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Sample records for aerial image based

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  2. Aerial Image Systems

    NASA Astrophysics Data System (ADS)

    Clapp, Robert E.

    1987-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  4. 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.

  5. Estimating growth status of winter wheat based on aerial images and hyperspectral data

    NASA Astrophysics Data System (ADS)

    Han, Yunxia; Li, Minzan; Jia, Liangliang; Zhang, Xijie; Zhang, Fusuo

    2005-08-01

    The aim of this paper is to estimate the growth status and yield of winter wheat using aerial images and hyperspectral data obtained by unmanned aircraft, and then to perform precision management to the crop. The test farm was divided into 48 cells. Twenty-four cells were selected as variable rate fertilization area, and the other 24 cells were used as contrast area with low fertilization in growth season. In 2004, the aerial images of winter wheat canopy were measured from an unmanned aircraft. The SPAD value of crop leaf was acquired using a SPAD-502 chlorophyll meter, and then the hyperspectral reflectance of the crop canopy was measured by a handheld spectroradiometer. The vegetation indices, NDVI and DVI, were calculated from the hyperspectral data. The characteristics of the aerial images were used to evaluate the growth status. The RGB values of all cells were calculated from aerial images. The result showed that total nitrogen had better correlation with SPAD, NDVI, DVI, and RGB. NDVI and DVI had high correlation with the growth condition, and R/(R+G+B) and G/(R+G+B) had good correlation with the growth status and yield. The variable rate fertilization based on aerial images and NDVI was executed in the experimental cells. The yield map showed that the spatial variation of the yield was reduced and the total yield was increased. While in contrast cells, the spatial variation of the yield is greater than in experimental cells because of the spatial variation of the field nutrition. Therefore, it is practical to use aerial images and hyperspectral data of the crop canopy in estimation of the crop growth status.

  6. 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.

  7. Aerial Photographs and Satellite Images

    USGS Publications Warehouse

    U.S. Geological Survey

    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.

  8. 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.

  9. 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.

  10. 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

  11. An aerial remote sensing image's mosaic approach using multi-layer wavelet fusion based on structure similarity

    NASA Astrophysics Data System (ADS)

    Wei, Li; Shi, Junsheng; Huang, Xiaoqiao; Ding, Huimei

    2015-12-01

    In order to solve the problems that image's entropy of information decline obviously and boundary line phenomenon appear obviously in the processing of aerial remote sensing image's mosaic, an image mosaic approach is presented in this paper, which uses wavelet image fusion based on structure similarity and is capable of creating seamless mosaics in real-time. The approach consists of three steps. First, the overlapping area of two aerial images is extracted. Then, the two overlapping area images are fused adaptively by the method of multi-layer wavelet decomposition based on the structure similarity and appointed regulation. Finally, weighted average fusion is used again to avoid the visible boundary line for the both sides of the boundary of the above fusion image. Experimental results show the entropy of information, sharpness and standard deviation have been improved significantly, and the boundary line has been eliminated observably.

  12. 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.

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

    PubMed

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

    2015-01-01

    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. Comparison of event-based landslide inventory maps obtained interpreting satellite images and aerial photographs

    NASA Astrophysics Data System (ADS)

    Fiorucci, Federica; Cardinali, Mauro; Carlà Roberto; Mondini, Alessandro; Santurri, Leonardo; Guzzetti, Fausto

    2010-05-01

    Landslide inventory maps are a common type of map used for geomorphological investigations, land planning, and hazard and risk assessment. Landslide inventory maps covering medium to large areas are obtained primarily exploiting traditional geomorphological techniques. These techniques combine the visual and heuristic interpretation of stereoscopic aerial photographs with more or less extensive field investigations. Aerial photographs most commonly used to prepare landslide inventory maps range in scale from about 1:10,000 to about 1:40,000. Interpretation of satellite images is a relatively recent, powerful tool to obtain information of the Earth surface potentially useful for the production of landslide inventory maps. The usefulness of satellite information - and the associated technology - for the identification of landslides and the production of landslide inventory maps, remains largely unexplored. In this context, it is of interest to investigate the type, quantity, and quality of the information that can be retrieved analyzing images taken by the last generation of high and very-high resolution satellite sensors, and to compare this information with the information obtained from the analysis of traditional stereoscopic aerial photographs, or in the field. In the framework of the MORFEO project for the exploitation of Earth Observation data and technology for landslide identification and risk assessment, of the Italian Space Agency, we have compared two event-based landslide inventory maps prepared exploiting two different techniques. The two maps portray the geographical distribution and types of landslides triggered by rainfall in the period from November 2004 to May 2005 in the Collazzone area, Umbria, central Italy. The first map was prepared through reconnaissance field surveys carried out mostly along roads. The second map was obtained through the combined visual interpretation of 1:10,000 scale, colour ortho-photo maps, and images taken by the IKONOS

  15. a Robust Matching Method for Unmmaned Aerial Vehicle Images with Different Viewpoint Angles Based on Regional Coherency

    NASA Astrophysics Data System (ADS)

    Shao, Z.; Li, C.; Yang, N.

    2015-08-01

    One of the main challenges confronting high-resolution remote sensing image matching is how to address the issue of geometric deformation between images, especially when the images are obtained from different viewpoints. In this paper, a robust matching method for Unmanned Aerial Vehicle images of different viewpoint angles based on regional coherency is proposed. The literature on the geometric transform analysis reveals that if transformations between different pixel pairs are different, they can't be expressed by a uniform affine transform. While for the same real scene, if the instantaneous field of view or the target depth changes is small, transformation between pixels in the whole image can be approximated by an affine transform. On the basis of this analysis, a region coherency matching method for Unmanned Aerial Vehicle images is proposed. In the proposed method, the simplified mapping from image view change to scale change and rotation change has been derived. Through this processing, the matching between view change images can be converted into the matching between rotation and scale changed images. In the method, firstly local image regions are detected and view changes between these local regions are mapped to rotation and scale change by performing local region simulation. And then, point feature detection and matching are implemented in the simulated image regions. Finally, a group of Unmanned Aerial Vehicle images are adopted to verify the performance of proposed matching method respectively, and a comparative analysis with other methods demonstrates the effectiveness of the proposed method.

  16. Extracting roads based on Retinex and improved Canny operator with shape criteria in vague and unevenly illuminated aerial images

    NASA Astrophysics Data System (ADS)

    Ronggui, Ma; Weixing, Wang; Sheng, Liu

    2012-01-01

    An automatic road extraction method for vague aerial images is proposed in this paper. First, a high-resolution but low-contrast image is enhanced by using a Retinex-based algorithm. Then, the enhanced image is segmented with an improved Canny edge detection operator that can automatically threshold the image into a binary edge image. Subsequently, the linear and curved road segments are regulated by the Hough line transform and extracted based on several thresholds of road size and shapes, in which a number of morphological operators are used such as thinning (skeleton), junction detection, and endpoint detection. In experiments, a number of vague aerial images with bad uniformity are selected for testing. Similarity and discontinuation-based algorithms, such as Otsu thresholding, merge and split, edge detection-based algorithms, and the graph-based algorithm are compared with the new method. The experiment and comparison results show that the studied method can enhance vague, low-contrast, and unevenly illuminated color aerial road images; it can detect most road edges with fewer disturb elements and trace roads with good quality. The method in this study is promising.

  17. 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.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

    Qin, R.; Gruen, A.

    2014-08-01

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

  20. Contact area as the intuitive definition of contact CD based on aerial image analysis

    NASA Astrophysics Data System (ADS)

    Polonsky, Netanel; Sagiv, Amir; Mangan, Shmoolik

    2009-03-01

    As feature sizes continue to diminish, optical lithography is driven into the extreme low-k1 regime, where the high MEEF increasingly complicates the relationship between the mask pattern and the aerial image. This is true in particular for twodimensional mask patterns, which are by nature much more complicated than patterns possessing one-dimensional symmetry. Thus, the intricacy of 2D image formation typically requires a much broader arsenal of resolution enhancement techniques over complex phase shift masks, including SRAFs and OPC, as well as exotic off-axis illumination geometries. This complexity on the mask side makes the printability effect of a random defect on a 2D pattern a field of rich and delicate phenomenology. This complexity is reflected in the dispute over the CD definition of 2D patterns: some sources use the X and Y values, while others use the contact area. Here, we argue that for compact features, for which the largest dimension is not wider than the PSF of the stepper optics, the area definition is the natural one. We study the response of the aerial image to small perturbations in mask pattern. We show that any perturbation creates an effect extending in all directions, thus affecting the area and not the size in a single direction. We also show that, irrespective of the source of perturbation, the aerial signal is proportional to the variation in the area of the printed feature. The consequence of this effect is that aerial inspection signal scales linearly with the variation of printed area of the tested feature.

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    Harb Rabia, Ahmed; Terribile, Fabio

    2013-04-01

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

  3. 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.

  4. [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. PMID:26415454

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

    NASA Astrophysics Data System (ADS)

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

    2011-04-01

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

  6. Wavefront aberration measurement method for a hyper-NA lithographic projection lens based on principal component analysis of an aerial image.

    PubMed

    Zhu, Boer; Wang, Xiangzhao; Li, Sikun; Yan, Guanyong; Shen, Lina; Duan, Lifeng

    2016-04-20

    A wavefront aberration measurement method for a hyper-NA lithographic projection lens by use of an aerial image based on principal component analysis is proposed. Aerial images of the hyper-NA lithographic projection lens are expressed accurately by using polarized light and a vector imaging model, as well as by considering the polarization properties. As a result, the wavefront aberrations of the hyper-NA lithographic projection lens are measured accurately. The lithographic simulator PROLITH is used to validate the accuracies of the wavefront aberration measurement and analyze the impact of the polarization rotation of illumination on the accuracy of the wavefront aberration measurement, as well as the degree of polarized light and the sample interval of aerial images. The result shows that the proposed method can retrieve 33 terms of Zernike coefficients (Z5-Z37) with a maximum error of less than 0.00085λ. PMID:27140087

  7. 3D Buildings Extraction from Aerial Images

    NASA Astrophysics Data System (ADS)

    Melnikova, O.; Prandi, F.

    2011-09-01

    This paper introduces a semi-automatic method for buildings extraction through multiple-view aerial image analysis. The advantage of the used semi-automatic approach is that it allows processing of each building individually finding the parameters of buildings features extraction more precisely for each area. On the early stage the presented technique uses an extraction of line segments that is done only inside of areas specified manually. The rooftop hypothesis is used further to determine a subset of quadrangles, which could form building roofs from a set of extracted lines and corners obtained on the previous stage. After collecting of all potential roof shapes in all images overlaps, the epipolar geometry is applied to find matching between images. This allows to make an accurate selection of building roofs removing false-positive ones and to identify their global 3D coordinates given camera internal parameters and coordinates. The last step of the image matching is based on geometrical constraints in contrast to traditional correlation. The correlation is applied only in some highly restricted areas in order to find coordinates more precisely, in such a way significantly reducing processing time of the algorithm. The algorithm has been tested on a set of Milan's aerial images and shows highly accurate results.

  8. 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.

  9. 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.

  10. 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

  11. Research of Active Contour Model in Aerial Images

    NASA Astrophysics Data System (ADS)

    Kun, Wang; Li, Guo

    With the development of computer and aviation technology, the aerial image is facing an important issue is how to automate, including aerial images of the automatic extraction of the target. In this paper, the issue of aerial images to study the active contour model is introduced, that is, Snake model, to achieve the target aerial image of the semi-automatic contour extraction method. Snake model used the unique characteristic of the energy minimization, carried out on the image contour extraction, to obtain a clear, consistent and accurate image contour. The model is defined through the energy minimization of the function, given in the initial position of artificial circumstances, through the iterative calculation of Snake model will eventually form the minimum energy function has been described in the outline of the target partition. The results indicate that Snake model for aerial images of the edge contour extraction, verification, concluded that the Snake-based edge detection methods could be more objectively and accurately extract the edge of the outline of aerial images.

  12. 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

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

    PubMed

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

    2016-01-01

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

  14. Comparison of DSMs acquired by terrestrial laser scanning, UAV-based aerial images and ground-based optical images at the Super-Sauze landslide

    NASA Astrophysics Data System (ADS)

    Rothmund, Sabrina; Niethammer, Uwe; Walter, Marco; Joswig, Manfred

    2013-04-01

    In recent years, the high-resolution and multi-temporal 3D mapping of the Earth's surface using terrestrial laser scanning (TLS), ground-based optical images and especially low-cost UAV-based aerial images (Unmanned Aerial Vehicle) has grown in importance. This development resulted from the progressive technical improvement of the imaging systems and the freely available multi-view stereo (MVS) software packages. These different methods of data acquisition for the generation of accurate, high-resolution digital surface models (DSMs) were applied as part of an eight-week field campaign at the Super-Sauze landslide (South French Alps). An area of approximately 10,000 m² with long-term average displacement rates greater than 0.01 m/day has been investigated. The TLS-based point clouds were acquired at different viewpoints with an average point spacing between 10 to 40 mm and at different dates. On these days, more than 50 optical images were taken on points along a predefined line on the side part of the landslide by a low-cost digital compact camera. Additionally, aerial images were taken by a radio-controlled mini quad-rotor UAV equipped with another low-cost digital compact camera. The flight altitude ranged between 20 m and 250 m and produced a corresponding ground resolution between 0.6 cm and 7 cm. DGPS measurements were carried out as well in order to geo-reference and validate the point cloud data. To generate unscaled photogrammetric 3D point clouds from a disordered and tilted image set, we use the widespread open-source software package Bundler and PMVS2 (University of Washington). These multi-temporal DSMs are required on the one hand to determine the three-dimensional surface deformations and on the other hand it will be required for differential correction for orthophoto production. Drawing on the example of the acquired data at the Super-Sauze landslide, we demonstrate the potential but also the limitations of the photogrammetric point clouds. To

  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. 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.

  17. 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...

  18. 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

  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. PMID:24146963

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

    NASA Astrophysics Data System (ADS)

    Hron, V.; Halounova, L.

    2015-03-01

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

  1. Calculating aerial images from EUV masks

    NASA Astrophysics Data System (ADS)

    Pistor, Thomas V.; Neureuther, Andrew R.

    1999-06-01

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

  2. 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.

  3. Aerial photographs and satellite images

    USGS Publications Warehouse

    U.S. Geological Survey

    1995-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Straatsma, Menno; Huthoff, Fredrik

    2011-01-01

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

  5. 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.

  6. 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.

  7. Design of an integrated aerial image sensor

    NASA Astrophysics Data System (ADS)

    Xue, Jing; Spanos, Costas J.

    2005-05-01

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

  8. 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.

  9. 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

  10. Orientation-selective building detection in aerial images

    NASA Astrophysics Data System (ADS)

    Manno-Kovacs, Andrea; Sziranyi, Tamas

    2015-10-01

    This paper introduces a novel aerial building detection method based on region orientation as a new feature, which is used in various steps throughout the presented framework. As building objects are expected to be connected with each other on a regional level, exploiting the main orientation obtained from the local gradient analysis provides further information for detection purposes. The orientation information is applied for an improved edge map design, which is integrated with classical features like shadow and color. Moreover, an orthogonality check is introduced for finding building candidates, and their final shapes defined by the Chan-Vese active contour algorithm are refined based on the orientation information, resulting in smooth and accurate building outlines. The proposed framework is evaluated on multiple data sets, including aerial and high resolution optical satellite images, and compared to six state-of-the-art methods in both object and pixel level evaluation, proving the algorithm's efficiency.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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

  16. Fitting of Parametric Building Models to Oblique Aerial Images

    NASA Astrophysics Data System (ADS)

    Panday, U. S.; Gerke, M.

    2011-09-01

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

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

    PubMed

    Hammoudi, Karim; Dornaika, Fadi

    2011-01-01

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

  18. 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

  19. 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 2 November 1961. NCA History Collection - Cypress Hills National Cemetery, Jamaica Avenue Unit, 625 Jamaica Avenue, Brooklyn, Kings County, NY

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

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

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

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

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

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

  2. 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.

  3. Flexible vision-based navigation system for unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Blasch, Erik P.

    1995-01-01

    A critical component of unmanned aerial vehicles in the navigation system which provides position and velocity feedback for autonomous control. The Georgia Tech Aerial Robotics navigational system (NavSys) consists of four DVTStinger70C Integrated Vision Units (IVUs) with CCD-based panning platforms, software, and a fiducial onboard the vehicle. The IVUs independently scan for the retro-reflective bar-code fiducial while the NavSys image processing software performs a gradient threshold followed by a image search localization of three vertical bar-code lines. Using the (x,y) image coordinate and CCD angle, the NavSys triangulates the fiducial's (x,y) position, differentiates for velocity, and relays the information to the helicopter controller, which independently determines the z direction with an onboard altimeter. System flexibility is demonstrated by recognition of different fiducial shapes, night and day time operation, and is being extended to on-board and off-board navigation of aerial and ground vehicles. The navigation design provides a real-time, inexpensive, and effective system for determining the (x,y) position of the aerial vehicle with updates generated every 51 ms (19.6 Hz) at an accuracy of approximately +/- 2.8 in.

  4. 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.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  7. 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.

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

    NASA Astrophysics Data System (ADS)

    Höhle, J.

    2013-07-01

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

  9. 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

  10. 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.

  11. 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...

  12. 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

  13. 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...

  14. 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.

  15. Improved land cover mapping using aerial photographs and satellite images

    NASA Astrophysics Data System (ADS)

    Varga, Katalin; Szabó, Szilárd; Szabó, Gergely; Dévai, György; Tóthmérész, Béla

    2014-10-01

    Manual Land Cover Mapping using aerial photographs provides sufficient level of resolution for detailed vegetation or land cover maps. However, in some cases it is not possible to achieve the desired information over large areas, for example from historical data where the quality and amount of available images is definitely lower than from modern data. The use of automated and semiautomated methods offers the means to identify the vegetation cover using remotely sensed data. In this paper automated methods were tested on aerial photographs and satellite images to extract better and more reliable information about vegetation cover. These testswere performed by using automated analysis of LANDSAT7 images (with and without the surface model of the Shuttle Radar Topography Mission (SRTM)) and two temporally similar aerial photographs. The spectral bands were analyzed with supervised (maximum likelihood) methods. In conclusion, the SRTM and the combination of two temporally similar aerial photographs from earlier years were useful in separating the vegetation cover on a floodplain area. In addition the different date of the vegetation season also gave reliable information about the land cover. High quality information about old and present vegetation on a large area is an essential prerequisites ensuring the conservation of ecosystems

  16. Automatic geolocation of targets tracked by aerial imaging platforms using satellite imagery

    NASA Astrophysics Data System (ADS)

    Shukla, P. K.; Goel, S.; Singh, P.; Lohani, B.

    2014-11-01

    Tracking of targets from aerial platforms is an important activity in several applications, especially surveillance. Knowled ge of geolocation of these targets adds additional significant and useful information to the application. This paper determines the geolocation of a target being tracked from an aerial platform using the technique of image registration. Current approaches utilize a POS to determine the location of the aerial platform and then use the same for geolocation of the targets using the principle of photogrammetry. The constraints of cost and low-payload restrict the applicability of this approach using UAV platforms. This paper proposes a methodology for determining the geolocation of a target tracked from an aerial platform in a partially GPS devoid environment. The method utilises automatic feature based registration technique of a georeferenced satellite image with an ae rial image which is already stored in UAV's database to retrieve the geolocation of the target. Since it is easier to register subsequent aerial images due to similar viewing parameters, the subsequent overlapping images are registered together sequentially thus resulting in the registration of each of the images with georeferenced satellite image thus leading to geolocation of the target under interest. Using the proposed approach, the target can be tracked in all the frames in which it is visible. The proposed concept is verified experimentally and the results are found satisfactory. Using the proposed method, a user can obtain location of target of interest as well features on ground without requiring any POS on-board the aerial platform. The proposed approach has applications in surveillance for target tracking, target geolocation as well as in disaster management projects like search and rescue operations.

  17. Ground-Cover Measurements: Assessing Correlation Among Aerial and Ground-Based Methods

    NASA Astrophysics Data System (ADS)

    Booth, D. Terrance; Cox, Samuel E.; Meikle, Tim; Zuuring, Hans R.

    2008-12-01

    Wyoming’s Green Mountain Common Allotment is public land providing livestock forage, wildlife habitat, and unfenced solitude, amid other ecological services. It is also the center of ongoing debate over USDI Bureau of Land Management’s (BLM) adjudication of land uses. Monitoring resource use is a BLM responsibility, but conventional monitoring is inadequate for the vast areas encompassed in this and other public-land units. New monitoring methods are needed that will reduce monitoring costs. An understanding of data-set relationships among old and new methods is also needed. This study compared two conventional methods with two remote sensing methods using images captured from two meters and 100 meters above ground level from a camera stand (a ground, image-based method) and a light airplane (an aerial, image-based method). Image analysis used SamplePoint or VegMeasure software. Aerial methods allowed for increased sampling intensity at low cost relative to the time and travel required by ground methods. Costs to acquire the aerial imagery and measure ground cover on 162 aerial samples representing 9000 ha were less than 3000. The four highest correlations among data sets for bare ground—the ground-cover characteristic yielding the highest correlations (r)—ranged from 0.76 to 0.85 and included ground with ground, ground with aerial, and aerial with aerial data-set associations. We conclude that our aerial surveys are a cost-effective monitoring method, that ground with aerial data-set correlations can be equal to, or greater than those among ground-based data sets, and that bare ground should continue to be investigated and tested for use as a key indicator of rangeland health.

  18. An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors

    PubMed Central

    Kicherer, Stefan; Malpica, Jose A.; Alonso, Maria C.

    2008-01-01

    In this paper, an interactive technique for extracting cartographic features from aerial and spatial images is presented. The method is essentially an interactive method of image region segmentation based on pixel grey level and texture information. The underlying segmentation method is seeded region growing. The criterion for growing regions is based on both texture and grey level, where texture is quantified using co-occurrence matrices. The Kullback distance is utilised with co-occurrence matrices in order to describe the image texture, then the Theory of Evidence is applied to merge the information coming from texture and grey level image from the RGB bands. Several results from aerial and spatial images that support the technique are presented

  19. 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

  20. 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.

  1. Evaluation of Selected Features for CAR Detection in Aerial Images

    NASA Astrophysics Data System (ADS)

    Tuermer, S.; Leitloff, J.; Reinartz, P.; Stilla, U.

    2011-09-01

    The extraction of vehicles from aerial images provides a wide area traffic situation within a short time. Applications for the gathered data are various and reach from smart routing in the case of congestions to usability validation of roads in the case of disasters. The challenge of the vehicle detection task is finding adequate features which are capable to separate cars from other objects; especially those that look similar. We present an experiment where selected features show their ability of car detection. Precisely, Haar-like and HoG features are utilized and passed to the AdaBoost algorithm for calculating the final detector. Afterwards the classifying power of the features is accurately analyzed and evaluated. The tests a carried out on aerial data from the inner city of Munich, Germany and include small inner city roads with rooftops close by which raise the complexity factor.

  2. An improved algorithm of mask image dodging for aerial image

    NASA Astrophysics Data System (ADS)

    Zhang, Zuxun; Zou, Songbai; Zuo, Zhiqi

    2011-12-01

    The technology of Mask image dodging based on Fourier transform is a good algorithm in removing the uneven luminance within a single image. At present, the difference method and the ratio method are the methods in common use, but they both have their own defects .For example, the difference method can keep the brightness uniformity of the whole image, but it is deficient in local contrast; meanwhile the ratio method can work better in local contrast, but sometimes it makes the dark areas of the original image too bright. In order to remove the defects of the two methods effectively, this paper on the basis of research of the two methods proposes a balance solution. Experiments show that the scheme not only can combine the advantages of the difference method and the ratio method, but also can avoid the deficiencies of the two algorithms.

  3. 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.

  4. 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.

  5. 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

  6. 1. AERIAL VIEW, SHOWING MOBILE LAUNCHER. BASE IS CALLED LAUNCH ...

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

    1. AERIAL VIEW, SHOWING MOBILE LAUNCHER. BASE IS CALLED LAUNCH PLATFORM AND TOWER ON RIGHT IS CALLED LAUNCH UMBILICAL TOWER, (LUT). - Mobile Launcher One, Kennedy Space Center, Titusville, Brevard County, FL

  7. 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…

  8. Assessment of Photogrammetric Mapping Accuracy Based on Variation Flying Altitude Using Unmanned Aerial Vehicle

    NASA Astrophysics Data System (ADS)

    Udin, W. S.; Ahmad, A.

    2014-02-01

    Photogrammetry is the earliest technique used to collect data for topographic mapping. The recent development in aerial photogrammetry is the used of large format digital aerial camera for producing topographic map. The aerial photograph can be in the form of metric or non-metric imagery. The cost of mapping using aerial photogrammetry is very expensive. In certain application, there is a need to map small area with limited budget. Due to the development of technology, small format aerial photogrammetry technology has been introduced and offers many advantages. Currently, digital map can be extracted from digital aerial imagery of small format camera mounted on light weight platform such as unmanned aerial vehicle (UAV). This study utilizes UAV system for large scale stream mapping. The first objective of this study is to investigate the use of light weight rotary-wing UAV for stream mapping based on different flying height. Aerial photograph were acquired at 60% forward lap and 30% sidelap specifications. Ground control points and check points were established using Total Station technique. The digital camera attached to the UAV was calibrated and the recovered camera calibration parameters were then used in the digital images processing. The second objective is to determine the accuracy of the photogrammetric output. In this study, the photogrammetric output such as stereomodel in three dimensional (3D), contour lines, digital elevation model (DEM) and orthophoto were produced from a small stream of 200m long and 10m width. The research output is evaluated for planimetry and vertical accuracy using root mean square error (RMSE). Based on the finding, sub-meter accuracy is achieved and the RMSE value decreases as the flying height increases. The difference is relatively small. Finally, this study shows that UAV is very useful platform for obtaining aerial photograph and subsequently used for photogrammetric mapping and other applications.

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

    PubMed

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

    2014-01-01

    Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology. PMID:24892103

  10. 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.

  11. Performance Validation of High Resolution Digital Surface Models Generated by Dense Image Matching with the Aerial Images

    NASA Astrophysics Data System (ADS)

    Yastikli, N.; Bayraktar, H.; Erisir, Z.

    2014-11-01

    The digital surface models (DSM) are the most popular products to determine visible surface of Earth which includes all non-terrain objects such as vegetation, forest, and man-made constructions. The airborne light detection and ranging (LiDAR) is the preferred technique for high resolution DSM generation in local coverage. The automatic generation of the high resolution DSM is also possible with stereo image matching using the aerial images. The image matching algorithms usually rely on the feature based matching for DSM generation. First, feature points are extracted and then corresponding features are searched in the overlapping images. These image matching algorithms face with the problems in the areas which have repetitive pattern such as urban structure and forest. The recent innovation in camera technology and image matching algorithm enabled the automatic dense DSM generation for large scale city and environment modelling. The new pixel-wise matching approaches are generates very high resolution DSMs which corresponds to the ground sample distance (GSD) of the original images. The numbers of the research institutes and photogrammetric software vendors are currently developed software tools for dense DSM generation using the aerial images. This new approach can be used high resolution DSM generation for the larger cities, rural areas and forest even Nation-wide applications. In this study, the performance validation of high resolution DSM generated by pixel-wise dense image matching in part of Istanbul was aimed. The study area in Istanbul is including different land classes such as open areas, forest and built-up areas to test performance of dense image matching in different land classes. The obtained result from this performance validation in Istanbul test area showed that, high resolution DSM which corresponds to the ground sample distance (GSD) of original aerial image can be generated successfully by pixel-wise dense image matching using commercial and

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  13. 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.

  14. 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

  15. High-resolution EUV imaging tools for resist exposure and aerial image monitoring

    NASA Astrophysics Data System (ADS)

    Booth, M.; Brisco, O.; Brunton, A.; Cashmore, J.; Elbourn, P.; Elliner, G.; Gower, M.; Greuters, J.; Grunewald, P.; Gutierrez, R.; Hill, T.; Hirsch, J.; Kling, L.; McEntee, N.; Mundair, S.; Richards, P.; Truffert, V.; Wallhead, I.; Whitfield, M.; Hudyma, R.

    2005-05-01

    Key features are presented of two high-resolution EUV imaging tools: the MS-13 Microstepper wafer exposure and the RIM-13 reticle imaging microscope. The MS-13 has been developed for EUV resist testing and technology evaluation at the 32nm node and beyond, while the RIM-13 is designed for actinic aerial image monitoring of blank and patterned EUV reticles. Details of the design architecture, module layout, major subsystems and performance are presented for both tools.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  18. 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.

  19. 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.

  20. 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...

  1. Towards aerial natural gas leak detection system based on TDLAS

    NASA Astrophysics Data System (ADS)

    Liu, Shuyang; Zhou, Tao; Jia, Xiaodong

    2014-11-01

    Pipeline leakage is a complex scenario for sensing system due to the traditional high cost, low efficient and labor intensive detection scheme. TDLAS has been widely accepted as industrial trace gas detection method and, thanks to its high accuracy and reasonable size, it has the potential to meet pipeline gas leakage detection requirements if it combines with the aerial platform. Based on literature study, this paper discussed the possibility of applying aerial TDLAS principle in pipeline gas leak detection and the key technical foundation of implementing it. Such system is able to result in a high efficiency and accuracy measurement which will provide sufficient data in time for the pipeline leakage detection.

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

    PubMed

    Rosnell, Tomi; Honkavaara, Eija

    2012-01-01

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

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

    PubMed Central

    Rosnell, Tomi; Honkavaara, Eija

    2012-01-01

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

  4. 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.

  5. 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.

  6. D Classification of Crossroads from Multiple Aerial Images Using Markov Random Fields

    NASA Astrophysics Data System (ADS)

    Kosov, S.; Rottensteiner, F.; Heipke, C.; Leitloff, J.; Hinz, S.

    2012-08-01

    The precise classification and reconstruction of crossroads from multiple aerial images is a challenging problem in remote sensing. We apply the Markov Random Fields (MRF) approach to this problem, a probabilistic model that can be used to consider context in classification. A simple appearance-based model is combined with a probabilistic model of the co-occurrence of class label at neighbouring image sites to distinguish up to 14 different classes that are relevant for scenes containing crossroads. The parameters of these models are learnt from training data. We use multiple overlap aerial images to derive a digital surface model (DSM) and a true orthophoto without moving cars. From the DSM and the orthophoto we derive feature vectors that are used in the classification. One of the features is a car confidence value that is supposed to support the classification when the road surface is occluded by static cars. Our approach is evaluated on a dataset of airborne photos of an urban area by a comparison of the results to reference data. Whereas the method has problems in distinguishing classes having a similar appearance, it is shown to produce promising results if a reduced set of classes is considered, yielding an overall classification accuracy of 74.8%.

  7. Object-Based Analysis of Aerial Photogrammetric Point Cloud and Spectral Data for Land Cover Mapping

    NASA Astrophysics Data System (ADS)

    Debella-Gilo, M.; Bjørkelo, K.; Breidenbach, J.; Rahlf, J.

    2013-04-01

    The acquisition of 3D point data with the use of both aerial laser scanning (ALS) and matching of aerial stereo images coupled with advances in image processing algorithms in the past years provide opportunities to map land cover types with better precision than before. The present study applies Object-Based Image Analysis (OBIA) to 3D point cloud data obtained from matching of stereo aerial images together with spectral data to map land cover types of the Nord-Trøndelag county of Norway. The multi-resolution segmentation algorithm of the Definiens eCognition™ software is used to segment the scenes into homogenous objects. The objects are then classified into different land cover types using rules created based on the definitions given for each land cover type by the Norwegian Forest and Landscape Institute. The quality of the land cover map was evaluated using data collected in the field as part of the Norwegian National Forest Inventory. The results show that the classification has an overall accuracy of about 80% and a kappa index of about 0.65. OBIA is found to be a suitable method for utilizing 3D remote sensing data for land cover mapping in an effort to replace manual delineation methods.

  8. Computational inspection applied to a mask inspection system with advanced aerial imaging capability

    NASA Astrophysics Data System (ADS)

    Pang, Linyong; Peng, Danping; He, Lin; Chen, Dongxue; Dam, Thuc; Tolani, Vikram; Tam, Aviram; Staud, Wolf

    2010-03-01

    At the most advanced technology nodes, such as 32nm and 22nm, aggressive OPC and Sub-Resolution Assist Features (SRAFs) are required. However, their use results in significantly increased mask complexity, challenging mask defect dispositioning more than ever. To address these challenges in mask inspection and defect dispositioning, new mask inspection technologies have been developed that not only provide high resolution masks imaged at the same wavelength as the scanner, but that also provide aerial images by using both: software simulation and hardware emulation. The original mask patterns stored by the optics of mask inspection systems can be recovered using a patented algorithm based on the Level Set Method. More accurate lithography simulation models can be used to further evaluate defects on simulated resist patterns using the recovered mask pattern in high resolution and aerial mode. An automated defect classification based on lithography significance and local CD changes is also developed to disposition tens of thousands of potential defects in minutes, so that inspection throughput is not impacted.

  9. 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.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  12. 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.

  13. Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

    NASA Astrophysics Data System (ADS)

    Li, Xiaoxiao; Myint, Soe W.; Zhang, Yujia; Galletti, Chritopher; Zhang, Xiaoxiang; Turner, Billie L.

    2014-12-01

    Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.

  14. Semi-automated analysis of high-resolution aerial images to quantify docks in glacial lakes

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

    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 K^) 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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...

  19. 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.

  20. Three-Dimensional Building Reconstruction Using Images Obtained by Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Wefelscheid, C.; Hänsch, R.; Hellwich, O.

    2011-09-01

    Unmanned Aerial Vehicles (UAVs) offer several new possibilities in a wide range of applications. One example is the 3D reconstruction of buildings. In former times this was either restricted by earthbound vehicles to the reconstruction of facades or by air-borne sensors to generate only very coarse building models. This paper describes an approach for fully automatic image-based 3D reconstruction of buildings using UAVs. UAVs are able to observe the whole 3D scene and to capture images of the object of interest from completely different perspectives. The platform used by this work is a Falcon 8 octocopter from Ascending Technologies. A slightly modified high-resolution consumer camera serves as sensor for data acquisition. The final 3D reconstruction is computed offline after image acquisition and follows a reconstruction process originally developed for image sequences obtained by earthbound vehicles. The per- formance of the described method is evaluated on benchmark datasets showing that the achieved accuracy is high and even comparable with Light Detection and Ranging (LIDAR). Additionally, the results of the application of the complete processing-chain starting at image acquisition and ending in a dense surface-mesh are presented and discussed.

  1. Aerial image measurement technique for automated reticle defect disposition (ARDD) in wafer fabs

    NASA Astrophysics Data System (ADS)

    Zibold, Axel M.; Schmid, Rainer M.; Stegemann, B.; Scheruebl, Thomas; Harnisch, Wolfgang; Kobiyama, Yuji

    2004-08-01

    The Aerial Image Measurement System (AIMS)* for 193 nm lithography emulation has been brought into operation successfully worldwide. A second generation system comprising 193 nm AIMS capability, mini-environment and SMIF, the AIMS fab 193 plus is currently introduced into the market. By adjustment of numerical aperture (NA), illumination type and partial illumination coherence to match the conditions in 193 nm steppers or scanners, it can emulate the exposure tool for any type of reticles like binary, OPC and PSM down to the 65 nm node. The system allows a rapid prediction of wafer printability of defects or defect repairs, and critical features, like dense patterns or contacts on the masks without the need to perform expensive image qualification consisting of test wafer exposures followed by SEM measurements. Therefore, AIMS is a mask quality verification standard for high-end photo masks and established in mask shops worldwide. The progress on the AIMS technology described in this paper will highlight that besides mask shops there will be a very beneficial use of the AIMS in the wafer fab and we propose an Automated Reticle Defect Disposition (ARDD) process. With smaller nodes, where design rules are 65 nm or less, it is expected that smaller defects on reticles will occur in increasing numbers in the wafer fab. These smaller mask defects will matter more and more and become a serious yield limiting factor. With increasing mask prices and increasing number of defects and severability on reticles it will become cost beneficial to perform defect disposition on the reticles in wafer production. Currently ongoing studies demonstrate AIMS benefits for wafer fab applications. An outlook will be given for extension of 193 nm aerial imaging down to the 45 nm node based on emulation of immersion scanners.

  2. U.S. DOE, Kazakhstan government launch aerial imaging project

    SciTech Connect

    Hamm, J.

    1997-10-01

    The US Department of Energy (DOE) and the Kazakhstan government have launched a breakthrough science and technology mission to use DOE technology developed to detect weapons proliferation to search for oil and mineral reserves in Kazakhstan. The Pacific Northwest National Laboratory is leading the research effort, which began in June. This mission to conduct airborne imaging flights over Kazakhstan is the result of a recently signed agreement between Pacific Northwest and Earth Search Sciences Inc., a remote sensing firm based in Idaho, to look for oil and mineral deposits in the Republic of Kazakhstan in central Asia. It is the first time this technology will be used outside the United States.

  3. 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.

  4. 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...

  5. Crop Status Monitoring using Multispectral and Thermal Imaging systems for Accessible Aerial Platforms

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agricultural aircraft and unmanned aerial systems (UAS) are easily scheduled and accessible remote sensing platforms. Canopy temperature data were taken with an Electrophysics PV-320T thermal imaging camera mounted in agricultural aircraft. Weather data and soil water potential were monitored and th...

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. RIM-13: A high-resolution imaging tool for aerial image monitoring of patterned and blank EUV reticles

    NASA Astrophysics Data System (ADS)

    Booth, M.; Brunton, A.; Cashmore, J.; Elbourn, P.; Elliner, G.; Gower, M.; Greuters, J.; Hirsch, J.; Kling, L.; McEntee, N.; Richards, P.; Truffert, V.; Wallhead, I.; Whitfield, M.

    2006-03-01

    Key features of the RIM-13 EUV actinic reticle imaging microscope are summarised. This is a tool which generates aerial images from blank or patterned EUV masks, emulating the illumination and projection optics of an exposure tool. Such images of mask defects, acquired by a CCD camera, are analysed using the tool software to predict their effect on resist exposure. Optical, mechanical and software performance of the tool are reported.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Zen, Luan; Tan, Jiubin; Zhao, Zhongwen

    2008-10-01

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

  13. 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

  14. 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.

  15. 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.

  16. Miniaturization of sub-meter resolution hyperspectral imagers on unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Hill, Samuel L.; Clemens, Peter

    2014-05-01

    Traditional airborne environmental monitoring has frequently deployed hyperspectral imaging as a leading tool for characterizing and analyzing a scene's critical spectrum-based signatures for applications in agriculture genomics and crop health, vegetation and mineral monitoring, and hazardous material detection. As the acceptance of hyperspectral evaluation grows in the airborne community, there has been a dramatic trend in moving the technology from use on midsize aircraft to Unmanned Aerial Systems (UAS). The use of UAS accomplishes a number of goals including the reduction in cost to run multiple seasonal evaluations over smaller but highly valuable land-areas, the ability to use frequent data collections to make rapid decisions on land management, and the improvement of spatial resolution by flying at lower altitudes (< 150 m). Despite this trend, there are several key parameters affecting the use of traditional hyperspectral instruments in UAS with payloads less than 0.5 kg (~1lb) where size, weight and power (SWaP) are critical to how high and how far a given UAS can fly. Additionally, on many of the light-weight UAS, users are frequently trying to capture data from one or more instruments to augment the hyperspectral data collection, thus reducing the amount of SWaP available to the hyperspectral instrumentation. The following manuscript will provide an analysis on a newly-developed miniaturized hyperspectral imaging platform that provides full hyperspectral resolution and traditional hyperspectral capabilities without sacrificing performance to accommodate the decreasing SWaP of smaller and smaller UAS platforms.

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

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

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

  18. 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.

  19. Orientation and Dense Reconstruction of Unordered Terrestrial and Aerial Wide Baseline Image Sets

    NASA Astrophysics Data System (ADS)

    Bartelsen, J.; Mayer, H.; Hirschmüller, H.; Kuhn, A.; Michelini, M.

    2012-07-01

    In this paper we present an approach for detailed and precise automatic dense 3D reconstruction using images from consumer cameras. The major difference between our approach and many others is that we focus on wide-baseline image sets. We have combined and improved several methods, particularly, least squares matching, RANSAC, scale-space maxima and bundle adjustment, for robust matching and parameter estimation. Point correspondences and the five-point algorithm lead to relative orientation. Due to our robust matching method it is possible to orient images under much more unfavorable conditions, for instance concerning illumination changes or scale differences, than for often used operators such as SIFT. For dense reconstruction, we use our orientation as input for Semiglobal Matching (SGM) resulting into dense depth images. The latter can be fused into a 2.5D model for eliminating the redundancy of the highly overlapping depth images. However, some applications require full 3D models. A solution to this problem is part of our current work, for which preliminary results are presented in this paper. With very small unmanned aerial systems (Micro UAS) it is possible to acquire images which have a perspective similar to terrestrial images and can thus be combined with them. Such a combination is useful for an almost complete 3D reconstruction of urban scenes. We have applied our approach to several hundred aerial and terrestrial images and have generated detailed 2.5D and 3D models of urban areas.

  20. 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.

  1. 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

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

    PubMed

    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

  3. Large-scale aerial images capture details of invasive plant populations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Satellite and aerial remote sensing have been successfully used to measure invasive weed infestations over very large areas, but have limited resolution. Ground-based methods have provided detailed measurements of invasive weeds, but can measure only limited areas. Here we test a novel approach th...

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

    PubMed Central

    Terletzky, Pat; Ramsey, Robert Douglas

    2014-01-01

    Our research presents a proof-of-concept that explores a new and innovative method to identify large animals in aerial imagery with single day image differencing. We acquired two aerial images of eight fenced pastures and conducted a principal component analysis of each image. We then subtracted the first principal component of the two pasture images followed by heuristic thresholding to generate polygons. The number of polygons represented the number of potential cattle (Bos taurus) and horses (Equus caballus) in the pasture. The process was considered semi-automated because we were not able to automate the identification of spatial or spectral thresholding values. Imagery was acquired concurrently with ground counts of animal numbers. Across the eight pastures, 82% of the animals were correctly identified, mean percent commission was 53%, and mean percent omission was 18%. The high commission error was due to small mis-alignments generated from image-to-image registration, misidentified shadows, and grouping behavior of animals. The high probability of correctly identifying animals suggests short time interval image differencing could provide a new technique to enumerate wild ungulates occupying grassland ecosystems, especially in isolated or difficult to access areas. To our knowledge, this was the first attempt to use standard change detection techniques to identify and enumerate large ungulates. PMID:24454827

  5. Mapping potential Blanding's turtle habitat using aerial orthophotographic imagery and object based classification

    NASA Astrophysics Data System (ADS)

    Barker, Rebecca

    Blanding's turtle (Emydoidea blandingii) is a threatened species in southern Quebec that is being inventoried to determine abundance and potential habitat by the Quebec Ministry of Natural Resources and Wildlife. In collaboration with that program and using spring leaf-off aerial orthophotos of Gatineau Park, attributes associated with known habitat criteria were analyzed: wetlands with open water, vegetation mounds for camouflage and thermoregulation, and logs for spring sun-basking. Pixel-based classification to separate wetlands from other land cover types was followed by object-based segmentation and rule-based classification of within--wetland vegetation and logs. Classifications integrated several image characteristics including texture, context, shape, area and spectral attributes. Field data and visual interpretation showed the accuracies of wetland and within wetland habitat feature classifications to be over 82.5%. The wetland classification results were used to develop a ranked potential habitat suitability map for Blanding's turtle that can be employed in conservation planning and management.

  6. Seasonal landslide mapping and estimation of landslide mobilization rates using aerial and satellite images

    NASA Astrophysics Data System (ADS)

    Fiorucci, F.; Cardinali, M.; Carlà, R.; Rossi, M.; Mondini, A. C.; Santurri, L.; Ardizzone, F.; Guzzetti, F.

    2011-06-01

    We tested the possibility of using digital, color aerial ortho-photographs and monoscopic, panchromatic satellite images of comparable spatial and radiometric resolution, to map recent landslides in Italy and to update existing measures of landslide mobilization. In a 90-km 2 area in Umbria, central Apennines, rainfall resulted in abundant landslides in the period from September 2004 to June 2005. Analysis of the rainfall record determined the approximate dates of landslide occurrence and revealed that the slope failures occurred in response to moderately wet rainfall periods. The slope failures occurred primarily in cultivated terrain and left subtle morphological and land cover signatures, making the recognition and mapping of the individual landslides problematic. Despite the difficulty with the identification of the landslides without the use of stereoscopic visualization, visual analysis of the aerial and satellite images allowed mapping 457 new landslides, ranging in area 3.0 × 10 1 < AL < 2.5 × 10 4 m 2, for a total landslide area ALT = 6.92 × 10 5 m 2. To identify the landslides, the investigators adopted the interpretation criteria commonly used to identify and map landslides on aerial photography. The result confirms that monoscopic, very high resolution images taken by airborne and satellite sensors can be used to prepare landslide maps even where slope failures are difficult to detect, provided the imagery has sufficient geometric and radiometric resolutions. The different dates of the aerial (March 2005) and the satellite (June-July 2005) images allowed the temporal segmentation of the landslide information, and studying the statistics of landslide area and volume for different periods. Compared to pre-existing information on the abundance and size of the landslides in the area, the inventory obtained by studying the aerial and satellite images proved more complete. The new mapping showed 145% more landslides and 85% more landslide area than a pre

  7. Two matrix approaches for aerial image formation obtained by extending and modifying the transmission cross coefficients.

    PubMed

    Yamazoe, Kenji

    2010-06-01

    This paper physically compares two different matrix representations of partially coherent imaging with the introduction of matrices E and Z, containing the source, object, and pupil. The matrix E is obtained by extending the Hopkins transmission cross coefficient (TCC) approach such that the pupil function is shifted while the matrix Z is obtained by shifting the object spectrum. The aerial image I can be written as a convex quadratic form I = = , where |phi> is a column vector representing plane waves. It is shown that rank(Z) < or = rank(E) = rank(T) = N, where T is the TCC matrix and N is the number of the point sources for a given unpolarized illumination. Therefore, the matrix Z requires fewer than N eigenfunctions for a complete aerial image formation, while the matrix E or T always requires N eigenfunctions. More importantly, rank(Z) varies depending on the degree of coherence determined by the von Neumann entropy, which is shown to relate to the mutual intensity. For an ideal pinhole as an object, emitting spatially coherent light, only one eigenfunction--i.e., the pupil function--is enough to describe the coherent imaging. In this case, we obtain rank(Z) = 1 and the pupil function as the only eigenfunction regardless of the illumination. However, rank(E) = rank(T) = N even when the object is an ideal pinhole. In this sense, aerial image formation with the matrix Z is physically more meaningful than with the matrix E. The matrix Z is decomposed as B(dagger)B, where B is a singular matrix, suggesting that the matrix B as well as Z is a principal operator characterizing the degree of coherence of the partially coherent imaging. PMID:20508699

  8. 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.

  9. 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.

  10. 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.

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

    PubMed

    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. PMID:12801180

  12. 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.

  13. Knowledge-based understanding of aerial surveillance video

    NASA Astrophysics Data System (ADS)

    Cheng, Hui; Butler, Darren

    2006-05-01

    Aerial surveillance has long been used by the military to locate, monitor and track the enemy. Recently, its scope has expanded to include law enforcement activities, disaster management and commercial applications. With the ever-growing amount of aerial surveillance video acquired daily, there is an urgent need for extracting actionable intelligence in a timely manner. Furthermore, to support high-level video understanding, this analysis needs to go beyond current approaches and consider the relationships, motivations and intentions of the objects in the scene. In this paper we propose a system for interpreting aerial surveillance videos that automatically generates a succinct but meaningful description of the observed regions, objects and events. For a given video, the semantics of important regions and objects, and the relationships between them, are summarised into a semantic concept graph. From this, a textual description is derived that provides new search and indexing options for aerial video and enables the fusion of aerial video with other information modalities, such as human intelligence, reports and signal intelligence. Using a Mixture-of-Experts video segmentation algorithm an aerial video is first decomposed into regions and objects with predefined semantic meanings. The objects are then tracked and coerced into a semantic concept graph and the graph is summarized spatially, temporally and semantically using ontology guided sub-graph matching and re-writing. The system exploits domain specific knowledge and uses a reasoning engine to verify and correct the classes, identities and semantic relationships between the objects. This approach is advantageous because misclassifications lead to knowledge contradictions and hence they can be easily detected and intelligently corrected. In addition, the graph representation highlights events and anomalies that a low-level analysis would overlook.

  14. 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.

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

    NASA Astrophysics Data System (ADS)

    Hill, Samuel L.; Clemens, Peter

    2015-06-01

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

  16. Underwater binocular imaging of aerial objects versus the position of eyes relative to the flat water surface.

    PubMed

    Barta, András; Horváth, Gábor

    2003-12-01

    The apparent position, size, and shape of aerial objects viewed binocularly from water change as a result of the refraction of light at the water surface. Earlier studies of the refraction-distorted structure of the aerial binocular visual field of underwater observers were restricted to either vertically or horizontally oriented eyes. Here we calculate the position of the binocular image point of an aerial object point viewed by two arbitrarily positioned underwater eyes when the water surface is flat. Assuming that binocular image fusion is performed by appropriate vergent eye movements to bring the object's image onto the foveae, the structure of the aerial binocular visual field is computed and visualized as a function of the relative positions of the eyes. We also analyze two erroneous representations of the underwater imaging of aerial objects that have occurred in the literature. It is demonstrated that the structure of the aerial binocular visual field of underwater observers distorted by refraction is more complex than has been thought previously. PMID:14686517

  17. Multidirectional Building Detection in Aerial Images Without Shape Templates

    NASA Astrophysics Data System (ADS)

    Manno-Kovacs, A.; Sziranyi, T.

    2013-05-01

    The aim of this paper is to exploit orientation information of an urban area for extracting building contours without shape templates. Unlike using shape templates, these given contours describe more variability and reveal the fine details of the building outlines, resulting in a more accurate detection process, which is beneficial for many tasks, like map updating and city planning. According to our assumption, orientation of the closely located buildings is coherent, it is related to the road network, therefore adaptation of this information can lead to more efficient building detection results. The introduced method first extracts feature points for representing the urban area. Orientation information in the feature point neighborhoods is analyzed to define main orientations. Based on orientation information, the urban area is classified into different directional clusters. The edges of the classified building groups are then emphasized with shearlet based edge detection method, which is able to detect edges only in the main directions, resulting in an efficient connectivity map. In the last step, with the fusion of the feature points and connectivity map, building contours are detected with a non-parametric active contour method.

  18. 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 ...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

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

    USGS Publications Warehouse

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

    2013-01-01

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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  6. Automatic Road Extraction Based on Integration of High Resolution LIDAR and Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Rahimi, S.; Arefi, H.; Bahmanyar, R.

    2015-12-01

    In recent years, the rapid increase in the demand for road information together with the availability of large volumes of high resolution Earth Observation (EO) images, have drawn remarkable interest to the use of EO images for road extraction. Among the proposed methods, the unsupervised fully-automatic ones are more efficient since they do not require human effort. Considering the proposed methods, the focus is usually to improve the road network detection, while the roads' precise delineation has been less attended to. In this paper, we propose a new unsupervised fully-automatic road extraction method, based on the integration of the high resolution LiDAR and aerial images of a scene using Principal Component Analysis (PCA). This method discriminates the existing roads in a scene; and then precisely delineates them. Hough transform is then applied to the integrated information to extract straight lines; which are further used to segment the scene and discriminate the existing roads. The roads' edges are then precisely localized using a projection-based technique, and the round corners are further refined. Experimental results demonstrate that our proposed method extracts and delineates the roads with a high accuracy.

  7. Digital Camera Calibration Using Images Taken from AN Unmanned Aerial Vehicle

    NASA Astrophysics Data System (ADS)

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

    2011-09-01

    For calibrating the camera, an accurate determination of the interior orientation parameters is needed. For more accurate results, the calibration images should be taken under conditions that are similar to the field samples. The aim of this work is the establishment of an efficient and accurate digital camera calibration method to be used in particular working conditions, as it can be found with our UAV (Unmanned Aerial Vehicle) photogrammetric projects. The UAV used in this work was md4-200 modelled by Microdrones. The microdrone is also equipped with a standard digital non- metric camera, the Pentax Optio A40 camera. To find out the interior orientation parameters of the digital camera, two calibration methods were done. A lab calibration based on a flat pattern and a field calibration were fulfilled. To carry out the calibration, Photomodeler Scanner software was used in both cases. The lab calibration process was completely automatic using a calibration grid. The focal length was fixed at widest angle and the network included a total of twelve images with± 90º roll angles. In order to develop the field calibration, a flight plan was programmed including a total of twelve images. In the same way as in the lab calibration, the focal length was fixed at widest angle. The field test used in the study was a flat surface located on the University of Almería campus and a set of 67 target points were placed. The calibration field area was 25 × 25 m approximately and the altitude flight over ground was 50 m. After the software processing, the camera calibration parameter values were obtained. The paper presents the process, the results and the accuracy of these calibration methods. The field calibration method reduced the final total error obtained in the previous lab calibration. Furthermore the overall RMSs obtained from both methods are similar. Therefore we will apply the field calibration results to all our photogrammetric projects in which the flight high

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  9. Mass Balance of Glaciers In Southern Chile, Based On Dems From Aster and Aerial Photographs

    NASA Astrophysics Data System (ADS)

    Rivera, A.; Casassa, G.; Bown, F.; Fernandez, A.

    The glaciers located in the Chilean southern Andes region (41-51S) have been re- treating and shrinking during most of the last century, in response to a climate warm- ing trend recognised in many climatic stations of the country. During recent years, several calving and small mountain glaciers have been analysed, in an attempt to cor- relate the short historical glacier variation (no longer than 150 years) with long term dendrochronological series (from 300 to 1000 years). The aim of this analysis is to un- derstand climate change during the last millennia, as well as the mechanisms of glacier response to such climatic changes. In this context, mass balance studies are one of the most important approaches to determine the specific relationship of glaciers to annual and decadal climatic changes. In Chile, only one glacier (glaciar Echaurren, 33S) has been systematically measured since 1975, generating the longest mass balance series of the country. To account for the mass balance of glaciers in the southern region of Chile, a geodetic method is presented, based upon the comparison of digital elevation models (DEM) obtained from aerial photographs and ASTER imagery from different dates. This method have been applied to glaciar Chico located at 49S in the Southern Patagonia Icefield, where we have generated DEMs from aerial photographs of 1975 and 1995, as well as one DEM from an ASTER image of October 2001. The DEMs are geo-referenced to a network of GPS points, measured in several field campaigns carried out during recent years at rock outcrops and in the accumulation area of the glacier. The last campaign was done during September and October 2001, allowing a high accuracy ground control validation for DEM derived from the contemporary ASTER image. The mass balance analysis is complemented with frontal variations derived from Landsat TM imagery, as well as field data and aerial photographs. One preliminary result of this study shows a consistent ice thinning, at

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

    NASA Astrophysics Data System (ADS)

    Markov, Eugene

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

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

    SciTech Connect

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

    2011-02-21

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

  15. Demonstration of a multimode longwave infrared imaging system on an unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Jones, Terry L.; Romanski, John G.; Buckley, John J.; Girata, Anthony J.

    1999-07-01

    The RISTA II sensor was integrated into the Altus Unmanned Aerial Vehicle (UAV) and flown over Camp Roberts and Ft. Hunter Ligget, CA in July 1998. The RISTA II demonstration system consisted of a long-wave IR imager, a digital data link, and a ground processing facility (GPF) containing an aided target recognizer, data storage devices, and operator workstations. Imagery was compressed on the UAV and sent on the GPF over a 10.71 Mbit per second digital data link. Selected image frames from the GPF were sent near real-time over a T1 link to observers in Rosslyn, VA. The sensor operated in a variety of scanning and framing modes. Both manual and automatic sensor pointing were demonstrated. Seven flights were performed at altitudes up to 7500m and range sup to 60 km from the GPF. Applicability to numerous military and civilian scenarios was demonstrated.

  16. Modelling and representation issues in automated feature extraction from aerial and satellite images

    NASA Astrophysics Data System (ADS)

    Sowmya, Arcot; Trinder, John

    New digital systems for the processing of photogrammetric and remote sensing images have led to new approaches to information extraction for mapping and Geographic Information System (GIS) applications, with the expectation that data can become more readily available at a lower cost and with greater currency. Demands for mapping and GIS data are increasing as well for environmental assessment and monitoring. Hence, researchers from the fields of photogrammetry and remote sensing, as well as computer vision and artificial intelligence, are bringing together their particular skills for automating these tasks of information extraction. The paper will review some of the approaches used in knowledge representation and modelling for machine vision, and give examples of their applications in research for image understanding of aerial and satellite imagery.

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

    NASA Astrophysics Data System (ADS)

    Kubalska, J. L.; Preuss, R.

    2013-12-01

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

  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. 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

  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. Semantic Segmentation of Aerial Images in Urban Areas with Class-Specific Higher-Order Cliques

    NASA Astrophysics Data System (ADS)

    Montoya-Zegarra, J. A.; Wegner, J. D.; Ladický, L.; Schindler, K.

    2015-03-01

    In this paper we propose an approach to multi-class semantic segmentation of urban areas in high-resolution aerial images with classspecific object priors for buildings and roads. What makes model design challenging are highly heterogeneous object appearances and shapes that call for priors beyond standard smoothness or co-occurrence assumptions. The data term of our energy function consists of a pixel-wise classifier that learns local co-occurrence patterns in urban environments. To specifically model the structure of roads and buildings, we add high-level shape representations for both classes by sampling large sets of putative object candidates. Buildings are represented by sets of compact polygons, while roads are modeled as a collection of long, narrow segments. To obtain the final pixel-wise labeling, we use a CRF with higher-order potentials that balances the data term with the object candidates. We achieve overall labeling accuracies of > 80%.

  2. 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. PMID:26328703

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  4. Stereoscopic Imaging for Obstacle Detection Onboard Low-Flying Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Hanna, Emad

    Obstacle detection for low-flying unmanned aerial vehicles (UAVs) poses unique engineering challenges in terms of real-time implementation as well as system accuracy. Of all the available techniques for carrying out this task, optical sensors stand out as an inexpensive, lightweight and reliable solution. Image processing methods are used to analyze the images captured by the UAV camera(s) and to generate information pertaining to the location and motion of the obstacles in the field of view. These methods, however, can be computationally intensive and must be optimized if they are to be implemented in a moving vehicle. Additionally, the measurement of distance usually requires a high level of calibration before the results are useful. This thesis proposes a calibration method rooted in image data analysis and shows how this can be used to accurately predict the distance to obstacles. An algorithm tailored specifically to low-flying UAVs (Sparse Edge Reconstruction) is presented. Both the calibration method and the algorithm were used to analyze video gathered on a low-altitude test flight.

  5. 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.

  6. Object-based spatiotemporal analysis of vine canopy vigor using an inexpensive unmanned aerial vehicle remote sensing system

    NASA Astrophysics Data System (ADS)

    Mathews, Adam J.

    2014-01-01

    Remotely sensed imagery provides a rapid assessment of spatial variability in grapevine canopy vigor that correlates with crop performance. Unmanned aerial vehicles (UAVs) provide a low-cost image acquisition platform with high spatial and temporal resolutions. Using a UAV and digital cameras, aerial images of a Texas vineyard were captured at postflowering, veraison, and harvest. Imagery was processed to generate orthophotos in units of reflectance, which were then segmented to extract per-vine estimates of canopy area (planimetric extent) and normalized difference vegetation index (NDVI)-based canopy density. Derived canopy area and density values were compared to the harvest variables of number of clusters, cluster size, and yield to explore correlations. Planimetrically derived canopy area yielded significant, positive relationships, whereas NDVI-based canopy density exhibited no significant relationships due to sensor-related radiometric inaccuracy. A vine performance index was calculated to map spatial variation in canopy vigor for the entire growing season. Future management zones were delineated using spatial grouping analysis.

  7. 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.

  8. 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.

  9. Vision based guidance and flight control in problems of aerial tracking

    NASA Astrophysics Data System (ADS)

    Stepanyan, Vahram

    The use of visual sensors in providing the necessary information for the autonomous guidance and navigation of the unmanned-air vehicles (UAV) or micro-air vehicles (MAV) applications is inspired by biological systems and is motivated first of all by the reduction of the navigational sensor cost. Also, visual sensors can be more advantageous in military operations since they are difficult to detect. However, the design of a reliable guidance, navigation and control system for aerial vehicles based only on visual information has many unsolved problems, ranging from hardware/software development to pure control-theoretical issues, which are even more complicated when applied to the tracking of maneuvering unknown targets. This dissertation describes guidance law design and implementation algorithms for autonomous tracking of a flying target, when the information about the target's current position is obtained via a monocular camera mounted on the tracking UAV (follower). The visual information is related to the target's relative position in the follower's body frame via the target's apparent size, which is assumed to be constant, but otherwise unknown to the follower. The formulation of the relative dynamics in the inertial frame requires the knowledge of the follower's orientation angles, which are assumed to be known. No information is assumed to be available about the target's dynamics. The follower's objective is to maintain a desired relative position irrespective of the target's motion. Two types of guidance laws are designed and implemented in the dissertation. The first one is a smooth guidance law that guarantees asymptotic tracking of a target, the velocity of which is viewed as a time-varying disturbance, the change in magnitude of which has a bounded integral. The second one is a smooth approximation of a discontinuous guidance law that guarantees bounded tracking with adjustable bounds when the target's acceleration is viewed as a bounded but otherwise

  10. 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

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    McLeod, Tara

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

  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. Registration of Laser Scanning Point Clouds and Aerial Images Using either Artificial or Natural Tie Features

    NASA Astrophysics Data System (ADS)

    Rönnholm, P.; Haggrén, H.

    2012-07-01

    Integration of laser scanning data and photographs is an excellent combination regarding both redundancy and complementary. Applications of integration vary from sensor and data calibration to advanced classification and scene understanding. In this research, only airborne laser scanning and aerial images are considered. Currently, the initial registration is solved using direct orientation sensors GPS and inertial measurements. However, the accuracy is not usually sufficient for reliable integration of data sets, and thus the initial registration needs to be improved. A registration of data from different sources requires searching and measuring of accurate tie features. Usually, points, lines or planes are preferred as tie features. Therefore, the majority of resent methods rely highly on artificial objects, such as buildings, targets or road paintings. However, in many areas no such objects are available. For example in forestry areas, it would be advantageous to be able to improve registration between laser data and images without making additional ground measurements. Therefore, there is a need to solve registration using only natural features, such as vegetation and ground surfaces. Using vegetation as tie features is challenging, because the shape and even location of vegetation can change because of wind, for example. The aim of this article was to compare registration accuracies derived by using either artificial or natural tie features. The test area included urban objects as well as trees and other vegetation. In this area, two registrations were performed, firstly, using mainly built objects and, secondly, using only vegetation and ground surface. The registrations were solved applying the interactive orientation method. As a result, using artificial tie features leaded to a successful registration in all directions of the coordinate system axes. In the case of using natural tie features, however, the detection of correct heights was difficult causing

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

    SciTech Connect

    Cheriyadat, Anil M

    2011-01-01

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

  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. 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).

  18. 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.

  19. An Integrated Photogrammetric and Spatial Database Management System for Producing Fully Structured Data Using Aerial and Remote Sensing Images

    PubMed Central

    Ahmadi, Farshid Farnood; Ebadi, Hamid

    2009-01-01

    3D spatial data acquired from aerial and remote sensing images by photogrammetric techniques is one of the most accurate and economic data sources for GIS, map production, and spatial data updating. However, there are still many problems concerning storage, structuring and appropriate management of spatial data obtained using these techniques. According to the capabilities of spatial database management systems (SDBMSs); direct integration of photogrammetric and spatial database management systems can save time and cost of producing and updating digital maps. This integration is accomplished by replacing digital maps with a single spatial database. Applying spatial databases overcomes the problem of managing spatial and attributes data in a coupled approach. This management approach is one of the main problems in GISs for using map products of photogrammetric workstations. Also by the means of these integrated systems, providing structured spatial data, based on OGC (Open GIS Consortium) standards and topological relations between different feature classes, is possible at the time of feature digitizing process. In this paper, the integration of photogrammetric systems and SDBMSs is evaluated. Then, different levels of integration are described. Finally design, implementation and test of a software package called Integrated Photogrammetric and Oracle Spatial Systems (IPOSS) is presented. PMID:22574014

  20. An integrated photogrammetric and spatial database management system for producing fully structured data using aerial and remote sensing images.

    PubMed

    Ahmadi, Farshid Farnood; Ebadi, Hamid

    2009-01-01

    3D spatial data acquired from aerial and remote sensing images by photogrammetric techniques is one of the most accurate and economic data sources for GIS, map production, and spatial data updating. However, there are still many problems concerning storage, structuring and appropriate management of spatial data obtained using these techniques. According to the capabilities of spatial database management systems (SDBMSs); direct integration of photogrammetric and spatial database management systems can save time and cost of producing and updating digital maps. This integration is accomplished by replacing digital maps with a single spatial database. Applying spatial databases overcomes the problem of managing spatial and attributes data in a coupled approach. This management approach is one of the main problems in GISs for using map products of photogrammetric workstations. Also by the means of these integrated systems, providing structured spatial data, based on OGC (Open GIS Consortium) standards and topological relations between different feature classes, is possible at the time of feature digitizing process. In this paper, the integration of photogrammetric systems and SDBMSs is evaluated. Then, different levels of integration are described. Finally design, implementation and test of a software package called Integrated Photogrammetric and Oracle Spatial Systems (IPOSS) is presented. PMID:22574014

  1. Image-based monitoring to measure ecological change in rangelands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High-resolution image-based methods can increase the speed and accuracy of ecological monitoring while reducing monitoring costs. We evaluated the efficacy of systematic aerial and ground sampling protocols to detect stocking-rate differences across 130 ha of shortgrass prairie. Manual and automated...

  2. 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

  3. 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

  4. 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.

  5. Detection of building changes from aerial images and light detection and ranging (LIDAR) data

    NASA Astrophysics Data System (ADS)

    Chen, Liang-Chien; Lin, Li-Jer

    2010-11-01

    Building models are built to provide three-dimensional (3-D) spatial information, which is needed in a variety of applications including city planning, construction management, location-based services of urban infrastructures, and the like. However, 3-D building models have to be updated on a timely manner to meet the changing demand. Rather than reconstructing building models for the entire area, it would be more convenient and effective to only update parts of the areas where there were changes. This paper aims at developing a new method, namely double-threshold strategy, to find such changes within 3-D building models in the region of interest with the aid of light detection and ranging (LIDAR) data. The proposed modeling scheme comprises three steps, namely, data pre-processing, change detection in building areas, and validation. In the first step for data pre-processing, data registration was carried out based on multi-source data. The second step for data pre-processing requires using the triangulation of an irregular network of data points collected by Light Detection And Ranging (LIDAR), focusing on those locations containing walls or other above-ground objects that were ever removed. Then, change detection in the building models can be made possible for finding differences in height by comparing the LIDAR point measurements and the estimates of the building models. The results may be further refined using spectral and feature information collected from aerial imagery. A double-threshold strategy was applied to cope with the highly sensitive thresholding often encountered when using the rule-based approach. Finally, ground truth data were used for model validation. Research findings clearly indicate that the double-threshold strategy improves the overall accuracy from 93.1% to 95.9%.

  6. Draper Laboratory small autonomous aerial vehicle

    NASA Astrophysics Data System (ADS)

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

    1997-06-01

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

  7. 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.

  8. 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...

  9. 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...

  10. 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.

  11. 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...

  12. a Uav Based Close-Range Rapid Aerial Monitoring System for Emergency Responses

    NASA Astrophysics Data System (ADS)

    Choi, K.; Lee, I.

    2011-09-01

    As the occurrences and scales of disasters and accidents have been increased due to the global warming, the terrorists' attacks, and many other reasons, the demand for rapid responses for the emergent situations also has been thus ever-increasing. These emergency responses are required to be customized to each individual site for more effective management of the emergent situations. These requirements can be satisfied with the decisions based on the spatial changes on the target area, which should be detected immediately or in real-time. Aerial monitoring without human operators is an appropriate means because the emergency areas are usually inaccessible. Therefore, a UAV is a strong candidate as the platform for the aerial monitoring. In addition, the sensory data from the UAV system usually have higher resolution than other system because the system can operate at a lower altitude. If the transmission and processing of the data could be performed in real-time, the spatial changes of the target area can be detected with high spatial and temporal resolution by the UAV rapid mapping systems. As a result, we aim to develop a rapid aerial mapping system based on a UAV, whose key features are the effective acquisition of the sensory data, real-time transmission and processing of the data. In this paper, we will introduce the general concept of our system, including the main features, intermediate results, and explain our real-time sensory data georeferencing algorithm which is a core for prompt generation of the spatial information from the sensory data.

  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. 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

  15. 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

  16. 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.

  17. Auto-measurement system of aerial camera lens' resolution based on orthogonal linear CCD

    NASA Astrophysics Data System (ADS)

    Zhao, Yu-liang; Zhang, Yu-ye; Ding, Hong-yi

    2010-10-01

    The resolution of aerial camera lens is one of the most important camera's performance indexes. The measurement and calibration of resolution are important test items in in maintenance of camera. The traditional method that is observing resolution panel of collimator rely on human's eyes using microscope and doing some computing. The method is of low efficiency and susceptible to artificial factors. The measurement results are unstable, too. An auto-measurement system of aerial camera lens' resolution, which uses orthogonal linear CCD sensor as the detector to replace reading microscope, is introduced. The system can measure automatically and show result real-timely. In order to measure the smallest diameter of resolution panel which could be identified, two orthogonal linear CCD is laid on the imaging plane of measured lens and four intersection points are formed on the orthogonal linear CCD. A coordinate system is determined by origin point of the linear CCD. And a circle is determined by four intersection points. In order to obtain the circle's radius, firstly, the image of resolution panel is transformed to pulse width of electric signal which is send to computer through amplifying circuit and threshold comparator and counter. Secondly, the smallest circle would be extracted to do measurement. The circle extraction made using of wavelet transform which has character of localization in the domain of time and frequency and has capability of multi-scale analysis. Lastly, according to the solution formula of lens' resolution, we could obtain the resolution of measured lens. The measuring precision on practical measurement is analyzed, and the result indicated that the precision will be improved when using linear CCD instead of reading microscope. Moreover, the improvement of system error is determined by the pixel's size of CCD. With the technique of CCD developed, the pixel's size will smaller, the system error will be reduced greatly too. So the auto

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

    NASA Astrophysics Data System (ADS)

    Rutzinger, Martin; Bremer, Magnus; Ragg, Hansjörg

    2013-04-01

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

  19. Aerial photographic reproductions

    USGS Publications Warehouse

    U.S. Geological Survey

    1975-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Tanathong, Supannee; Lee, Impyeong

    2014-11-01

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

  1. 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.

  2. 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.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2005-05-01

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

  5. Guiding the Search for Surface Rupture and Paleoseismic Sites using Low-Level Aerial Surveys, Geodetic Imaging, Remote Sensing and Field Mapping (Invited)

    NASA Astrophysics Data System (ADS)

    Hudnut, K. W.; Fletcher, J. M.; Teran, O.; Gonzalez-Garcia, J. J.; Hinojosa, A.; Rockwell, T. K.; Akciz, S. O.; Leprince, S.; Fielding, E. J.; Briggs, R. W.; Crone, A. J.; Gold, R. D.; Prentice, C. S.; Stock, J.; Avouac, J.; Simons, M.; Galetzka, J. E.; Lynch, D. K.; Cowgill, E.; Oskin, M. E.; Morelan, A.; Aslaksen, M.; Sellars, J.; Woolard, J.

    2010-12-01

    The significant earthquakes of 2010 produced surficial expressions ranging from blind faulting and coastal uplift in Leogane, Haiti and Maule, Chile to surface faulting in Baja California, Mexico and Yushu, China. In Haiti and Baja California geodetic imaging methods strongly guided field reconnaissance and surface rupture mapping efforts, yet in quite different ways. In these challenging examples, InSAR, UAVSAR and optical image differencing, as well as SAR pixel tracking methods, were used to locate and quantify ground deformation and ruptures. In Baja California prominent rupture occurred in parts of the Cucapah mountains, yet along an 11 km-long stepover section, the zone of faulting was discontinuous and obscured by rockfalls. Optical image differencing helped identify surface rupture, especially through this stepover. SAR pixel tracking confirmed that rupture occurred along the newly identified Indiviso fault in Baja California, though masked by ground failure in the Colorado River Delta. Also in Baja California (and extending north of the US-MX border), a complex set of NE-SW cross-faults and N-S breaks were imaged with UAVSAR, InSAR, and aerial photography allowing the intricate pattern of faulting to be scrutinized. In Haiti, surface rupture along the inferred source fault was not observed during initial reconnaissance. This led to extensive imagery- and field-based searches for surface deformation, aided by InSAR, which revealed that surface deformation was caused primarily by off-fault blind thrusting. In Baja California, high resolution (up to 3-5 cm GSD) aerial imaging by low-altitude aerial stereo photography was then used to identify promising locations for measuring slip vectors on the fault, and to aid in mapping the surface rupture in detail (at 1:500 scale). Digital aerial photography with 0.1 m GSD by NOAA using their DSS 439 camera was rapidly reduced to orthomosaics (at 0.25 m GSD) and then used as uniform base imagery for rupture mapping. In

  6. 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.

  7. An aerial radiological survey of the Davis-Monthan Air Force Base and surrounding area, Tucson, Arizona

    SciTech Connect

    1995-09-01

    An aerial radiological survey, which was conducted from March 1 to 13, 1995, covered a 51-square-mile (132-square-kilometer) area centered on the Davis-Monthan Air Force Base (DMAFB) in Tucson, Arizona. The results of the survey are reported as contours of bismuth-214 ({sup 214}Bi) soil concentrations, which are characteristic of natural uranium and its progeny, and as contours of the total terrestrial exposure rates extrapolated to one meter above ground level. All data were scaled and overlaid on an aerial photograph of the DMAFB area. The terrestrial exposure rates varied from 9 to 20 microroentgens per hour at one meter above the ground. Elevated levels of terrestrial radiation due to increased concentrations of {sup 214}Bi (natural uranium) were observed over the Southern Pacific railroad yard and along portions of the railroad track bed areas residing both within and outside the base boundaries. No man-made, gamma ray-emitting radioactive material was observed by the aerial survey. High-purity germanium spectrometer and pressurized ionization chamber measurements at eight locations within the base boundaries were used to verify the integrity of the aerial results. The results of the aerial and ground-based measurements were found to be in agreement. However, the ground-based measurements were able to detect minute quantities of cesium-137 ({sup 137}Cs) at six of the eight locations examined. The presence of {sup 137}Cs is a remnant of fallout from foreign and domestic atmospheric nuclear weapons testing that occurred in the 1950s and early 1960s. Cesium-137 concentrations varied from 0.1 to 0.3 picocuries per gram, which is below the minimum detectable activity of the aerial system.

  8. 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... Air Force Base, Fla. (a) The danger zones—(1) Aerial gunnery range in west part of Choctawhatchee Bay. The danger zone shall encompass all navigable waters of the United States as defined at 33 CFR...

  9. 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... Air Force Base, Fla. (a) The danger zones—(1) Aerial gunnery range in west part of Choctawhatchee Bay. The danger zone shall encompass all navigable waters of the United States as defined at 33 CFR...

  10. 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.

  11. 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

  12. 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

    2015-01-01

    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

  13. 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.

  14. 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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

    White, S. M.; Madsen, E.

    2013-12-01

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

  18. 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. 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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  2. An automatic stain removal algorithm of series aerial photograph based on flat-field correction

    NASA Astrophysics Data System (ADS)

    Wang, Gang; Yan, Dongmei; Yang, Yang

    2010-10-01

    The dust on the camera's lens will leave dark stains on the image. Calibrating and compensating the intensity of the stained pixels play an important role in the airborne image processing. This article introduces an automatic compensation algorithm for the dark stains. It's based on the theory of flat-field correction. We produced a whiteboard reference image by aggregating hundreds of images recorded in one flight and use their average pixel values to simulate the uniform white light irradiation. Then we constructed a look-up table function based on this whiteboard image to calibrate the stained image. The experiment result shows that the proposed procedure can remove lens stains effectively and automatically.

  3. 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

  4. 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. PMID:23255169

  5. 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.

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    1996-11-01

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

  8. 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.

  9. 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.

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

    ERIC Educational Resources Information Center

    Jack, Robert F.

    1984-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. Drogue detection for vision-based autonomous aerial refueling via low rank and sparse decomposition with multiple features

    NASA Astrophysics Data System (ADS)

    Gao, Shibo; Cheng, Yongmei; Song, Chunhua

    2013-09-01

    The technology of vision-based probe-and-drogue autonomous aerial refueling is an amazing task in modern aviation for both manned and unmanned aircraft. A key issue is to determine the relative orientation and position of the drogue and the probe accurately for relative navigation system during the approach phase, which requires locating the drogue precisely. Drogue detection is a challenging task due to disorderly motion of drogue caused by both the tanker wake vortex and atmospheric turbulence. In this paper, the problem of drogue detection is considered as a problem of moving object detection. A drogue detection algorithm based on low rank and sparse decomposition with local multiple features is proposed. The global and local information of drogue is introduced into the detection model in a unified way. The experimental results on real autonomous aerial refueling videos show that the proposed drogue detection algorithm is effective.

  13. Observations of coastal systems using low-cost, high-resolution, balloon and kite-based aerial imagery

    NASA Astrophysics Data System (ADS)

    Griffith, A.; Young, R.

    2012-04-01

    Remote-sensed aerial imagery has been one of the primary methods for tracking shoreline change, but the low availability of high-quality data that is temporally relevant to the area of interest is often too expensive for small scale studies, if the data even exist. The Program for the Study of Developed Shorelines (PSDS) at Western Carolina University has been using balloon and kite mounted cameras for two years to make observations of highly dynamic, near shore systems in the southeastern United States. Through a partnership with GrassrootsMapping.org, our program was introduced to the system of aerial photography which collects images for under 200 USD at resolutions of 5-10 cm/pixel. The system is field transportable and can collect imagery on an as-needed basis, instead of scheduling aerial over flights or waiting for Google Earth imagery to be updated. Successful research trips to Beaufort County, South Carolina have identified buildings and infrastructure that are at risk of inundation from sea-level rise. The region experiences daily tidal fluctuations in excess of 2 m, allowing imagery to be captured at a variety of tidal cycles. The method has identified wetlands adjacent to developed areas lacking a buffer area allowing them to expand as sea levels rise. Due to the high resolution of the images, changes over shorter time intervals can be observed, such as the transition from high marsh to low marsh, as sea levels rise. After the 2010 Deepwater Horizon oil spill, PSDS staff mapped the oil spill on several trips to the Gulf of Mexico. Repeated visits to the same area have yielded a time series of images with greater frequency than more expensive methods. Finally, offshore sand movements at tidal inlets have been observed in detail on beaches in southern Georgia.

  14. 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.

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

    PubMed

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

    1964-11-01

    Aerial infrared-sensor surveys of Kilauea volcano have depicted the areal extent and the relative intensity of abnormal thermal features in the caldera area of the volcano and along its associated rift zones. Many of these anomalies show correlation with visible steaming and reflect convective transfer of heat to the surface from subterranean sources. Structural details of the volcano, some not evident from surface observation, are also delineated by their thermal abnormalities. Several changes were observed in the patterns of infrared emission during the period of study; two such changes show correlation in location with subsequent eruptions, but the cause-and-effect relationship is uncertain. Thermal anomalies were also observed on the southwest flank of Mauna Loa; images of other volcanoes on the island of Hawaii, and of Haleakala on the island of Maui, revealed no thermal abnormalities. Approximately 25 large springs issuing into the ocean around the periphery of Hawaii have been detected. Infrared emission varies widely with surface texture and composition, suggesting that similar observations may have value for estimating surface conditions on the moon or planets. PMID:17729994

  16. Aerial multispectral imaging for cotton yield estimation under different irrigation and nitrogen treatments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton yield varied spatially within a field. The variability can be caused by various production inputs such as soil property, water management, and fertilizer application. Airborne multispectral imaging is capable of providing data and information to study effects of the inputs on the yield qualit...

  17. 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.

  18. Design of Pel Adaptive DPCM coding based upon image partition

    NASA Astrophysics Data System (ADS)

    Saitoh, T.; Harashima, H.; Miyakawa, H.

    1982-01-01

    A Pel Adaptive DPCM coding system based on image partition is developed which possesses coding characteristics superior to those of the Block Adaptive DPCM coding system. This method uses multiple DPCM coding loops and nonhierarchical cluster analysis. It is found that the coding performances of the Pel Adaptive DPCM coding method differ depending on the subject images. The Pel Adaptive DPCM designed using these methods is shown to yield a maximum performance advantage of 2.9 dB for the Girl and Couple images and 1.5 dB for the Aerial image, although no advantage was obtained for the moon image. These results show an improvement over the optimally designed Block Adaptive DPCM coding method proposed by Saito et al. (1981).

  19. 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...

  20. 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...

  1. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2004-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Shibuya, Masato; Takada, Akira; Nakashima, Toshiharu

    2016-04-01

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

  4. Study on Construction of 3d Building Based on Uav Images

    NASA Astrophysics Data System (ADS)

    Xie, F.; Lin, Z.; Gui, D.; Lin, H.

    2012-07-01

    Based on the characteristics of Unmanned Aerial Vehicle (UAV) system for low altitude aerial photogrammetry and the need of three dimensional (3D)city modeling, a method of fast 3D building modeling using the images from UAV carrying four-combined camera is studied. Firstly, by contrasting and analyzing the mosaic structures of the existing four-combined cameras, a new type of four-combined camera with special design of overlap images is designed, which improves the self-calibration function to achieve the high precision imaging by automatically eliminating the error of machinery deformation and the time lag with every exposure, and further reduce the weight of the imaging system. Secondly, several-angle images including vertical images and oblique images gotten by the UAV system are used for the detail measure of building surfaces and the texture extraction. Finally, two tests that are aerial photography with large scale mapping of 1:1000 and 3D building construction in Shandong University of Science and Technology and aerial photography with large scale mapping of 1:500 and 3D building construction in Henan University of Urban Construction, provide authentication model for construction of 3D building based on combined wide-angle camera images from UAV system. It is demonstrated that the UAV system for low altitude aerial photogrammetry can be used in the construction of 3D building production, and the technology solution in this paper offers a new, fast and technical plan for the 3D expression of the city landscape, fine modeling and visualization.

  5. 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

  6. 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...

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

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

    PubMed

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

    2015-01-01

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

  14. 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.

  15. Model based image restoration for underwater images

    NASA Astrophysics Data System (ADS)

    Stephan, Thomas; Frühberger, Peter; Werling, Stefan; Heizmann, Michael

    2013-04-01

    The inspection of offshore parks, dam walls and other infrastructure under water is expensive and time consuming, because such constructions must be inspected manually by divers. Underwater buildings have to be examined visually to find small cracks, spallings or other deficiencies. Automation of underwater inspection depends on established water-proved imaging systems. Most underwater imaging systems are based on acoustic sensors (sonar). The disadvantage of such an acoustic system is the loss of the complete visual impression. All information embedded in texture and surface reflectance gets lost. Therefore acoustic sensors are mostly insufficient for these kind of visual inspection tasks. Imaging systems based on optical sensors feature an enormous potential for underwater applications. The bandwidth from visual imaging systems reach from inspection of underwater buildings via marine biological applications through to exploration of the seafloor. The reason for the lack of established optical systems for underwater inspection tasks lies in technical difficulties of underwater image acquisition and processing. Lightening, highly degraded images make a computational postprocessing absolutely essential.

  16. 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.

  17. 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).

  18. 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

  19. Imaging of skull base tumours.

    PubMed

    Thust, Stefanie Catherine; Yousry, Tarek

    2016-01-01

    The skull base is a highly complex and difficult to access anatomical region, which constitutes a relatively common site for neoplasms. Imaging plays a central role in establishing the differential diagnosis, to determine the anatomic tumour spread and for operative planning. All skull base imaging should be performed using thin-section multiplanar imaging, whereby CT and MRI can be considered complimentary. An interdisciplinary team approach is central to improve the outcome of these challenging tumours. PMID:27330416

  20. Comparative analysis of transcriptomes in aerial stems and roots of Ephedra sinica based on high-throughput mRNA sequencing.

    PubMed

    Okada, Taketo; Takahashi, Hironobu; Suzuki, Yutaka; Sugano, Sumio; Noji, Masaaki; Kenmoku, Hiromichi; Toyota, Masao; Kanaya, Shigehiko; Kawahara, Nobuo; Asakawa, Yoshinori; Sekita, Setsuko

    2016-12-01

    Ephedra plants are taxonomically classified as gymnosperms, and are medicinally important as the botanical origin of crude drugs and as bioresources that contain pharmacologically active chemicals. Here we show a comparative analysis of the transcriptomes of aerial stems and roots of Ephedra sinica based on high-throughput mRNA sequencing by RNA-Seq. De novo assembly of short cDNA sequence reads generated 23,358, 13,373, and 28,579 contigs longer than 200 bases from aerial stems, roots, or both aerial stems and roots, respectively. The presumed functions encoded by these contig sequences were annotated by BLAST (blastx). Subsequently, these contigs were classified based on gene ontology slims, Enzyme Commission numbers, and the InterPro database. Furthermore, comparative gene expression analysis was performed between aerial stems and roots. These transcriptome analyses revealed differences and similarities between the transcriptomes of aerial stems and roots in E. sinica. Deep transcriptome sequencing of Ephedra should open the door to molecular biological studies based on the entire transcriptome, tissue- or organ-specific transcriptomes, or targeted genes of interest. PMID:27625990

  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. 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.

  3. 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.

  4. An aerial radiological survey of the Wright-Patterson Air Force Base and surrounding area, Fairborn, Ohio

    SciTech Connect

    1995-08-01

    An aerial radiological survey was conducted over areas of Wright-Patterson Air Force Base (WPAFB) and the immediate surrounding area, during the period July 7 through 20, 1994. The survey was conducted to measure and map the gamma radiation in the area. This mission was the first aerial radiation survey conducted at WPAFB. In the surveyed area, five small localized sources of gamma radiation were detected which were atypical of naturally-occurring radionuclides. On WPAFB property, these sources included a radiation storage facility in Area B (krypton-85) and an ash pile near the Area C flight line (low energy gamma activity). In the area covered outside WPAFB boundaries, sources included cesium-137 in excess of worldwide fallout over a landfill in a northern Dayton industrial area, an X-ray radiography source over a steel plant in the same industrial area, and a mixture of cesium-137 in excess of worldwide fallout and possibly iridium-192 in an area near Crystal Lakes, Ohio. The naturally-occurring gamma emitters (uranium-238 and progeny, thorium and progeny, and potassium-40) were detected in the remaining area with a total exposure rate range of 4 to 16 {mu}R/h; this range is typical of that found in the United States, 1 to 20 {mu}R/h.

  5. Robust crack detection strategies for aerial inspection

    NASA Astrophysics Data System (ADS)

    Aldea, Emanuel; Le Hégarat, Sylvie

    2015-04-01

    In this work, we evaluate the relevance of current state of the art algorithms widely employed in the detection of cracks, for the specific context of aerial inspection, which is characterized by image quality degradation. In this study we focus on minimal cost path and on Marked Point Process algorithms, and we test their resilience to motion blur. The results show that the current strategies for defect detection are sensitive to the quality of input images; alternatively, we suggest some improvements based on a-contrario methods that are able to cope with significant motion blur.

  6. 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.

  7. 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

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

    PubMed

    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

  9. Estimating discharge rates of oily wastes and deterrence based on aerial surveillance data collected in western Canadian marine waters.

    PubMed

    O'Hara, P D; Serra-Sogas, N; Canessa, R; Keller, P; Pelot, R

    2013-04-15

    Illegal discharge of waste oil from ships is a major source of mortality for seabirds globally. Using linear and log-linear regression, we explored the relationship between detection rates of marine oily discharges and surveillance effort at different time scales, based on data collected in the Canadian Pacific Ocean by the National Aerial Surveillance Program (NASP) from 1997 to 2006. We introduce an approach for quantifying reductions in discharge rates with increased surveillance while controlling appropriately for surveillance effort, as standard linear correction for effort can introduce considerable bias. Despite low probabilities of detection (0.088-1.1%), we found evidence for reduced discharge rates with increasing surveillance effort for data summarized monthly and bimonthly in region A, which is closest to the NASP base airport. Using residuals derived from the best-fit log-linear models, we found detected discharge rates declined annually (-[0.070 spills/month]×year). PMID:23453813

  10. Imaging based refractometers

    SciTech Connect

    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.

  11. Research on Virtual Simulation of the Aerial Passenger Device Based on Three-Dimensional Visualization and Virtual Simulation

    NASA Astrophysics Data System (ADS)

    Wang, Jingchong; Wang, Dahu; Liu, Haiyang

    Analyzing the key design for Aerial Passenger Device, 3DMAX is applied for creating models which is the key technology and corresponding safety protection device. Combined with Quest3D engine for setting, such as roadway and safety devices are displayed in virtual. Finally Aerial Passenger Device is in the virtual scene. Then simulation results examine the Aerial Passenger Device's rationality and safety reducing the cycle of system optimization and technology improvement.

  12. 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.

  13. Staircase-scene-based nonuniformity correction in aerial point target detection systems.

    PubMed

    Huo, Lijun; Zhou, Dabiao; Wang, Dejiang; Liu, Rang; He, Bin

    2016-09-01

    Focal-plane arrays (FPAs) are often interfered by heavy fixed-pattern noise, which severely degrades the detection rate and increases the false alarms in airborne point target detection systems. Thus, high-precision nonuniformity correction is an essential preprocessing step. In this paper, a new nonuniformity correction method is proposed based on a staircase scene. This correction method can compensate for the nonlinear response of the detector and calibrate the entire optical system with computational efficiency and implementation simplicity. Then, a proof-of-concept point target detection system is established with a long-wave Sofradir FPA. Finally, the local standard deviation of the corrected image and the signal-to-clutter ratio of the Airy disk of a Boeing B738 are measured to evaluate the performance of the proposed nonuniformity correction method. Our experimental results demonstrate that the proposed correction method achieves high-quality corrections. PMID:27607295

  14. Semantic-based high resolution remote sensing image retrieval

    NASA Astrophysics Data System (ADS)

    Guo, Dihua

    High Resolution Remote Sensing (HRRS) imagery has been experiencing extraordinary development in the past decade. Technology development means increased resolution imagery is available at lower cost, making it a precious resource for planners, environmental scientists, as well as others who can learn from the ground truth. Image retrieval plays an important role in managing and accessing huge image database. Current image retrieval techniques, cannot satisfy users' requests on retrieving remote sensing images based on semantics. In this dissertation, we make two fundamental contributions to the area of content based image retrieval. First, we propose a novel unsupervised texture-based segmentation approach suitable for accurately segmenting HRRS images. The results of existing segmentation algorithms dramatically deteriorate if simply adopted to HRRS images. This is primarily clue to the multi-texture scales and the high level noise present in these images. Therefore, we propose an effective and efficient segmentation model, which is a two-step process. At high-level, we improved the unsupervised segmentation algorithm by coping with two special features possessed by HRRS images. By preprocessing images with wavelet transform, we not only obtain multi-resolution images but also denoise the original images. By optimizing the splitting results, we solve the problem of textons in HRRS images existing in different scales. At fine level, we employ fuzzy classification segmentation techniques with adjusted parameters for different land cover. We implement our algorithm using real world 1-foot resolution aerial images. Second, we devise methodologies to automatically annotate HRRS images based on semantics. In this, we address the issue of semantic feature selection, the major challenge faced by semantic-based image retrieval. To discover and make use of hidden semantics of images is application dependent. One type of the semantics in HRRS image is conveyed by composite

  15. Image based autodocking without calibration

    SciTech Connect

    Sutanto, H.; Sharma, R.; Varma, V.

    1997-03-01

    The calibration requirements for visual servoing can make it difficult to apply in many real-world situations. One approach to image-based visual servoing without calibration is to dynamically estimate the image Jacobian and use it as the basis for control. However, with the normal motion of a robot toward the goal, the estimation of the image Jacobian deteriorates over time. The authors propose the use of additional exploratory motion to considerably improve the estimation of the image Jacobian. They study the role of such exploratory motion in a visual servoing task. Simulations and experiments with a 6-DOF robot are used to verify the practical feasibility of the approach.

  16. 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).

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  18. 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.

  19. Age Determination by Back Length for African Savanna Elephants: Extending Age Assessment Techniques for Aerial-Based Surveys

    PubMed Central

    Trimble, Morgan J.; van Aarde, Rudi J.; Ferreira, Sam M.; Nørgaard, Camilla F.; Fourie, Johan; Lee, Phyllis C.; Moss, Cynthia J.

    2011-01-01

    Determining the age of individuals in a population can lead to a better understanding of population dynamics through age structure analysis and estimation of age-specific fecundity and survival rates. Shoulder height has been used to accurately assign age to free-ranging African savanna elephants. However, back length may provide an analog measurable in aerial-based surveys. We assessed the relationship between back length and age for known-age elephants in Amboseli National Park, Kenya, and Addo Elephant National Park, South Africa. We also compared age- and sex-specific back lengths between these populations and compared adult female back lengths across 11 widely dispersed populations in five African countries. Sex-specific Von Bertalanffy growth curves provided a good fit to the back length data of known-age individuals. Based on back length, accurate ages could be assigned relatively precisely for females up to 23 years of age and males up to 17. The female back length curve allowed more precise age assignment to older females than the curve for shoulder height does, probably because of divergence between the respective growth curves. However, this did not appear to be the case for males, but the sample of known-age males was limited to ≤27 years. Age- and sex-specific back lengths were similar in Amboseli National Park and Addo Elephant National Park. Furthermore, while adult female back lengths in the three Zambian populations were generally shorter than in other populations, back lengths in the remaining eight populations did not differ significantly, in support of claims that growth patterns of African savanna elephants are similar over wide geographic regions. Thus, the growth curves presented here should allow researchers to use aerial-based surveys to assign ages to elephants with greater precision than previously possible and, therefore, to estimate population variables. PMID:22028925

  20. 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.

  1. Image Data Bases on Campus.

    ERIC Educational Resources Information Center

    Kaplan, Reid; Mathieson, Gordon

    1989-01-01

    A description of how image database technology was used to develop two prototypes for academic and administrative applications at Yale University, one using a video data base integration and the other using document-scanning data base technology, is presented. Technical underpinnings for the creation of data bases are described. (Author/MLW)

  2. 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.

  3. 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. PMID:16566471

  4. 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. PMID:27432686

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

    PubMed

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

    2015-01-01

    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. PMID:25808767

  6. Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images

    PubMed Central

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

    2015-01-01

    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. PMID:25808767

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  9. Aerial camera auto focusing system

    NASA Astrophysics Data System (ADS)

    Wang, Xuan; Lan, Gongpu; Gao, Xiaodong; Liang, Wei

    2012-10-01

    Before the aerial photographic task, the cameras focusing work should be performed at first to compensate the defocus caused by the changes of the temperature, pressure etc. A new method of aerial camera auto focusing is proposed through traditional photoelectric self-collimation combined with image processing method. Firstly, the basic principles of optical self-collimation and image processing are introduced. Secondly, the limitations of the two are illustrated and the benefits of the new method are detailed. Then the basic principle, the system composition and the implementation of this new method are presented. Finally, the data collection platform is set up reasonably and the focus evaluation function curve is draw. The results showed that: the method can be used in the Aerial camera focusing field, adapt to the aviation equipment trends of miniaturization and lightweight .This paper is helpful to the further work of accurate and automatic focusing.

  10. Implementation strategy of wafer-plane and aerial-plane inspection for advanced mask manufacture

    NASA Astrophysics Data System (ADS)

    Kim, Won-Sun; Chung, Dong-Hoon; Jeon, Chan-Uk; Cho, HanKu; Huang, William; Miller, John; Inderhees, Gregg; Pinto, Becky; Hur, Jiuk; Park, Kihun; Han, Jay

    2009-04-01

    Inspection of aggressive Optical Proximity Correction (OPC) designs, improvement of usable sensitivity, and reduction of cost of ownership are the three major challenges for today's mask inspection methodologies. In this paper we will discuss using aerial-plane inspection and wafer-plane inspection as novel approaches to address these challenges for advanced reticles. Wafer-plane inspection (WPI) and aerial-plane inspection (API) are two lithographic inspection modes. This suite of new inspection modes is based on high resolution reflected and transmitted light images in the reticle plane. These images together with scanner parameters are used to generate the aerial plane image using either vector or scalar models. Then information about the resist is applied to complete construction of the wafer plane image. API reports defects based on intensity differences between test and reference images at the aerial plane, whereas WPI applies a resist model to the aerial image to enhance discrimination between printable and non-printable defects at the wafer plane. The combination of WPI and API along with the industry standard Reticle Plane Inspection (RPI) is designed to handle complex OPC features, improve usable sensitivity and reduce the cost of ownership. This paper will explore the application of aerial-plane and wafer-plane die-to-die inspections on advanced reticles. Inspection sensitivity, inspectability, and comparison with Aerial Imaging Measurement System (AIMSTM[1]) or wafer-print-line will be analyzed. Most importantly, the implementation strategy of a combination of WPI and API along with RPI leading-edge mask manufacturing will be discussed.

  11. 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.

  12. 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.

  13. 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)

  14. Fovea based image quality assessment

    NASA Astrophysics Data System (ADS)

    Guo, Anan; Zhao, Debin; Liu, Shaohui; Cao, Guangyao

    2010-07-01

    Humans are the ultimate receivers of the visual information contained in an image, so the reasonable method of image quality assessment (IQA) should follow the properties of the human visual system (HVS). In recent years, IQA methods based on HVS-models are slowly replacing classical schemes, such as mean squared error (MSE) and Peak Signal-to-Noise Ratio (PSNR). IQA-structural similarity (SSIM) regarded as one of the most popular HVS-based methods of full reference IQA has apparent improvements in performance compared with traditional metrics in nature, however, it performs not very well when the images' structure is destroyed seriously or masked by noise. In this paper, a new efficient fovea based structure similarity image quality assessment (FSSIM) is proposed. It enlarges the distortions in the concerned positions adaptively and changes the importances of the three components in SSIM. FSSIM predicts the quality of an image through three steps. First, it computes the luminance, contrast and structure comparison terms; second, it computes the saliency map by extracting the fovea information from the reference image with the features of HVS; third, it pools the above three terms according to the processed saliency map. Finally, a commonly experimental database LIVE IQA is used for evaluating the performance of the FSSIM. Experimental results indicate that the consistency and relevance between FSSIM and mean opinion score (MOS) are both better than SSIM and PSNR clearly.

  15. 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.

  16. 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.

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

    PubMed

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

    2016-01-01

    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

  18. 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

  19. Object-Based Image Compression

    NASA Astrophysics Data System (ADS)

    Schmalz, Mark S.

    2003-01-01

    Image compression frequently supports reduced storage requirement in a computer system, as well as enhancement of effective channel bandwidth in a communication system, by decreasing the source bit rate through reduction of source redundancy. The majority of image compression techniques emphasize pixel-level operations, such as matching rectangular or elliptical sampling blocks taken from the source data stream, with exemplars stored in a database (e.g., a codebook in vector quantization or VQ). Alternatively, one can represent a source block via transformation, coefficient quantization, and selection of coefficients deemed significant for source content approximation in the decompressed image. This approach, called transform coding (TC), has predominated for several decades in the signal and image processing communities. A further technique that has been employed is the deduction of affine relationships from source properties such as local self-similarity, which supports the construction of adaptive codebooks in a self-VQ paradigm that has been called iterated function systems (IFS). Although VQ, TC, and IFS based compression algorithms have enjoyed varying levels of success for different types of applications, bit rate requirements, and image quality constraints, few of these algorithms examine the higher-level spatial structure of an image, and fewer still exploit this structure to enhance compression ratio. In this paper, we discuss a fourth type of compression algorithm, called object-based compression, which is based on research in joint segmentaton and compression, as well as previous research in the extraction of sketch-like representations from digital imagery. Here, large image regions that correspond to contiguous recognizeable objects or parts of objects are segmented from the source, then represented compactly in the compressed image. Segmentation is facilitated by source properties such as size, shape, texture, statistical properties, and spectral

  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. Suitability of low cost commercial off-the-shelf aerial platforms and consumer grade digital cameras for small format aerial photography

    NASA Astrophysics Data System (ADS)

    Turley, Anthony Allen

    Many research projects require the use of aerial images. Wetlands evaluation, crop monitoring, wildfire management, environmental change detection, and forest inventory are but a few of the applications of aerial imagery. Low altitude Small Format Aerial Photography (SFAP) is a bridge between satellite and man-carrying aircraft image acquisition and ground-based photography. The author's project evaluates digital images acquired using low cost commercial digital cameras and standard model airplanes to determine their suitability for remote sensing applications. Images from two different sites were obtained. Several photo missions were flown over each site, acquiring images in the visible and near infrared electromagnetic bands. Images were sorted and analyzed to select those with the least distortion, and blended together with Microsoft Image Composite Editor. By selecting images taken within minutes apart, radiometric qualities of the images were virtually identical, yielding no blend lines in the composites. A commercial image stitching program, Autopano Pro, was purchased during the later stages of this study. Autopano Pro was often able to mosaic photos that the free Image Composite Editor was unable to combine. Using telemetry data from an onboard data logger, images were evaluated to calculate scale and spatial resolution. ERDAS ER Mapper and ESRI ArcGIS were used to rectify composite images. Despite the limitations inherent in consumer grade equipment, images of high spatial resolution were obtained. Mosaics of as many as 38 images were created, and the author was able to record detailed aerial images of forest and wetland areas where foot travel was impractical or impossible.

  2. An Image-Based Technique for 3d Building Reconstruction Using Multi-View Uav Images

    NASA Astrophysics Data System (ADS)

    Alidoost, F.; Arefi, H.

    2015-12-01

    Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs) images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM) is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.

  3. Knowledge based SAR images exploitations

    NASA Astrophysics Data System (ADS)

    Wang, David L.

    1987-01-01

    One of the basic functions of SAR images exploitation system is the detection of man-made objects. The performance of object detection is strongly limited by performance of segmentation modules. This paper presents a detection paradigm composed of an adaptive segmentation algorithm based on a priori knowledge of objects followed by a top-down hierarchical detection process that generates and evaluates object hypotheses. Shadow information and inter-object relationships can be added to the knowledge base to improve performance over that of a statistical detector based only on the attributes of individual objects.

  4. Image-based querying of urban knowledge databases

    NASA Astrophysics Data System (ADS)

    Cho, Peter; Bae, Soonmin; Durand, Fredo

    2009-05-01

    We extend recent automated computer vision algorithms to reconstruct the global three-dimensional structures for photos and videos shot at fixed points in outdoor city environments. Mosaics of digital stills and embedded videos are georegistered by matching a few of their 2D features with 3D counterparts in aerial ladar imagery. Once image planes are aligned with world maps, abstract urban knowledge can propagate from the latter into the former. We project geotagged annotations from a 3D map into a 2D video stream and demonstrate their tracking buildings and streets in a clip with significant panning motion. We also present an interactive tool which enables users to select city features of interest in video frames and retrieve their geocoordinates and ranges. Implications of this work for future augmented reality systems based upon mobile smart phones are discussed.

  5. 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.

  6. 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

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

    PubMed

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

    2015-01-01

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

  8. Moving Obstacle Avoidance for Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Lin, Yucong

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

  9. 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...

  10. Digital image-based titrations.

    PubMed

    Gaiao, Edvaldo da Nobrega; Martins, Valdomiro Lacerda; Lyra, Wellington da Silva; de Almeida, Luciano Farias; da Silva, Edvan Cirino; Araújo, Mário César Ugulino

    2006-06-16

    The exploitation of digital images obtained from a CCD camera (WebCam) as a novel instrumental detection technique for titration is proposed for the first time. Named of digital image-based (DIB) titration, it also requires, as a traditional titration (for example, spectrophotometric, potentiometric, conductimetric), a discontinuity in titration curves where there is an end point, which is associated to the chemical equivalence condition. The monitored signal in the DIB titration is a RGB-based value that is calculated, for each digital image, by using a proposed procedure based on the red, green, and blue colour system. The DIB titration was applied to determine HCl and H3PO4 in aqueous solutions and total alkalinity in mineral and tap waters. Its results were compared to the spectrophotometric (SPEC) titration and, by applying the paired t-test, no statistic difference between the results of both methods was verified at the 95% confidence level. Identical standard deviations were obtained by both titrations in the determinations of HCl and H3PO4, with a slightly better precision for DIB titration in the determinations of total alkalinity. The DIB titration shows to be an efficient and promising tool for quantitative chemical analysis and, as it employs an inexpensive device (WebCam) as analytical detector, it offers an economically viable alternative to titrations that need instrumental detection. PMID:17723410

  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. Image inpainting based on stacked autoencoders

    NASA Astrophysics Data System (ADS)

    Shcherbakov, O.; Batishcheva, V.

    2014-09-01

    Recently we have proposed the algorithm for the problem of image inpaiting (filling in occluded or damaged parts of images). This algorithm was based on the criterion spectrum entropy and showed promising results despite of using hand-crafted representation of images. In this paper, we present a method for solving image inpaiting task based on learning some image representation. Some results are shown to illustrate quality of image reconstruction.

  13. Building high dimensional imaging database for content based image search

    NASA Astrophysics Data System (ADS)

    Sun, Qinpei; Sun, Jianyong; Ling, Tonghui; Wang, Mingqing; Yang, Yuanyuan; Zhang, Jianguo

    2016-03-01

    In medical imaging informatics, content-based image retrieval (CBIR) techniques are employed to aid radiologists in the retrieval of images with similar image contents. CBIR uses visual contents, normally called as image features, to search images from large scale image databases according to users' requests in the form of a query image. However, most of current CBIR systems require a distance computation of image character feature vectors to perform query, and the distance computations can be time consuming when the number of image character features grows large, and thus this limits the usability of the systems. In this presentation, we propose a novel framework which uses a high dimensional database to index the image character features to improve the accuracy and retrieval speed of a CBIR in integrated RIS/PACS.

  14. Using enlarged stereo aerial images acquired by small-format nonmetric camera for large-scale ocean floor mapping at low tide

    NASA Astrophysics Data System (ADS)

    Adamos, Christos; Faig, Wolfgang

    1993-10-01

    HY-GRO '92 is a project currently carried out by the Ocean Mapping Group at the University of New Brunswick. One of the purposes of this project is the investigation of the relationship between acoustic mapping data and the actual ocean seabed bathymetry. In order to facilitate the comparison, ground truthing information (Digital Elevation Model) has been collected using stereo aerial photography of tidal areas at low tide. The required DEM accuracy is in the magnitude of a few centimeters. A reasonable photoscale for providing the required DEM accuracy would be 1:3750. With a focal length of 80 mm the flying height has to be 300 m. In that case the ground coverage of the 57 X 57 mm2 image format is 214 X 214 m2. It is clear that for large areas of interest (in our case: 2.5 X 2.5 km2) while maintaining the necessary overlap (60%) and sidelap (30%), the number of photographs and control points becomes unreasonably high, thus making the use of the small format camera not attractive anymore. The above encountered problem was solved with the acquisition of the original images in a four times smaller scale (1:15,000, flying height 1200 m, ground coverage 857 X 857 m2). Using a quality enlarger, the original images are enlarged by the same factor, so that the final image product is at the desired scale. The enlargement introduces effects of lens distortions and film deformations but they are again taken care of by the self calibrating bundle adjustment.

  15. Image super-resolution based on image adaptive decomposition

    NASA Astrophysics Data System (ADS)

    Xie, Qiwei; Wang, Haiyan; Shen, Lijun; Chen, Xi; Han, Hua

    2011-11-01

    In this paper we propose an image super-resolution algorithm based on Gaussian Mixture Model (GMM) and a new adaptive image decomposition algorithm. The new image decomposition algorithm uses local extreme of image to extract the cartoon and oscillating part of image. In this paper, we first decompose an image into oscillating and piecewise smooth (cartoon) parts, then enlarge the cartoon part with interpolation. Because GMM accurately characterizes the oscillating part, we specify it as the prior distribution and then formulate the image super-resolution problem as a constrained optimization problem to acquire the enlarged texture part and finally we obtain a fine result.

  16. 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.

  17. Image-based EUVL aberration metrology

    NASA Astrophysics Data System (ADS)

    Fenger, Germain Louis

    A significant factor in the degradation of nanolithographic image fidelity is optical wavefront aberration. As resolution of nanolithography systems increases, effects of wavefront aberrations on aerial image become more influential. The tolerance of such aberrations is governed by the requirements of features that are being imaged, often requiring lenses that can be corrected with a high degree of accuracy and precision. Resolution of lithographic systems is driven by scaling wavelength down and numerical aperture (NA) up. However, aberrations are also affected from the changes in wavelength and NA. Reduction in wavelength or increase in NA result in greater impact of aberrations, where the latter shows a quadratic dependence. Current demands in semiconductor manufacturing are constantly pushing lithographic systems to operate at the diffraction limit; hence, prompting a need to reduce all degrading effects on image properties to achieve maximum performance. Therefore, the need for highly accurate in-situ aberration measurement and correction is paramount. In this work, an approach has been developed in which several targets including phase wheel, phase disk, phase edges, and binary structures are used to generate optical images to detect and monitor aberrations in extreme ultraviolet (EUV) lithographic systems. The benefit of using printed patterns as opposed to other techniques is that the lithography system is tested under standard operating conditions. Mathematical models in conjunction with iterative lithographic simulations are used to determine pupil phase wavefront errors and describe them as combinations of Zernike polynomials.

  18. 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.

  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. 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%.

  1. 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).

  2. 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.

  3. 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.

  4. Remote sensing based detection of forested wetlands: An evaluation of LiDAR, aerial imagery, and their data fusion

    NASA Astrophysics Data System (ADS)

    Suiter, Ashley Elizabeth

    Multi-spectral imagery provides a robust and low-cost dataset for assessing wetland extent and quality over broad regions and is frequently used for wetland inventories. However in forested wetlands, hydrology is obscured by tree canopy making it difficult to detect with multi-spectral imagery alone. Because of this, classification of forested wetlands often includes greater errors than that of other wetlands types. Elevation and terrain derivatives have been shown to be useful for modelling wetland hydrology. But, few studies have addressed the use of LiDAR intensity data detecting hydrology in forested wetlands. Due the tendency of LiDAR signal to be attenuated by water, this research proposed the fusion of LiDAR intensity data with LiDAR elevation, terrain data, and aerial imagery, for the detection of forested wetland hydrology. We examined the utility of LiDAR intensity data and determined whether the fusion of Lidar derived data with multispectral imagery increased the accuracy of forested wetland classification compared with a classification performed with only multi-spectral image. Four classifications were performed: Classification A -- All Imagery, Classification B -- All LiDAR, Classification C -- LiDAR without Intensity, and Classification D -- Fusion of All Data. These classifications were performed using random forest and each resulted in a 3-foot resolution thematic raster of forested upland and forested wetland locations in Vermilion County, Illinois. The accuracies of these classifications were compared using Kappa Coefficient of Agreement. Importance statistics produced within the random forest classifier were evaluated in order to understand the contribution of individual datasets. Classification D, which used the fusion of LiDAR and multi-spectral imagery as input variables, had moderate to strong agreement between reference data and classification results. It was found that Classification A performed using all the LiDAR data and its derivatives

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

    PubMed

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

    2014-06-01

    Micro aerial vehicles, particularly quadrotors, have been used in a wide range of applications. However, the literature on aerial manipulation and grasping is limited and the work is based on quasi-static models. In this paper, we draw inspiration from agile, fast-moving birds such as raptors, that are able to capture moving prey on the ground or in water, and develop similar capabilities for quadrotors. We address dynamic grasping, an approach to prehensile grasping in which the dynamics of the robot and its gripper are significant and must be explicitly modeled and controlled for successful execution. Dynamic grasping is relevant for fast pick-and-place operations, transportation and delivery of objects, and placing or retrieving sensors. We show how this capability can be realized (a) using a motion capture system and (b) without external sensors relying only on onboard sensors. In both cases we describe the dynamic model, and trajectory planning and control algorithms. In particular, we present a methodology for flying and grasping a cylindrical object using feedback from a monocular camera and an inertial measurement unit onboard the aerial robot. This is accomplished by mapping the dynamics of the quadrotor to a level virtual image plane, which in turn enables dynamically-feasible trajectory planning for image features in the image space, and a vision-based controller with guaranteed convergence properties. We also present experimental results obtained with a quadrotor equipped with an articulated gripper to illustrate both approaches. PMID:24852023

  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. 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.

  8. Helicopter, Unmanned Aerial Vehicle (UAV) and Ground Based Photogrammetric Monitoring of Mass Movements in Deglaciating Landscapes

    NASA Astrophysics Data System (ADS)

    Dunning, S.; Allan, M. S.; Lim, M.; Rosser, N. J.

    2014-12-01

    When valley glaciers retreat and/or thin, they expose stores of sediment prone to failure and rapid reworking through a range of mass movement processes. The newly exposed bedrock slopes are also thought to undergo a period of more intense, or more frequent, failure before returning to the background norm. However, the magnitude-frequency of failures above and in front of ice is poorly constrained, as are their spatial relationship to previous ice extents. Here we show the results from a combination of repeat helicopter, UAV and ground based photogrammetry that has been processed using Structure from Motion (SfM) techniques to produce high-resolution elevation and change models. These data require few ground control and so lend themselves to deployment in remote, or difficult to access high-mountain regions where our understanding of failure patterns has been limited by a lack of high-quality monitoring data. Our initial data cover the valley walls of Glacier d'Argentiere, Mer De Glace, Glacier des Bossons and the Bionnassay Glacier on the French side of the Mt Blanc massif at the start and end of the summer 2014 season. These glaciers have a rich documented history of ice retreat, thinning, and permafrost locations to link to the spatial patterns of failure.

  9. Braided rivers corridor characterization at a regional scale based on high resolution archived aerial photos (example of the Rhône network, France)

    NASA Astrophysics Data System (ADS)

    Belletti, B.; Dufour, S.; Piégay, H.

    2009-12-01

    Aerial photos provide meaningful information for interpreting riverscape evolution and characterising aquatic and riparian habitats, but also fluvial forms and processes to better understand the links between physical processes and organisms. In this study we collected archived orthorectified aerial photos (50 cm in resolution) from the French National Geographical Institute (IGN) database. We selected 55 braided reaches, in average 2,658 km long, within the 45000 km of river length of the Rhône hydrographic network to study riverscape organization and to identify geographical patterns. An object-orientated method has been applied on the set of photos using the Definiens® 2007 software to detect and classify riverscape patches (e.g. gravel bars, water channels, forest, etc.). Based on the landscape mapping, metrics and indicators have been calculated to explain braided pattern characters (braiding intensity, riparian mosaic diversity and low flow channel network pattern) in relation to longitudinal, altitudinal and regional locations. We performed also an inter-annual comparison between two dates (about 1950 and 2000) for each reach to evaluate their temporal evolution. Advantages and limitations of high resolution aerial photos are discussed to answer to scientific questions at a regional scale and also to planning issues, notably in the case of the implementation of the European Water Framework Directive.

  10. Image enhancement based on gamma map processing

    NASA Astrophysics Data System (ADS)

    Tseng, Chen-Yu; Wang, Sheng-Jyh; Chen, Yi-An

    2010-05-01

    This paper proposes a novel image enhancement technique based on Gamma Map Processing (GMP). In this approach, a base gamma map is directly generated according to the intensity image. After that, a sequence of gamma map processing is performed to generate a channel-wise gamma map. Mapping through the estimated gamma, image details, colorfulness, and sharpness of the original image are automatically improved. Besides, the dynamic range of the images can be virtually expanded.

  11. 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.

  12. Performance evaluation of image-based location recognition approaches based on large-scale UAV imagery

    NASA Astrophysics Data System (ADS)

    Hesse, Nikolas; Bodensteiner, Christoph; Arens, Michael

    2014-10-01

    Recognizing the location where an image was taken, solely based on visual content, is an important problem in computer vision, robotics and remote sensing. This paper evaluates the performance of standard approaches for location recognition when applied to large-scale aerial imagery in both electro-optical (EO) and infrared (IR) domains. We present guidelines towards optimizing the performance and explore how well a standard location recognition system is suited to handle IR data. We show on three datasets that the performance of the system strongly increases if SIFT descriptors computed on Hessian-Affine regions are used instead of SURF features. Applications are widespread and include vision-based navigation, precise object geo-referencing or mapping.

  13. 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.

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

    DOE PAGESBeta

    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

  15. 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

  16. 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. PMID:21135917

  17. Image transformation based on learning dictionaries across image spaces.

    PubMed

    Jia, Kui; Wang, Xiaogang; Tang, Xiaoou

    2013-02-01

    In this paper, we propose a framework of transforming images from a source image space to a target image space, based on learning coupled dictionaries from a training set of paired images. The framework can be used for applications such as image super-resolution and estimation of image intrinsic components (shading and albedo). It is based on a local parametric regression approach, using sparse feature representations over learned coupled dictionaries across the source and target image spaces. After coupled dictionary learning, sparse coefficient vectors of training image patch pairs are partitioned into easily retrievable local clusters. For any test image patch, we can fast index into its closest local cluster and perform a local parametric regression between the learned sparse feature spaces. The obtained sparse representation (together with the learned target space dictionary) provides multiple constraints for each pixel of the target image to be estimated. The final target image is reconstructed based on these constraints. The contributions of our proposed framework are three-fold. 1) We propose a concept of coupled dictionary learning based on coupled sparse coding which requires the sparse coefficient vectors of a pair of corresponding source and target image patches to have the same support, i.e., the same indices of nonzero elements. 2) We devise a space partitioning scheme to divide the high-dimensional but sparse feature space into local clusters. The partitioning facilitates extremely fast retrieval of closest local clusters for query patches. 3) Benefiting from sparse feature-based image transformation, our method is more robust to corrupted input data, and can be considered as a simultaneous image restoration and transformation process. Experiments on intrinsic image estimation and super-resolution demonstrate the effectiveness and efficiency of our proposed method. PMID:22529324

  18. 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).

  19. Detection of windthrow areas by object based image segmentation

    NASA Astrophysics Data System (ADS)

    Schmoeckel, J.; Kauffmann, M.

    2003-04-01

    In high resolution aerial images, areas that are uniform from the view of the application are not represented by an average spectral pattern, but are resolved into their components. While this enhanced information content offers the possibility of a more differentiating and correct classification, the classical spectral classification of single pixels comes up against its limits. Image analysis methods that take into account local neighborhood characteristics (edges, textures) can help to some extent, but deliver crumbled information that needs additional treatment. The new method of object based multispectral image segmentation (software "eCognition") promises a sulution. In a first step, the image is segmented into areas that are "looking" uniform, with respect to spectral, textural and shape properties. For each area, some characteristic values are calculated. In the second step, the segments are classified according to these attributes. The classification can be refined by giving training areas and previous knowledge (fuzzy class membership functions). In a third step, the classification can be improved by iterative application of neighbourhood criteria. In this work, the object based segmentation approach is applied to the detection of windthrow areas in multispectral images gained by an airborne survey with a digital line scanner. The characteristic pattern of lying trees, that is obvious to the human observer, can be detected in this way. Additionally, foreground objects (clouds) and settelement areas, which must be excluded, can be found. The derivated damage pattern can be used for an analysis of orographical influence on storm damage to forests in mountain areas (contribution of J. Schmoeckel and Ch. Kottmeier).

  20. Adaptive planning of emergency aerial photogrammetric mission

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Gama, C.; Jalobeanu, A.

    2011-12-01

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

  2. 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

  3. 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

  4. L1-graph-based image matching approach for UAV navigation

    NASA Astrophysics Data System (ADS)

    Zhou, H. B.; Tian, J. W.; Zhang, D. Z.

    2011-11-01

    Keywords: Unmanned Aerial Vehicles (UAVs) are been increasingly used in civilian and military domains. Vision-aided inertial navigation system in UAV is studied by more and more researchers for it's non-contact, high accuracy and stability. In this paper, an L1-Graph-based image matching approach, which constructs neighbouring system based on sparse representation, is proposed for monocular motion vision measurement. Then, a scheme for amending the outputs of inertial sensor for the velocity measurement is designed, which fuse the outputs from the downward-looking velocity measurement and inertial sensor by Kalman filter. Experiments show this design form an accurate navigation solution.

  5. Clipping service: ATR-based SAR image compression

    NASA Astrophysics Data System (ADS)

    Rodkey, David L.; Welby, Stephen P.; Hostetler, Larry D.

    1996-06-01

    Future wide area surveillance systems such as the Tier II+ and Tier III- unmanned aerial vehicles (UAVs) will be gathering cast amounts of high resolution SAR data for transmission to ground stations and subsequent analysis by image interpreters to provide critical and timely information to field commanders. This extremely high data rate presents two problems. First, wide bandwidth data link channels which would be needed to transmit this high data rate presents two problems. First, wide bandwidth data link channels which would be needed to transmit this imagery to a ground station are both expensive and difficult to obtain. Second, the volume of data which is generated by the system will quickly saturate any human-based analysis system without some degree of computer assistance. The ARPA sponsored clipping service program seeks to apply automatic target recognition (ATR) technology to perform 'intelligent' data compression on this imagery in a way which will provide a product on the ground that preserves essential information for further processing either by the military analyst or by a ground-based ATR system. An ATR system on board the UAV would examine the imagery data stream in real time determining regions of interest. Imagery from those regions would be transmitted to the ground in a manner which preserved most or all of the information contained in the original image. The remainder of the imagery would be transmitted to the ground with lesser fidelity. This paper presents system analysis deriving the operational requirements for the clipping service system and examines candidate architectures.

  6. Framland parcels extraction from high-resolution remote sensing images based on the two-stage image classification

    NASA Astrophysics Data System (ADS)

    Liu, Guoying; Song, Xu; Lv, Jing

    2015-12-01

    It is difficult and boring for people to artificially extract farmland parcels from high resolution remote sensing images. Therefore, automatic methods are in the urgent need to release image interpreters from such a work as well as achieve accurate results. In the past years, although many researchers have made attempts to solve this problem by using different techniques and also produced some good results, they still cannot meet the demand of practical applications. In this paper, a farmland extraction method is proposed based on a new technique of two-stage image classification. The first stage aims at producing a map of farmland area by using the supervised iterative conditional mode (ICM), where a novel mixture posterior is proposed based on the tree-structured interpretation of certain complex landscapes, e.g., farmland and building area, and the Markov random field model (MRF) is also used to make use of spatial information between neighboring pixels. The second stage extracts the farmland parcels by using the Meanshift algorithm (MS) based on the hybrid of the original image and the texture image produced by the local binary pattern (LBP) method. We applied our method to a piece of aerial image in the urban area of Taizhou, China. The results show that the proposed method has an ability to produce more accurate results than the MS method.

  7. 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

    2016-03-01

    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.

  8. 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.

  9. 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.

  10. 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

  11. Aerial videotape mapping of coastal geomorphic changes

    USGS Publications Warehouse

    Debusschere, Karolien; Penland, Shea; Westphal, Karen A.; Reimer, P. Douglas; McBride, Randolph A.

    1991-01-01

    An aerial geomorphic mapping system was developed to examine the spatial and temporal variability in the coastal geomorphology of Louisiana. Between 1984 and 1990 eleven sequential annual and post-hurricane aerial videotape surveys were flown covering periods of prolonged fair weather, hurricane impacts and subsequent post-storm recoveries. A coastal geomorphic classification system was developed to map the spatial and temporal geomorphic changes between these surveys. The classification system is based on 10 years of shoreline monitoring, analysis of aerial photography for 1940-1989, and numerous field surveys. The classification system divides shorelines into two broad classes: natural and altered. Each class consists of several genetically linked categories of shorelines. Each category is further subdivided into morphologic types on the basis of landform relief, elevation, habitat type, vegetation density and type, and sediment characteristics. The classification is used with imagery from the low-altitude, high-resolution aerial videotape surveys to describe and quantify the longshore and cross-shore geomorphic, sedimentologic, and vegetative character of Louisiana's shoreline systems. The mapping system makes it possible to delineate and map detailed geomorphic habitat changes at a resolution higher than that of conventional vertical aerial photography. Morphologic units are mapped parallel to the regional shoreline from the aerial videotape imagery onto the base maps at a scale of 1:24,000. The base maps were constructed from vertical aerial photography concurrent with the data of the video imagery.

  12. 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.

  13. 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., Jr.; 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

  14. Signature-based image identification

    NASA Astrophysics Data System (ADS)

    Abdel-Mottaleb, Mohamed; Vaithilingam, Gandhimathi; Krishnamachari, Santhana

    1999-11-01

    The use of digital images and video is growing on the Internet and on consumer devices. Digital images and video are easy to manipulate, but this ease of manipulation makes tampering with digital content possible. Examples of the misuse of digital content include violating copyrights of the content and tampering with important material such as contents of video surveillance. In this paper we present an algorithm that extracts a binary signature from an image. This approach can be used to search for possible copyright violations by finding images with signatures close to that of a given image. The experimental results show that the algorithm can be very effective in helping users to retrieve sets of almost identical images from large collections of images. The signature can also be used for tamper detection. We will show that the signatures we extract are immune to quantization errors that result from compression and decompression.

  15. Fast residential area extraction from remote sensing image based on Log-Gabor filter

    NASA Astrophysics Data System (ADS)

    Xiao, Jie; Cai, Chao

    2011-11-01

    Monitoring urbanization may help government agencies and urban region planners in updating land maps and forming long-term plans accordingly. In this paper, a novel method for fast extracting residential area from remote sensing images based on log-Gabor filter was proposed. The method is divided in three steps. Firstly, we detect the edge-oriented urban characteristics in a remote sensing image using log-Gabor filter. Secondly, with the filtering orientations perpendicular to each other, we choose two log-Gabor filter response images to suppress the noise and acquire a smooth spatial region. Thirdly, a set of smooth regions served as residential areas can be extracted using Otsu's method. We tested it on diverse aerial and satellite images and encouraging results were acquired. The comparison of our method with the classical texture analyzing method of co-occurrence matrix demonstrated its superiority.

  16. 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.

  17. Underwater Depth Estimation and Image Restoration Based on Single Images.

    PubMed

    Drews, Paulo L J; Nascimento, Erickson R; Botelho, Silvia S C; Campos, Mario Fernando Montenegro

    2016-01-01

    In underwater environments, the scattering and absorption phenomena affect the propagation of light, degrading the quality of captured images. In this work, the authors present a method based on a physical model of light propagation that takes into account the most significant effects to image degradation: absorption, scattering, and backscattering. The proposed method uses statistical priors to restore the visual quality of the images acquired in typical underwater scenarios. PMID:26960026

  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. 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.

  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. 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

  2. Genetic algorithm for bundle adjustment in aerial panoramic stitching

    NASA Astrophysics Data System (ADS)

    Zhang, Chunxiao; Wen, Gaojin; Wu, Chunnan; Wang, Hongmin; Shang, Zhiming; Zhang, Qian

    2015-03-01

    This paper presents a genetic algorithm for bundle adjustment in aerial panoramic stitching. Compared with the conventional LM (Levenberg-Marquardt) algorithm for bundle adjustment, the proposed bundle adjustment combining the genetic algorithm optimization eliminates the possibility of sticking into the local minimum, and not requires the initial estimation of desired parameters, naturally avoiding the associated steps, that includes the normalization of matches, the computation of homography transformation, the calculations of rotation transformation and the focal length. Since the proposed bundle adjustment is composed of the directional vectors of matches, taking the advantages of genetic algorithm (GA), the Jacobian matrix and the normalization of residual error are not involved in the searching process. The experiment verifies that the proposed bundle adjustment based on the genetic algorithm can yield the global solution even in the unstable aerial imaging condition.

  3. 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.

  4. 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.

  5. Image processing technique based on image understanding architecture

    NASA Astrophysics Data System (ADS)

    Kuvychko, Igor

    2000-12-01

    Effectiveness of image applications is directly based on its abilities to resolve ambiguity and uncertainty in the real images. That requires tight integration of low-level image processing with high-level knowledge-based reasoning, which is the solution of the image understanding problem. This article presents a generic computational framework necessary for the solution of image understanding problem -- Spatial Turing Machine. Instead of tape of symbols, it works with hierarchical networks dually represented as discrete and continuous structures. Dual representation provides natural transformation of the continuous image information into the discrete structures, making it available for analysis. Such structures are data and algorithms at the same time and able to perform graph and diagrammatic operations being the basis of intelligence. They can create derivative structures that play role of context, or 'measurement device,' giving the ability to analyze, and run top-bottom algorithms. Symbols naturally emerge there, and symbolic operations work in combination with new simplified methods of computational intelligence. That makes images and scenes self-describing, and provides flexible ways of resolving uncertainty. Classification of images truly invariant to any transformation could be done via matching their derivative structures. New proposed architecture does not require supercomputers, opening ways to the new image technologies.

  6. Multiple-image encryption based on computational ghost imaging

    NASA Astrophysics Data System (ADS)

    Wu, Jingjing; Xie, Zhenwei; Liu, Zhengjun; Liu, Wei; Zhang, Yan; Liu, Shutian

    2016-01-01

    We propose an optical multiple-image encryption scheme based on computational ghost imaging with the position multiplexing. In the encryption process, each plain image is encrypted into an intensity vector by using the computational ghost imaging with a different diffraction distance. The final ciphertext is generated by superposing all the intensity vectors together. Different from common multiple-image cryptosystems, the ciphertext in the proposed scheme is simply an intensity vector instead of a complex amplitude. Simulation results are presented to demonstrate the validity and security of the proposed multiple-image encryption method. The multiplexing capacity of the proposed method is also investigated. Optical experiment is presented to verify the validity of the proposed scheme in practical application.

  7. 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.

  8. Production-worthy full chip image-based verification

    NASA Astrophysics Data System (ADS)

    Yu, Zongchang; Zhang, Youping; Xiao, Yanjun; Li, Wanyu

    2007-10-01

    At 65nm technology node and below, with the ever-smaller process window, it is no longer sufficient to apply traditional model-based verification at only the nominal condition. Full-chip, full process-window verification has started to integrate into the OPC flow at the 65nm production as a way of preventing potentially weak post-OPC designs from reaching the mask making step. Through process-window analysis can be done by way of simulating wafer images at each of the corresponding focus and exposure dose conditions throughout the process window using an accurate and predictive FEM model. Alternatively, due to the strong correlation between the post-OPC design sensitivity to dose variation and aerial image (AI) quality, the study of through-dose behavior of the post-OPC design can also be carried out by carefully analyzing the AI. These types of analysis can be performed at multiple defocus conditions to assess the robustness of the post-OPC designs with respect to focus and dose variations. In this paper, we study the AI based approach for post-OPC verification in detail. For metal layer, the primary metrics for verification are bridging, necking, and via coverage. In this paper we are mainly interested in studying bridging and necking. The minimum AI value in the open space gives an indication of its susceptibility to bridging in an over-dosed situation. Lower minimum intensity indicates less risk of bridging. Conversely, the maximum AI between the metal lines provides indication of potential necking issues in an under-dosed situation. At times, however, in a complex 2D pattern area, the location as to where the AI reaches either maximum or minimum is not obvious. This requires a full-chip, dense image-based approach to fully explore the AI profile of the entire space of the design. We have developed such an algorithm to find the AI maximums and minimums that will bear true relevance to the bridging and necking analysis. In this paper, we apply the full

  9. Automatic georeferencing of imagery from high-resolution, low-altitude, low-cost aerial platforms

    NASA Astrophysics Data System (ADS)

    Geniviva, Amanda; Faulring, Jason; Salvaggio, Carl

    2014-06-01

    Existing nadir-viewing aerial image databases such as that available on Google Earth contain data from a variety of sources at varying spatial resolutions. Low-cost, low-altitude, high-resolution aerial systems such as unmanned aerial vehicles and balloon- borne systems can provide ancillary data sets providing higher resolution, oblique­ looking data to enhance the data available to the user. This imagery is difficult to georeference due to the different projective geometry present in these data. Even if this data is accompanied by metadata from global positioning system (GPS) and inertial measurement unit (IMU) sensors, the accuracy obtained from low-cost versions of these sensors is limited. Combining automatic image registration techniques with the information provided by the IMU and onboard GPS, it is possible to improve the positioning accuracy of these oblique data sets on the ground plane using existing orthorectified imagery available from sources such as Google Earth. Using both the affine scale-invariant feature transform (ASIFT) and maximally stable extremal regions (MSER), feature detectors aid in automatically detecting correspondences between the obliquely collected images and the base map. These correspondences are used to georeference the high-resolution, oblique image data collected from these low-cost aerial platforms providing the user with an enhanced visualization experience.

  10. 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

  11. 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…

  12. 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.

  13. Depth-based selective image reconstruction using spatiotemporal image analysis

    NASA Astrophysics Data System (ADS)

    Haga, Tetsuji; Sumi, Kazuhiko; Hashimoto, Manabu; Seki, Akinobu

    1999-03-01

    In industrial plants, a remote monitoring system which removes physical tour inspection is often considered desirable. However the image sequence given from the mobile inspection robot is hard to see because interested objects are often partially occluded by obstacles such as pillars or fences. Our aim is to improve the image sequence that increases the efficiency and reliability of remote visual inspection. We propose a new depth-based image processing technique, which removes the needless objects from the foreground and recovers the occluded background electronically. Our algorithm is based on spatiotemporal analysis that enables fine and dense depth estimation, depth-based precise segmentation, and accurate interpolation. We apply this technique to a real time sequence given from the mobile inspection robot. The resulted image sequence is satisfactory in that the operator can make correct visual inspection with less fatigue.

  14. Towards an NV Diamond Based Pressure Imager

    NASA Astrophysics Data System (ADS)

    Milbourne, Timothy; Barry, John; Turner, Matthew; Zhang, Huiliang; Arai, Keigo; Walsworth, Ronald

    2016-05-01

    The ability to image applied pressures is of great interest for various biological and physical applications. Using an array of wires printed on a thin layer of polydimethylsiloxane (PDMS), nitrogen-vacancy (NV) center-based magnetic field imaging techniques may be used to realize a combination of high sensitivity and spatial resolution not offered by current sensing technologies. Here we present the first steps toward such a NV-based pressure imager.

  15. 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.

  16. 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.

  17. Multifunctional imaging probe based on gadofulleride nanoplatform

    NASA Astrophysics Data System (ADS)

    Zheng, Jun-Peng; Liu, Qiao-Ling; Zhen, Ming-Ming; Jiang, Feng; Shu, Chun-Ying; Jin, Chan; Yang, Yongji; Alhadlaq, Hisham A.; Wang, Chun-Ru

    2012-05-01

    A FAR over-expressed tumor targeting multifunctional imaging probe has been fabricated based on gadofulleride nanoplatform. The combination of highly efficient MRI contrast enhancement and sensitive fluorescence imaging along with the preferential uptake toward FAR tumor cells suggest that the obtained multifunctional imaging probe possesses complementary capabilities for anatomical resolution and detection sensitivity.A FAR over-expressed tumor targeting multifunctional imaging probe has been fabricated based on gadofulleride nanoplatform. The combination of highly efficient MRI contrast enhancement and sensitive fluorescence imaging along with the preferential uptake toward FAR tumor cells suggest that the obtained multifunctional imaging probe possesses complementary capabilities for anatomical resolution and detection sensitivity. Electronic supplementary information (ESI) available: Materials, instruments and methods, synthesis details, XPS characterization for estimation of average molecular formula, evaluation of conjugated FA and FITC ratio, zeta potential and fluorescent images. See DOI: 10.1039/c2nr30836c

  18. 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.

  19. Image based SAR product simulation for analysis

    NASA Technical Reports Server (NTRS)

    Domik, G.; Leberl, F.

    1987-01-01

    SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

  20. Fusion of Multi-View and Multi-Scale Aerial Imagery for Real-Time Situation Awareness Applications

    NASA Astrophysics Data System (ADS)

    Zhuo, X.; Kurz, F.; Reinartz, P.

    2015-08-01

    Manned aircraft has long been used for capturing large-scale aerial images, yet the high costs and weather dependence restrict its availability in emergency situations. In recent years, MAV (Micro Aerial Vehicle) emerged as a novel modality for aerial image acquisition. Its maneuverability and flexibility enable a rapid awareness of the scene of interest. Since these two platforms deliver scene information from different scale and different view, it makes sense to fuse these two types of complimentary imagery to achieve a quick, accurate and detailed description of the scene, which is the main concern of real-time situation awareness. This paper proposes a method to fuse multi-view and multi-scale aerial imagery by establishing a common reference frame. In particular, common features among MAV images and geo-referenced airplane images can be extracted by a scale invariant feature detector like SIFT. From the tie point of geo-referenced images we derive the coordinate of corresponding ground points, which are then utilized as ground control points in global bundle adjustment of MAV images. In this way, the MAV block is aligned to the reference frame. Experiment results show that this method can achieve fully automatic geo-referencing of MAV images even if GPS/IMU acquisition has dropouts, and the orientation accuracy is improved compared to the GPS/IMU based georeferencing. The concept for a subsequent 3D classification method is also described in this paper.

  1. 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.

  2. Modeling aerial refueling operations

    NASA Astrophysics Data System (ADS)

    McCoy, Allen B., III

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

  3. 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.

  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. 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

  6. Novel image encryption based on quantum walks.

    PubMed

    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

  7. 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. PMID:27451232

  8. 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

  9. 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. PMID:24790555

  10. 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.

  11. Implantable image sensor based on intra-brain image transmission.

    PubMed

    Sasagawa, Kiyotaka; Ishii, Yoshiaki; Yokota, Shogo; Matsuda, Takashi; Davis, Peter; Zhang, Bing; Li, Keren; Noda, Toshihiko; Tokuda, Takashi; Ohta, Jun

    2013-01-01

    We developed and fabricated a micro-imager based on wireless intra-brain communication using conductive property of living tissues. An pixel array, analog-to-digital converter and transmitter are integrated on a single chip. The dimensions of the chip are 1 mm × 1mm × 0.15 mm. We demonstrate wireless image transmission through phosphate buffer saline as a brain phantom. PMID:24110074

  12. Wavelet based image quality self measurements

    NASA Astrophysics Data System (ADS)

    Al-Jawad, Naseer; Jassim, Sabah

    2010-04-01

    Noise in general is considered to be degradation in image quality. Moreover image quality is measured based on the appearance of the image edges and their clarity. Most of the applications performance is affected by image quality and level of different types of degradation. In general measuring image quality and identifying the type of noise or degradation is considered to be a key factor in raising the applications performance, this task can be very challenging. Wavelet transform now a days, is widely used in different applications. These applications are mostly benefiting from the wavelet localisation in the frequency domain. The coefficients of the high frequency sub-bands in wavelet domain are represented by Laplace histogram. In this paper we are proposing to use the Laplace distribution histogram to measure the image quality and also to identify the type of degradation affecting the given image. Image quality and the level of degradation are mostly measured using a reference image with reasonable quality. The discussed Laplace distribution histogram provides a self testing measurement for the quality of the image. This measurement is based on constructing the theoretical Laplace distribution histogram of the high frequency wavelet sub-band. This construction is based on the actual standard deviation, then to be compared with the actual Laplace distribution histogram. The comparison is performed using histogram intersection method. All the experiments are performed using the extended Yale database.

  13. Image content authentication based on channel coding

    NASA Astrophysics Data System (ADS)

    Zhang, Fan; Xu, Lei

    2008-03-01

    The content authentication determines whether an image has been tampered or not, and if necessary, locate malicious alterations made on the image. Authentication on a still image or a video are motivated by recipient's interest, and its principle is that a receiver must be able to identify the source of this document reliably. Several techniques and concepts based on data hiding or steganography designed as a means for the image authentication. This paper presents a color image authentication algorithm based on convolution coding. The high bits of color digital image are coded by the convolution codes for the tamper detection and localization. The authentication messages are hidden in the low bits of image in order to keep the invisibility of authentication. All communications channels are subject to errors introduced because of additive Gaussian noise in their environment. Data perturbations cannot be eliminated but their effect can be minimized by the use of Forward Error Correction (FEC) techniques in the transmitted data stream and decoders in the receiving system that detect and correct bits in error. This paper presents a color image authentication algorithm based on convolution coding. The message of each pixel is convolution encoded with the encoder. After the process of parity check and block interleaving, the redundant bits are embedded in the image offset. The tamper can be detected and restored need not accessing the original image.

  14. 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. PMID:27016450

  15. 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%.

  16. 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.

  17. Technical development for automatic aerial triangulation of high resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Xiong, Zhen

    algorithms have been investigated. Those algorithms can be grouped into two categories: area based and feature based. However, both area based and feature based algorithms share a common limitation: ambiguity in a homogeneous area. Neither of the methods could efficiently extract tie points from the low texture area. In this research, a robust interest point matching algorithm has been developed. This algorithm incorporates spatial information through constructing a control network from 'super' interest points. Experiments show that the proposed algorithm almost solved the ambiguity problem in a "poorly textured" area. Sensor model refinement is the core of aerial triangulation. The challenge is the use of the Rational Polynomial Camera (RPC) model in some high resolution satellites, such as IKONOS and QuickBird. Although some direct methods and indirect methods have been investigated, they either require excessive information concerning the RPC which is unavailable to the public (direct methods), or has rigorous conditions which seriously limits its applications (indirect methods). In this research, a generic method was developed for RPC refinement. The proposed method does not need any information about the RPC itself, and is not restrained by any conditions. Theoretically, the proposed generic method can be used in any kind of camera in which RPC is used as a sensor model. Based on the proposed generic method for RPC refinement, a robust bundle block adjustment model is developed. This bundle block adjustment algorithm can efficiently process the high resolution satellite images and can reach sub-pixel accuracy in image space and sub-meter accuracy in object space. Experiments were conducted to verify this application.

  18. 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.

  19. Segmentation-based CT image compression

    NASA Astrophysics Data System (ADS)

    Thammineni, Arunoday; Mukhopadhyay, Sudipta; Kamath, Vidya

    2004-04-01

    The existing image compression standards like JPEG and JPEG 2000, compress the whole image as a single frame. This makes the system simple but inefficient. The problem is acute for applications where lossless compression is mandatory viz. medical image compression. If the spatial characteristics of the image are considered, it can give rise to a more efficient coding scheme. For example, CT reconstructed images have uniform background outside the field of view (FOV). Even the portion within the FOV can be divided as anatomically relevant and irrelevant parts. They have distinctly different statistics. Hence coding them separately will result in more efficient compression. Segmentation is done based on thresholding and shape information is stored using 8-connected differential chain code. Simple 1-D DPCM is used as the prediction scheme. The experiments show that the 1st order entropies of images fall by more than 11% when each segment is coded separately. For simplicity and speed of decoding Huffman code is chosen for entropy coding. Segment based coding will have an overhead of one table per segment but the overhead is minimal. Lossless compression of image based on segmentation resulted in reduction of bit rate by 7%-9% compared to lossless compression of whole image as a single frame by the same prediction coder. Segmentation based scheme also has the advantage of natural ROI based progressive decoding. If it is allowed to delete the diagnostically irrelevant portions, the bit budget can go down as much as 40%. This concept can be extended to other modalities.

  20. "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…

  1. ENVIRONMENTAL APPLICATION OF LOW ALTITUDE AERIAL PHOTOGRAPHY

    EPA Science Inventory

    The most practical avenue for development of these goals is to continue to use the LAAPS system at field sites that require aerial imaging. For the sake of convenience, I believe that the local field sites can provide a convenient location to develop new applications and test enh...

  2. 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.

  3. 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

  4. 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…

  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. 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

  7. 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.

  8. 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

  9. 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

  10. MODEL-BASED IMAGE RECONSTRUCTION FOR MRI

    PubMed Central

    Fessler, Jeffrey A.

    2010-01-01

    Magnetic resonance imaging (MRI) is a sophisticated and versatile medical imaging modality. Traditionally, MR images are reconstructed from the raw measurements by a simple inverse 2D or 3D fast Fourier transform (FFT). However, there are a growing number of MRI applications where a simple inverse FFT is inadequate, e.g., due to non-Cartesian sampling patterns, non-Fourier physical effects, nonlinear magnetic fields, or deliberate under-sampling to reduce scan times. Such considerations have led to increasing interest in methods for model-based image reconstruction in MRI. PMID:21135916

  11. Binary image authentication based on watermarking algorithm

    NASA Astrophysics Data System (ADS)

    Masoodifar, Behrang; Hashemi, S. Mojtaba; Zarei, Omid

    2011-06-01

    A digital image watermark embedding and extracting algorithm is presented based on the Finite Ridgelet Transform (FRT) which can efficiently represent image with linear singularities. In general RT also has directional sensitivity so that among the transformed coefficients the most significant one represents the most energetic direction of straight edges in an image. In this paper effect of RT is compared with wavelet transform in watermarking application. Different noises with different PSNR are added into the watermarked image in the experiments and the results are of robustness and transparency.

  12. Spin scan tomographic array-based imager.

    PubMed

    Hovland, Harald

    2014-12-29

    This work presents a novel imaging device based on tomographic reconstruction. Similar in certain aspects to the earlier presented tomographic scanning (TOSCA) principle, it provides several important enhancements. The device described generates a stream of one-dimensional projections from a linear array of thin stripe detectors onto which the (circular) image of the scene is rotated. A two-dimensional image is then reproduced from the one-dimensional signals using tomographic processing techniques. A demonstrator is presented. Various aspects of the design and construction are discussed, and resulting images and movies are presented. PMID:25607168

  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%). PMID:24897869

  14. Image-Based Flow Modeling

    NASA Astrophysics Data System (ADS)

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

    2009-11-01

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

  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. Reverse-Time Migration Based Optical Imaging.

    PubMed

    Wang, Zhiyong; Ding, Hao; Lu, Guijin; Bi, Xiaohong

    2016-01-01

    We theoretically demonstrated a new optical imaging technique based on reverse-time migration (RTM) for reconstructing optical structures in homogeneous media for the first time. RTM is a powerful wave-equation-based method to reconstruct the image of the structure by modeling the wave propagation inside the media with both forward modeling and reverse-time extrapolation. While RTM is commonly used with acoustic seismic waves, this paper represents the first effort to develop optical RTM imaging method for biomedical research. To refine the image quality, we further developed new methods to suppress the low-wavenumber artifact (LWA). When compared with the conventional means for LWA suppression such as Laplacian filtering, illumination normalization, and the ratio method, our new derivative-based and power-image methods are able to significantly reduce LWA, resulting in high-quality reconstructed images with sufficient contrasts and spatial resolutions for structure identification. The optical RTM imaging technique may provide a new platform for non-invasive optical imaging of structures in deep layers of tissues for biomedical applications. PMID:26292337

  17. Edge-based image restoration.

    PubMed

    Rareş, Andrei; Reinders, Marcel J T; Biemond, Jan

    2005-10-01

    In this paper, we propose a new image inpainting algorithm that relies on explicit edge information. The edge information is used both for the reconstruction of a skeleton image structure in the missing areas, as well as for guiding the interpolation that follows. The structure reconstruction part exploits different properties of the edges, such as the colors of the objects they separate, an estimate of how well one edge continues into another one, and the spatial order of the edges with respect to each other. In order to preserve both sharp and smooth edges, the areas delimited by the recovered structure are interpolated independently, and the process is guided by the direction of the nearby edges. The novelty of our approach lies primarily in exploiting explicitly the constraint enforced by the numerical interpretation of the sequential order of edges, as well as in the pixel filling method which takes into account the proximity and direction of edges. Extensive experiments are carried out in order to validate and compare the algorithm both quantitatively and qualitatively. They show the advantages of our algorithm and its readily application to real world cases. PMID:16238052

  18. An image mosaic method based on corner

    NASA Astrophysics Data System (ADS)

    Jiang, Zetao; Nie, Heting

    2015-08-01

    In view of the shortcomings of the traditional image mosaic, this paper describes a new algorithm for image mosaic based on the Harris corner. Firstly, Harris operator combining the constructed low-pass smoothing filter based on splines function and circular window search is applied to detect the image corner, which allows us to have better localisation performance and effectively avoid the phenomenon of cluster. Secondly, the correlation feature registration is used to find registration pair, remove the false registration using random sampling consensus. Finally use the method of weighted trigonometric combined with interpolation function for image fusion. The experiments show that this method can effectively remove the splicing ghosting and improve the accuracy of image mosaic.

  19. Fast single image dehazing based on image fusion

    NASA Astrophysics Data System (ADS)

    Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian

    2015-01-01

    Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.

  20. No-reference image quality metric based on image classification

    NASA Astrophysics Data System (ADS)

    Choi, Hyunsoo; Lee, Chulhee

    2011-12-01

    In this article, we present a new no-reference (NR) objective image quality metric based on image classification. We also propose a new blocking metric and a new blur metric. Both metrics are NR metrics since they need no information from the original image. The blocking metric was computed by considering that the visibility of horizontal and vertical blocking artifacts can change depending on background luminance levels. When computing the blur metric, we took into account the fact that blurring in edge regions is generally more sensitive to the human visual system. Since different compression standards usually produce different compression artifacts, we classified images into two classes using the proposed blocking metric: one class that contained blocking artifacts and another class that did not contain blocking artifacts. Then, we used different quality metrics based on the classification results. Experimental results show that each metric correlated well with subjective ratings, and the proposed NR image quality metric consistently provided good performance with various types of content and distortions.

  1. Aerial Photography Summary Record System

    USGS Publications Warehouse

    U.S. Geological Survey

    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.

  2. Aerial Terrain Mapping Using Unmanned Aerial Vehicle Approach

    NASA Astrophysics Data System (ADS)

    Tahar, K. N.

    2012-08-01

    This paper looks into the latest achievement in the low-cost Unmanned Aerial Vehicle (UAV) technology in their capacity to map the semi-development areas. The objectives of this study are to establish a new methodology or a new algorithm in image registration during interior orientation process and to determine the accuracy of the photogrammetric products by using UAV images. Recently, UAV technology has been used in several applications such as mapping, agriculture and surveillance. The aim of this study is to scrutinize the usage of UAV to map the semi-development areas. The performance of the low cost UAV mapping study was established on a study area with two image processing methods so that the results could be comparable. A non-metric camera was attached at the bottom of UAV and it was used to capture images at both sites after it went through several calibration steps. Calibration processes were carried out to determine focal length, principal distance, radial lens distortion, tangential lens distortion and affinity. A new method in image registration for a non-metric camera is discussed in this paper as a part of new methodology of this study. This method used the UAV Global Positioning System (GPS) onboard to register the UAV image for interior orientation process. Check points were established randomly at both sites using rapid static Global Positioning System. Ground control points are used for exterior orientation process, and check point is used for accuracy assessment of photogrammetric product. All acquired images were processed in a photogrammetric software. Two methods of image registration were applied in this study, namely, GPS onboard registration and ground control point registration. Both registrations were processed by using photogrammetric software and the result is discussed. Two results were produced in this study, which are the digital orthophoto and the digital terrain model. These results were analyzed by using the root mean square

  3. 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

  4. A multicore based parallel image registration method.

    PubMed

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

    2009-01-01

    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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  6. Open Source Image-Processing Tools for Low-Cost Uav-Based Landslide Investigations

    NASA Astrophysics Data System (ADS)

    Niethammer, U.; Rothmund, S.; Schwaderer, U.; Zeman, J.; Joswig, M.

    2011-09-01

    In recent years, the application of unmanned aerial vehicles (UAVs) has become more common and the availability of lightweight digital cameras has enabled UAV-systems to represent affordable and practical remote sensing platforms, allowing flexible and high- resolution remote sensing investigations. In the course of numerous UAV-based remote sensing campaigns significant numbers of airborne photographs of two different landslides have been acquired. These images were used for ortho-mosaic and digital terrain model (DTM) generation, thus allowing for high-resolution landslide monitoring. Several new open source image- and DTM- processing tools are now providing a complete remote sensing working cycle with the use of no commercial hard- or software.

  7. Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aerial multispectral images are a good source of crop, soil, and ground coverage information. Spectral reflectance indices provide a useful tool for monitoring crop growing status. A series of aerial images were acquired by an airborne MS4100 multispectral imaging system on the cotton and soybean f...

  8. Robust vehicle detection in low-resolution aerial imagery

    NASA Astrophysics Data System (ADS)

    Sahli, Samir; Ouyang, Yueh; Sheng, Yunlong; Lavigne, Daniel A.

    2010-04-01

    We propose a feature-based approach for vehicle detection in aerial imagery with 11.2 cm/pixel resolution. The approach is free of all constraints related to the vehicles appearance. The scale-invariant feature transform (SIFT) is used to extract keypoints in the image. The local structure in the neighbouring of the SIFT keypoints is described by 128 gradient orientation based features. A Support Vector Machine is used to create a model which is able to predict if the SIFT keypoints belong to or not to car structures in the image. The collection of SIFT keypoints with car label are clustered in the geometric space into subsets and each subset is associated to one car. This clustering is based on the Affinity Propagation algorithm modified to take into account specific spatial constraint related to geometry of cars at the given resolution.

  9. Wavelet-based stereo images reconstruction using depth images

    NASA Astrophysics Data System (ADS)

    Jovanov, Ljubomir; Pižurica, Aleksandra; Philips, Wilfried

    2007-09-01

    It is believed by many that three-dimensional (3D) television will be the next logical development toward a more natural and vivid home entertaiment experience. While classical 3D approach requires the transmission of two video streams, one for each view, 3D TV systems based on depth image rendering (DIBR) require a single stream of monoscopic images and a second stream of associated images usually termed depth images or depth maps, that contain per-pixel depth information. Depth map is a two-dimensional function that contains information about distance from camera to a certain point of the object as a function of the image coordinates. By using this depth information and the original image it is possible to reconstruct a virtual image of a nearby viewpoint by projecting the pixels of available image to their locations in 3D space and finding their position in the desired view plane. One of the most significant advantages of the DIBR is that depth maps can be coded more efficiently than two streams corresponding to left and right view of the scene, thereby reducing the bandwidth required for transmission, which makes it possible to reuse existing transmission channels for the transmission of 3D TV. This technique can also be applied for other 3D technologies such as multimedia systems. In this paper we propose an advanced wavelet domain scheme for the reconstruction of stereoscopic images, which solves some of the shortcommings of the existing methods discussed above. We perform the wavelet transform of both the luminance and depth images in order to obtain significant geometric features, which enable more sensible reconstruction of the virtual view. Motion estimation employed in our approach uses Markov random field smoothness prior for regularization of the estimated motion field. The evaluation of the proposed reconstruction method is done on two video sequences which are typically used for comparison of stereo reconstruction algorithms. The results demonstrate

  10. 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.

  11. An image adaptive, wavelet-based watermarking of digital images

    NASA Astrophysics Data System (ADS)

    Agreste, Santa; Andaloro, Guido; Prestipino, Daniela; Puccio, Luigia

    2007-12-01

    In digital management, multimedia content and data can easily be used in an illegal way--being copied, modified and distributed again. Copyright protection, intellectual and material rights protection for authors, owners, buyers, distributors and the authenticity of content are crucial factors in solving an urgent and real problem. In such scenario digital watermark techniques are emerging as a valid solution. In this paper, we describe an algorithm--called WM2.0--for an invisible watermark: private, strong, wavelet-based and developed for digital images protection and authenticity. Using discrete wavelet transform (DWT) is motivated by good time-frequency features and well-matching with human visual system directives. These two combined elements are important in building an invisible and robust watermark. WM2.0 works on a dual scheme: watermark embedding and watermark detection. The watermark is embedded into high frequency DWT components of a specific sub-image and it is calculated in correlation with the image features and statistic properties. Watermark detection applies a re-synchronization between the original and watermarked image. The correlation between the watermarked DWT coefficients and the watermark signal is calculated according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has shown to be resistant against geometric, filtering and StirMark attacks with a low rate of false alarm.

  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. Observing snow cover using unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Spallek, Waldemar; Witek, Matylda; Niedzielski, Tomasz

    2016-04-01

    Snow cover is a key environmental variable that influences high flow events driven by snow-melt episodes. Estimates of snow extent (SE), snow depth (SD) and snow water equivalent (SWE) allow to approximate runoff caused by snow-melt episodes. These variables are purely spatial characteristics, and hence their pointwise measurements using terrestrial monitoring systems do not offer the comprehensive and fully-spatial information on water storage in snow. Existing satellite observations of snow reveal moderate spatial resolution which, not uncommonly, is not fine enough to estimate the above-mentioned snow-related variables for small catchments. High-resolution aerial photographs and the resulting orthophotomaps and digital surface models (DSMs), obtained using unmanned aerial vehicles (UAVs), may offer spatial resolution of 3 cm/px. The UAV-based observation of snow cover may be done using the near-infrared (NIR) cameras and visible-light cameras. Since the beginning of 2015, in frame of the research project no. LIDER/012/223/L-5/13/NCBR/2014 financed by the National Centre for Research and Development of Poland, we have performed a series of the UAV flights targeted at four sites in the Kwisa catchment in the Izerskie Mts. (part of the Sudetes, SW Poland). Observations are carried out with the ultralight UAV swinglet CAM (produced by senseFly, lightweight 0.5 kg, wingspan 80 cm) which enables on-demand sampling at low costs. The aim of the field work is to acquire aerial photographs taken using the visible-light and NIR cameras for a purpose of producing time series of DSMs and orthophotomaps with snow cover for all sites. The DSMs are used to calculate SD as difference between observational (with snow) and reference (without snow) models. In order to verify such an approach to compute SD we apply several procedures, one of which is the estimation of SE using the corresponding orthophotomaps generated on a basis of visual-light and NIR images. The objective of this

  14. 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.

  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. 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.

  17. 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.

  18. 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.

  19. Optimal halftoning for network-based imaging

    NASA Astrophysics Data System (ADS)

    Ostromoukhov, Victor

    2000-12-01

    In this contribution, we introduce a multiple depth progressive representation for network-based still and moving images. A simple quantization algorithm associated with this representation provides optimal image quality. By optimum, we mean the best possible visual quality for a given value of information under real life constraints such as physical, psychological , or legal constraints. A special variant of the algorithm, multi-depth coherent error diffusion, addresses a specific problem of temporal coherence between frames in moving images. The output produced with our algorithm is visually pleasant because its Fourier spectrum is close to the 'blue noise'.

  20. 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.

  1. Computer vision for image-based transcriptomics.

    PubMed

    Stoeger, Thomas; Battich, Nico; Herrmann, Markus D; Yakimovich, Yauhen; Pelkmans, Lucas

    2015-09-01

    Single-cell transcriptomics has recently emerged as one of the most promising tools for understanding the diversity of the transcriptome among single cells. Image-based transcriptomics is unique compared to other methods as it does not require conversion of RNA to cDNA prior to signal amplification and transcript quantification. Thus, its efficiency in transcript detection is unmatched by other methods. In addition, image-based transcriptomics allows the study of the spatial organization of the transcriptome in single cells at single-molecule, and, when combined with superresolution microscopy, nanometer resolution. However, in order to unlock the full power of image-based transcriptomics, robust computer vision of single molecules and cells is required. Here, we shortly discuss the setup of the experimental pipeline for image-based transcriptomics, and then describe in detail the algorithms that we developed to extract, at high-throughput, robust multivariate feature sets of transcript molecule abundance, localization and patterning in tens of thousands of single cells across the transcriptome. These computer vision algorithms and pipelines can be downloaded from: https://github.com/pelkmanslab/ImageBasedTranscriptomics. PMID:26014038

  2. 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.

  3. 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. PMID:23405088

  4. 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

  5. Aerial photographic reproductions

    USGS Publications Warehouse

    U.S. Geological Survey

    1971-01-01

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

  6. 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.

  7. Aerial Perspective Artistry

    ERIC Educational Resources Information Center

    Wolfe, Linda

    2010-01-01

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

  8. Average Gait Differential Image Based Human Recognition

    PubMed Central

    Chen, Jinyan; Liu, Jiansheng

    2014-01-01

    The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI) is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI), AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA) is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition. PMID:24895648

  9. 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.

  10. 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. PMID:17218741

  11. 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

  12. Ultrasound image-based respiratory motion tracking

    NASA Astrophysics Data System (ADS)

    Hwang, Youngkyoo; Kim, Jung-Bae; Kim, Yong Sun; Bang, Won-Chul; Kim, James D. K.; Kim, ChangYeong

    2012-03-01

    Respiratory motion tracking has been issues for MR/CT imaging and noninvasive surgery such as HIFU and radiotherapy treatment when we apply these imaging or therapy technologies to moving organs such as liver, kidney or pancreas. Currently, some bulky and burdensome devices are placed externally on skin to estimate respiratory motion of an organ. It estimates organ motion indirectly using skin motion, not directly using organ itself. In this paper, we propose a system that measures directly the motion of organ itself only using ultrasound image. Our system has automatically selected a window in image sequences, called feature window, which is able to measure respiratory motion robustly even to noisy ultrasound images. The organ's displacement on each ultrasound image has been directly calculated through the feature window. It is very convenient to use since it exploits a conventional ultrasound probe. In this paper, we show that our proposed method can robustly extract respiratory motion signal with regardless of reference frame. It is superior to other image based method such as Mutual Information (MI) or Correlation Coefficient (CC). They are sensitive to what the reference frame is selected. Furthermore, our proposed method gives us clear information of the phase of respiratory cycle such as during inspiration or expiration and so on since it calculate not similarity measurement like MI or CC but actual organ's displacement.

  13. 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

  14. Image enhancement based on edge boosting algorithm

    NASA Astrophysics Data System (ADS)

    Ngernplubpla, Jaturon; Chitsobhuk, Orachat

    2015-12-01

    In this paper, a technique for image enhancement based on proposed edge boosting algorithm to reconstruct high quality image from a single low resolution image is described. The difficulty in single-image super-resolution is that the generic image priors resided in the low resolution input image may not be sufficient to generate the effective solutions. In order to achieve a success in super-resolution reconstruction, efficient prior knowledge should be estimated. The statistics of gradient priors in terms of priority map based on separable gradient estimation, maximum likelihood edge estimation, and local variance are introduced. The proposed edge boosting algorithm takes advantages of these gradient statistics to select the appropriate enhancement weights. The larger weights are applied to the higher frequency details while the low frequency details are smoothed. From the experimental results, the significant performance improvement quantitatively and perceptually is illustrated. It can be seen that the proposed edge boosting algorithm demonstrates high quality results with fewer artifacts, sharper edges, superior texture areas, and finer detail with low noise.

  15. 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. PMID:26828757

  16. Metagratings for Diffraction Based, Compact, Holographic Imaging

    NASA Astrophysics Data System (ADS)

    Inampudi, Sandeep; Podolskiy, Viktor; Multiscale Electromagnetics Group Team

    2013-03-01

    Recent developments in semiconductor technology brought to life a new generation of highly-compact visible-frequency cameras. Unfortunately, straight forward extension of this progress to low-frequency domains (such as mid-IR imaging) is impossible since the pixel size at these frequencies is limited by free-space diffraction limit. Here we present an approach to realize highly-compact imaging systems at lower frequencies. Our approach takes advantage of high refractive index of materials commonly utilized in semiconductor detectors of mid-IR radiation, accompanied by metagratings, structures with engineered diffraction properties, to achieve a 10-fold reduction in the pixel size. In contrast to conventional refraction-based imaging, the approach essentially produces a digital hologram - a 2D projection of the 3D optical field, enabling a post-imaging ``refocusing'' of the picture. The perspectives of numerical recovery of the optical field and the stability of such recovery are discussed.

  17. 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

  18. Intelligent Image Based Computer Aided Education (IICAE)

    NASA Astrophysics Data System (ADS)

    David, Amos A.; Thiery, Odile; Crehange, Marion

    1989-03-01

    Artificial Intelligence (AI) has found its way into Computer Aided Education (CAE), and there are several systems constructed to put in evidence its interesting advantages. We believe that images (graphic or real) play an important role in learning. However, the use of images, outside their use as illustration, makes it necessary to have applications such as AI. We shall develop the application of AI in an image based CAE and briefly present the system under construction to put in evidence our concept. We shall also elaborate a methodology for constructing such a system. Futhermore we shall briefly present the pedagogical and psychological activities in a learning process. Under the pedagogical and psychological aspect of learning, we shall develop areas such as the importance of image in learning both as pedagogical objects as well as means for obtaining psychological information about the learner. We shall develop the learner's model, its use, what to build into it and how. Under the application of AI in an image based CAE, we shall develop the importance of AI in exploiting the knowledge base in the learning environment and its application as a means of implementing pedagogical strategies.

  19. 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

  20. Multispectral image fusion based on fractal features

    NASA Astrophysics Data System (ADS)

    Tian, Jie; Chen, Jie; Zhang, Chunhua

    2004-01-01

    Imagery sensors have been one indispensable part of the detection and recognition systems. They are widely used to the field of surveillance, navigation, control and guide, et. However, different imagery sensors depend on diverse imaging mechanisms, and work within diverse range of spectrum. They also perform diverse functions and have diverse circumstance requires. So it is unpractical to accomplish the task of detection or recognition with a single imagery sensor under the conditions of different circumstances, different backgrounds and different targets. Fortunately, the multi-sensor image fusion technique emerged as important route to solve this problem. So image fusion has been one of the main technical routines used to detect and recognize objects from images. While, loss of information is unavoidable during fusion process, so it is always a very important content of image fusion how to preserve the useful information to the utmost. That is to say, it should be taken into account before designing the fusion schemes how to avoid the loss of useful information or how to preserve the features helpful to the detection. In consideration of these issues and the fact that most detection problems are actually to distinguish man-made objects from natural background, a fractal-based multi-spectral fusion algorithm has been proposed in this paper aiming at the recognition of battlefield targets in the complicated backgrounds. According to this algorithm, source images are firstly orthogonally decomposed according to wavelet transform theories, and then fractal-based detection is held to each decomposed image. At this step, natural background and man-made targets are distinguished by use of fractal models that can well imitate natural objects. Special fusion operators are employed during the fusion of area that contains man-made targets so that useful information could be preserved and features of targets could be extruded. The final fused image is reconstructed from the

  1. 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.

  2. 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.

  3. 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.

  4. 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).

  5. 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.

  6. 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...

  7. 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

  8. 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.

  9. 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. PMID:27410537

  10. Text Indexing of Images Based on Graphical Image Content.

    ERIC Educational Resources Information Center

    Patrick, Timothy B.; Sievert, MaryEllen C.; Popescu, Mihail

    1999-01-01

    Describes an alternative method for indexing images in an image database. The method consists of manually indexing a selected reference image, and then using retrieval by graphical content to automatically transfer the manually assigned index terms from the reference image to the images to be indexed. (AEF)

  11. Bayer image parallel decoding based on GPU

    NASA Astrophysics Data System (ADS)

    Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua

    2012-11-01

    In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.

  12. An image registration based ultrasound probe calibration

    NASA Astrophysics Data System (ADS)

    Li, Xin; Kumar, Dinesh; Sarkar, Saradwata; Narayanan, Ram

    2012-02-01

    Reconstructed 3D ultrasound of prostate gland finds application in several medical areas such as image guided biopsy, therapy planning and dose delivery. In our application, we use an end-fire probe rotated about its axis to acquire a sequence of rotational slices to reconstruct 3D TRUS (Transrectal Ultrasound) image. The image acquisition system consists of an ultrasound transducer situated on a cradle directly attached to a rotational sensor. However, due to system tolerances, axis of probe does not align exactly with the designed axis of rotation resulting in artifacts in the 3D reconstructed ultrasound volume. We present a rigid registration based automatic probe calibration approach. The method uses a sequence of phantom images, each pair acquired at angular separation of 180 degrees and registers corresponding image pairs to compute the deviation from designed axis. A modified shadow removal algorithm is applied for preprocessing. An attribute vector is constructed from image intensity and a speckle-insensitive information-theoretic feature. We compare registration between the presented method and expert-corrected images in 16 prostate phantom scans. Images were acquired at multiple resolutions, and different misalignment settings from two ultrasound machines. Screenshots from 3D reconstruction are shown before and after misalignment correction. Registration parameters from automatic and manual correction were found to be in good agreement. Average absolute differences of translation and rotation between automatic and manual methods were 0.27 mm and 0.65 degree, respectively. The registration parameters also showed lower variability for automatic registration (pooled standard deviation σtranslation = 0.50 mm, σrotation = 0.52 degree) compared to the manual approach (pooled standard deviation σtranslation = 0.62 mm, σrotation = 0.78 degree).

  13. 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

  14. 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.

  15. Advanced MEMS-based infrared imager

    NASA Astrophysics Data System (ADS)

    Chen, Ming

    2003-04-01

    Infrared radiation imager is of important for a wide range of applications. IR infrared imagers have not been widely available due to cost and complexity issues. A major cost of IR imager is associated with the requirements of cooling and pixel-level integration with electronic amplifier and read-out circuitry that are often incompatible with the detector materials. Recent research activities have lead to a new class of IR imager based on thermally isolated MEMS (micro-electromechanical systems) arrays whose bending can be directly detected by optical means. This approach eliminates the need for cooling and complex electronic multiplexers, holding the potential to drastically reduce IR imager cost. However, MEMS based IR imaging devices demonstrated to date are less sensitive than the commercially available ones. We have established a comprehensive finite element model (FEM) using Ansys tool. An accurate computer model for the proposed MEME IR detector is critical for the device development and fabrication. The model greatly enhanced our capability to cost effectively optimize the design from concept to fabrication layout. Our model predicts the deformation of this pixel structure under a surface stress for both thermal and photo-induced effects under various conditions. This simulation model provided a design base for new generation of optical MEMS IR sensors that has higher sensitivity and the potential of incorporating passive thermal amplification. Our simple MEMS design incorporates optical read-out, which eliminates the drawback of electronic means that inevitably introduce additional signal loss due to thermal contact made to the detector element. When packaged under vacuum environment, significant sensitivity improvement is anticipated. The deflection of a cantilever as a function of a rise in its temperature is determined by the classical thermomechanical governing equation for a bimaterial cantilever beam. Our finite element model is established using

  16. 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.

  17. 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.

  18. AERIAL RADIOLOGICAL SURVEYS

    SciTech Connect

    Proctor, A.E.

    1997-06-09

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