, displaying an opposite trend in comparison to a wild type. In addition, auxin transport facilitators (SlPIN1, SlPIN4, SlLAX5) were more expressed in aer apices than in hypocotyls, suggesting that auxin moves faster from the upper to the lower part of the stem. Consequently, a significantly higher level of free and conjugated IAA was found at the base of aer stems with respect to their apices. This auxin accumulation is likely the cause of the aer phenotype.

  18. [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.

  19. Variational exemplar-based image colorization.

    PubMed

    Bugeau, Aurélie; Ta, Vinh-Thong; Papadakis, Nicolas

    2014-01-01

    In this paper, we address the problem of recovering a color image from a grayscale one. The input color data comes from a source image considered as a reference image. Reconstructing the missing color of a grayscale pixel is here viewed as the problem of automatically selecting the best color among a set of color candidates while simultaneously ensuring the local spatial coherency of the reconstructed color information. To solve this problem, we propose a variational approach where a specific energy is designed to model the color selection and the spatial constraint problems simultaneously. The contributions of this paper are twofold. First, we introduce a variational formulation modeling the color selection problem under spatial constraints and propose a minimization scheme, which computes a local minima of the defined nonconvex energy. Second, we combine different patch-based features and distances in order to construct a consistent set of possible color candidates. This set is used as input data and our energy minimization automatically selectsthe best color to transfer for each pixel of the grayscale image. Finally, the experiments illustrate the potentiality of our simple methodology and show that our results are very competitive with respect to the state-of-the-art methods.