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Sample records for aerial image based

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

    PubMed

    Yamamoto, Hirotsugu; Tomiyama, Yuka; Suyama, Shiro

    2014-11-01

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

  2. 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.

  3. Aerial Image Systems

    NASA Astrophysics Data System (ADS)

    Clapp, Robert E.

    1987-09-01

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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  6. Coastline Extraction from Aerial Images Based on Edge Detection

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  7. Aerial Photographs and Satellite Images

    USGS Publications Warehouse

    ,

    1997-01-01

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

  8. 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.

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

    NASA Astrophysics Data System (ADS)

    Vozenilek, Vit

    2015-12-01

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

  10. 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.

  11. 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

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

    NASA Astrophysics Data System (ADS)

    Chen, Haijun; Houkes, Zweitze

    1998-09-01

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

  13. 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.

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

    PubMed

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

    2015-02-02

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

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

    Chen, Haijun; Houkes, Zweitze

    1997-12-01

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

  18. Discovering discriminative graphlets for aerial image categories recognition.

    PubMed

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

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  20. 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

  1. 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.

  2. [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.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Sun, Bo; He, Jun; Li, Hongyu

    2008-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-11-01

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

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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...

  14. 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.

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

    PubMed

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

    2013-01-01

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

  16. 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

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

    PubMed Central

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

    2013-01-01

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

  18. 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.

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

    SciTech Connect

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

    2010-02-12

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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

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

    PubMed

    Kakeya, Hideki; Ishizuka, Shuta; Sato, Yuya

    2014-10-01

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

  6. 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.

  7. Aberration analysis in aerial images formed by lithographic lenses

    NASA Astrophysics Data System (ADS)

    Freitag, Wolfgang; Grossmann, Wilfried; Grunewald, Uwe

    1992-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Ostrowski, W.

    2016-10-01

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

  9. 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.

  10. 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

  11. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2005-01-01

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

  13. 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

  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. 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

  17. 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

  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. 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

  20. 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.

  1. Direct Penguin Counting Using Unmanned Aerial Vehicle Image

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

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

    SciTech Connect

    Jadkowski, M.A.; Convery, P.

    1996-02-01

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

  7. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  10. 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

  11. 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...

  12. 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...

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  15. 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

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  18. 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.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Fernandez, Paz; Whitworth, Malcolm

    2016-10-01

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

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

    PubMed

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

    2016-02-01

    Fast and accurately categorizing the millions of aerial images on Google Maps is a useful technique in pattern recognition. Existing methods cannot handle this task successfully due to two reasons: 1) the aerial images' topologies are the key feature to distinguish their categories, but they cannot be effectively encoded by a conventional visual codebook and 2) it is challenging to build a realtime image categorization system, as some geo-aware Apps update over 20 aerial images per second. To solve these problems, we propose an efficient aerial image categorization algorithm. It focuses on learning a discriminative topological codebook of aerial images under a multitask learning framework. The pipeline can be summarized as follows. We first construct a region adjacency graph (RAG) that describes the topology of each aerial image. Naturally, aerial image categorization can be formulated as RAG-to-RAG matching. According to graph theory, RAG-to-RAG matching is conducted by enumeratively comparing all their respective graphlets (i.e., small subgraphs). To alleviate the high time consumption, we propose to learn a codebook containing topologies jointly discriminative to multiple categories. The learned topological codebook guides the extraction of the discriminative graphlets. Finally, these graphlets are integrated into an AdaBoost model for predicting aerial image categories. Experimental results show that our approach is competitive to several existing recognition models. Furthermore, over 24 aerial images are processed per second, demonstrating that our approach is ready for real-world applications. PMID:25794407

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

    PubMed

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

    2016-02-01

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

  3. Building FAÇADE Separation in Vertical Aerial Images

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  4. 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…

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  14. 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.

  15. 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.

  16. 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.

  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. Net-Faim: distributed computation of aerial images

    NASA Astrophysics Data System (ADS)

    Hollerbach, Uwe

    1998-06-01

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

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. Rule-Based Interpreting Of Aerial Photographs Using LES

    NASA Astrophysics Data System (ADS)

    Perkins, W. A.; Laffey, T. J.; Nguyen, T. A.

    1985-04-01

    Human photo-interpreters use expert knowledge and contextual information to help them analyze a scene. We have experimented with the Lockheed Expert System (LES) to see if contextual information can be useful in interpreting aerial photographs. First, the grey-scale image is segmented into uniform or slowly-varying intensity regions or contiguous textured regions using an edge-based segmentation technique. Next, the system computes a set of attributes for each region. Some of these attributes are based on local properties of that region only (e.g., area, average-intensity, texture-strength, etc.), while others are based on contextual or global information (e.g., adjacent-regions and nearby-regions). Finally, LES is given the task of classifying all the regions using the attribute values. It makes use of multiple goals and multiple rule sets to determine the best classification; regions, which do not satisfy any of the rules, are left unclassified. Unlike programs which use statistical methods, LES uses contextual information such as the fact that cars are likely to be adjacent to roads, which significantly improves its performance on regions which are difficult to classify.

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

    NASA Astrophysics Data System (ADS)

    Zhou, Qianfei; Liu, Jinghong

    2015-01-01

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

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Grigillo, D.; Kanjir, U.

    2012-07-01

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

  7. 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.

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

    NASA Technical Reports Server (NTRS)

    Bayard, David S.; Padgett, Curtis W.

    2012-01-01

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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  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. 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.

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

    NASA Astrophysics Data System (ADS)

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

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

  16. 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...

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

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

  19. Object-Based Arctic Sea Ice Feature Extraction through High Spatial Resolution Aerial photos

    NASA Astrophysics Data System (ADS)

    Miao, X.; Xie, H.

    2015-12-01

    High resolution aerial photographs used to detect and classify sea ice features can provide accurate physical parameters to refine, validate, and improve climate models. However, manually delineating sea ice features, such as melt ponds, submerged ice, water, ice/snow, and pressure ridges, is time-consuming and labor-intensive. An object-based classification algorithm is developed to automatically extract sea ice features efficiently from aerial photographs taken during the Chinese National Arctic Research Expedition in summer 2010 (CHINARE 2010) in the MIZ near the Alaska coast. The algorithm includes four steps: (1) the image segmentation groups the neighboring pixels into objects based on the similarity of spectral and textural information; (2) the random forest classifier distinguishes four general classes: water, general submerged ice (GSI, including melt ponds and submerged ice), shadow, and ice/snow; (3) the polygon neighbor analysis separates melt ponds and submerged ice based on spatial relationship; and (4) pressure ridge features are extracted from shadow based on local illumination geometry. The producer's accuracy of 90.8% and user's accuracy of 91.8% are achieved for melt pond detection, and shadow shows a user's accuracy of 88.9% and producer's accuracies of 91.4%. Finally, pond density, pond fraction, ice floes, mean ice concentration, average ridge height, ridge profile, and ridge frequency are extracted from batch processing of aerial photos, and their uncertainties are estimated.

  20. 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.

  1. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. Rule-Based Interpreting Of Aerial Photographs Using The Lockheed Expert System

    NASA Astrophysics Data System (ADS)

    Perkins, W. A.; Faffey, T. J.; Nguyen, T. A.

    1986-03-01

    Human photointerpreters use expert knowledge and contextual information to help them analyze a scene. We have experimented with the Lockheed Expert System (LES) to see if contextual information can be useful in interpreting aerial photographs. First, the gray-scale image is segmented into uniform or slowly varying intensity regions or contiguous textured regions using an edge-based segmentation technique. Next, the system computes a set of attributes for each region. Some of these attributes are based on local properties of that region only (e.g., area, average intensity, texture strength, etc.); others are based on contextual or global information (e.g., adjacent regions and nearby regions). Finally, LES is given the task of classifying all the regions using the attribute values. It utilizes multiple goals and multiple rule sets to determine the best classification; regions that do not satisfy any of the rules are left unclassified. The authors obtained the rules by an introspection technique after studying many aerial photographs. Unlike programs that use only statistics in the region under consideration, LES can use contextual information such as the fact that cars are likely to be adjacent to roads, which significantly improves its performance on regions that are difficult to classify.

  1. 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.

  2. 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.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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 ...

  12. 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.

  13. 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.

  14. 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

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

    NASA Astrophysics Data System (ADS)

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

    1999-12-01

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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Runway detection of an unmanned landing aerial vehicle based on vision

    NASA Astrophysics Data System (ADS)

    Wang, Hongqun; Peng, Jiaxiong; Li, Lingling

    2005-10-01

    When an monocular vision-based unmanned aerial vehicle (UAV) based on vision is flown to the final approach fix to intercept the glide slope without the navigation of Global Positioning System (GPS), the position and orientation of the airport runway in image must be detected accurately so as to a host of suitable procedures have to be followed. The optimum length of the final approach is about five miles from the runway threshold. The front view of the runway, which is achieved at the moment, is very illegible. The approaching marking (cross bar) of the runway are showed as some white spots of high intensity and the complicated backgrounds of the airport are included in the images. In this case, spots with high intensity should be extracted and classified, some of these spots are just the images of the background noises and the pseudo-targets, which can't be separated with the spots of the runway as in the view there is no significant characteristic difference among them ostensibly. Fortunately, in the terrestrial coordinate space, most of the runway marks are located at the apexes of a rectangle, having some geometric relationships. The relationship among the projection coordinates of the runway spots in the images can be determined according to the perspective principle, the constraint condition of the rectangle as well as the front shot constraint condition of the target, by using this relationship, the runway approaching marks can be separated, the position and the direction of the runway in the images can be identified. In this paper, the clustering management is adopted so as to greatly reduce the computing time. The consequence of the experiments shows that by this algorithm, even from a place far away from the runway whose marks are unclear, we also can effectively detect the runway.

  2. 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

  3. 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

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

    PubMed

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

    2015-01-01

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

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Osumi, Ayumu; Ito, Youichi

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

  7. 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.

  8. Vision-based fast navigation of micro aerial vehicles

    NASA Astrophysics Data System (ADS)

    Loianno, Giuseppe; Kumar, Vijay

    2016-05-01

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

  9. 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.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  12. Aerial Photography

    NASA Technical Reports Server (NTRS)

    1985-01-01

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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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).

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    Erfanifard, Yousef; Stereńczak, Krzysztof; Behnia, Negin

    2014-01-01

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

  3. 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

  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. 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...

  6. 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.

  7. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  9. 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.

  10. 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...

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    Sheng, Yongwei

    2004-04-01

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

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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.

  1. Aerial photographic reproductions

    USGS Publications Warehouse

    ,

    1975-01-01

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

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

    PubMed

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

    2003-07-20

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

  3. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  5. 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.

  6. 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.

  7. 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.

  8. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

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

    PubMed

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

    2015-01-01

    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

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

    PubMed

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

    2015-12-12

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

  17. 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

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

    NASA Astrophysics Data System (ADS)

    Rango, Albert; Laliberte, Andrea; Herrick, Jeffrey E.; Winters, Craig; Havstad, Kris; Steele, Caiti; Browning, Dawn

    2009-08-01

    Rangeland comprises as much as 70% of the Earth's land surface area. Much of this vast space is in very remote areas that are expensive and often impossible to access on the ground. Unmanned Aerial Vehicles (UAVs) have great potential for rangeland management. UAVs have several advantages over satellites and piloted aircraft: they can be deployed quickly and repeatedly; they are less costly and safer than piloted aircraft; they are flexible in terms of flying height and timing of missions; and they can obtain imagery at sub-decimeter resolution. This hyperspatial imagery allows for quantification of plant cover, composition, and structure at multiple spatial scales. Our experiments have shown that this capability, from an off-the-shelf mini-UAV, is directly applicable to operational agency needs for measuring and monitoring. For use by operational agencies to carry out their mandated responsibilities, various requirements must be met: an affordable and reliable platform; a capability for autonomous, low altitude flights; takeoff and landing in small areas surrounded by rugged terrain; and an easily applied data analysis methodology. A number of image processing and orthorectification challenges have been or are currently being addressed, but the potential to depict the land surface commensurate with field data perspectives across broader spatial extents is unrivaled.

  19. 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.

  20. 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...

  1. 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…

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  4. 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

  5. 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.

  6. 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

  7. 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.

  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. A Texture Thesaurus for Browsing Large Aerial Photographs.

    ERIC Educational Resources Information Center

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

    1998-01-01

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

  11. Vision based control of unmanned aerial vehicles with applications to an autonomous four-rotor helicopter, quadrotor

    NASA Astrophysics Data System (ADS)

    Altug, Erdinc

    Our work proposes a vision-based stabilization and output tracking control method for a model helicopter. This is a part of our effort to produce a rotorcraft based autonomous Unmanned Aerial Vehicle (UAV). Due to the desired maneuvering ability, a four-rotor helicopter has been chosen as the testbed. On previous research on flying vehicles, vision is usually used as a secondary sensor. Unlike previous research, our goal is to use visual feedback as the main sensor, which is not only responsible for detecting where the ground objects are but also for helicopter localization. A novel two-camera method has been introduced for estimating the full six degrees of freedom (DOF) pose of the helicopter. This two-camera system consists of a pan-tilt ground camera and an onboard camera. The pose estimation algorithm is compared through simulation to other methods, such as four-point, and stereo method and is shown to be less sensitive to feature detection errors. Helicopters are highly unstable flying vehicles; although this is good for agility, it makes the control harder. To build an autonomous helicopter, two methods of control are studied---one using a series of mode-based, feedback linearizing controllers and the other using a back-stepping control law. Various simulations with 2D and 3D models demonstrate the implementation of these controllers. We also show global convergence of the 3D quadrotor controller even with large calibration errors or presence of large errors on the image plane. Finally, we present initial flight experiments where the proposed pose estimation algorithm and non-linear control techniques have been implemented on a remote-controlled helicopter. The helicopter was restricted with a tether to vertical, yaw motions and limited x and y translations.

  12. 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.

  13. 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.

  14. Optical image encryption based on diffractive imaging.

    PubMed

    Chen, Wen; Chen, Xudong; Sheppard, Colin J R

    2010-11-15

    In this Letter, we propose a method for optical image encryption based on diffractive imaging. An optical multiple random phase mask encoding system is applied, and one of the phase-only masks is selected and laterally translated along a preset direction during the encryption process. For image decryption, a phase retrieval algorithm is proposed to extract a high-quality plaintext. The feasibility and effectiveness of the proposed method are demonstrated by numerical results. The proposed method can provide a new strategy instead of conventional interference methods, and it may open up a new research perspective for optical image encryption.

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

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  16. 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.

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

    SciTech Connect

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

    1995-05-01

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

  18. 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.

  19. 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.

  20. 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

  1. Image based performance analysis of thermal imagers

    NASA Astrophysics Data System (ADS)

    Wegner, D.; Repasi, E.

    2016-05-01

    Due to advances in technology, modern thermal imagers resemble sophisticated image processing systems in functionality. Advanced signal and image processing tools enclosed into the camera body extend the basic image capturing capability of thermal cameras. This happens in order to enhance the display presentation of the captured scene or specific scene details. Usually, the implemented methods are proprietary company expertise, distributed without extensive documentation. This makes the comparison of thermal imagers especially from different companies a difficult task (or at least a very time consuming/expensive task - e.g. requiring the execution of a field trial and/or an observer trial). For example, a thermal camera equipped with turbulence mitigation capability stands for such a closed system. The Fraunhofer IOSB has started to build up a system for testing thermal imagers by image based methods in the lab environment. This will extend our capability of measuring the classical IR-system parameters (e.g. MTF, MTDP, etc.) in the lab. The system is set up around the IR- scene projector, which is necessary for the thermal display (projection) of an image sequence for the IR-camera under test. The same set of thermal test sequences might be presented to every unit under test. For turbulence mitigation tests, this could be e.g. the same turbulence sequence. During system tests, gradual variation of input parameters (e. g. thermal contrast) can be applied. First ideas of test scenes selection and how to assembly an imaging suite (a set of image sequences) for the analysis of imaging thermal systems containing such black boxes in the image forming path is discussed.

  2. 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.

  3. 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...

  4. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. 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.

  7. 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

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

    NASA Astrophysics Data System (ADS)

    Chen, Qi; Wang, Shugen; Liu, Xiuguo

    2016-06-01

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

  9. 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

  10. Sensor Fusion Based Fault-Tolerant Attitude Estimation Solutions for Small Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Gross, Jason Nicholas

    Navigation-grade inertial sensors are often too expensive and too heavy for use in most Small Unmanned Aerial Vehicle (SUAV) systems. Low-cost Micro-Electrical-Mechanical-Systems (MEMS) inertial sensors provide an attractive alternative, but currently do not provide an adequate navigation solution alone due to the presence of sensor bias. Toward addressing this problem, this research focuses on the development and experimental evaluation of sensor fusion algorithms to combine partially redundant information from low-cost sensor to achieve accurate SUAV attitude estimation. To conduct this research, several sets of SUAVs flight data that include measurements from a low-cost MEMS based Inertial Measurement Unit, a Global Positioning System receiver, and a set of low-grade tri-axial magnetometers are used to evaluate a variety of algorithms. In order to provide a baseline for performance evaluation, attitude measurements obtained directly with a high-quality mechanical vertical gyroscope are used as an independent attitude 'truth'. In addition, as a part of this project, a custom SUAV avionics system was developed to provide a platform for fault-tolerant flight control research. The overall goal of this research is to provide high-accuracy attitude estimation during nominal sensor performance conditions and in the event of sensors failures, while using only low-cost components. To achieve this goal, this study is carried out in three phases. The specific aim of the first phase is to obtain high-accuracy under nominal sensor conditions. During this phase, two different nonlinear Kalman filtering methods are applied to various sensor fusion formulations and evaluated with respect to estimation accuracy over diverse sets of flight data. Next, during the second phase, sensor fusion based calibration techniques are explored to further enhance estimation accuracy. Finally, the third phase of the study considers the design of a sensor fusion attitude estimation architecture

  11. 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

  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. 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.

  15. 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).

  16. 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 ...

  17. 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.

  18. D Surface Generation from Aerial Thermal Imagery

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  19. 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

  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. Vehicle detection in aerial surveillance using dynamic Bayesian networks.

    PubMed

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

    2012-04-01

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

  2. 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.

  3. Object-Based Change Detection Using Georeferenced Uav Images

    NASA Astrophysics Data System (ADS)

    Shi, J.; Wang, J.; Xu, Y.

    2011-09-01

    Unmanned aerial vehicles (UAV) have been widely used to capture and down-link real-time videos/images. However, their role as a low-cost airborne platform for capturing high-resolution, geo-referenced still imagery has not been fully utilized. The images obtained from UAV are advantageous over remote sensing images as they can be obtained at a low cost and potentially no risk to human life. However, these images are distorted due to the noise generated by the rotary wings which limits the usefulness of such images. One potential application of such images is to detect changes between the images of the same area which are collected over time. Change detection is of widespread interest due to a large number of applications, including surveillance and civil infrastructure. Although UAVs can provide images with high resolution in a portable and easy way, such images only cover small parts of the entire field of interest and are often with high deformation. Until now, there is not much application of change detection for UAV images. Also the traditional pixel-based change detection method does not give satisfactory results for such images. In this paper, we have proposed a novel object-based method for change detection using UAV images which can overcome the effect of deformation and can fully utilize the high resolution capability of UAV images. The developed method can be divided into five main blocks: pre-processing, image matching, image segmentation and feature extraction, change detection and accuracy evaluation. The pre-processing step is further divided into two sub-steps: the first sub-step is to geometrically correct the bi-temporal image based on the geo-reference information (GPS/INS) installed on the UAV system, and the second sub-step is the radiometric normalization using a histogram method. The image matching block uses the well-known scale-invariant feature transform (SIFT) algorithm to match the same areas in the images and then resample them. The

  4. 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.

  5. 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.

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  8. 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.

  9. 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.

  10. 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).

  11. Radiation Exchanges at the Atmosphere-Vegetation Canopy Boundary Layer Based on Unmanned Aerial Vehicle Observations

    NASA Astrophysics Data System (ADS)

    Dim, J. R.; Kajiwara, K.; Honda, Y.

    2007-12-01

    Radiation exchanges at the vegetation boundary layer, regulating the amount of energy received by the vegetation canopy are examined through remote sensing observations carried out by an unmanned helicopter, flying according to pre-programmed plans, above a forested area. Information obtained from the laser scanning system, radiometric measurements and aerial photographs are combined to ambient meteorological parameters in order to examine interactions between leaf characteristics, elements of vegetation structure, and the surrounding atmosphere. A vegetation mass transfer model showing variable dependencies of leaf water content, leaf temperature, leaf-air vapor-pressure differences and solar radiation intensity as well as canopy structure is used to discuss transpiration mechanisms of the studied forest.

  12. Image-based occupancy sensor

    DOEpatents

    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.

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

    PubMed

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

    2015-09-18

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

  14. 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

  15. 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).

  16. 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

  17. 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)

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

    PubMed

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

    2015-03-19

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

  20. 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

  1. 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

  2. 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

  3. 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.

  4. Age determination by back length for African savanna elephants: extending age assessment techniques for aerial-based surveys.

    PubMed

    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.

  5. 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

  6. 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)

  7. 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.

  8. 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.

  9. 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.

  10. 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

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

    PubMed

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

    2016-05-10

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

  12. 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

  13. 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.

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

    PubMed

    Zhu, B; Ramsey, M; Chen, H

    2000-01-01

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

  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.

  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. 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.

  1. Embedded Controller based Image Stabilizer

    NASA Astrophysics Data System (ADS)

    Teare, S. W.; Lamppa, D.; Sugimoto, K.; Yates, J.; Xiao, H.; Thompson, L. A.

    2004-05-01

    An image stabilization system is commonly used on astronomical telescopes to compensate for poor mount performance, low-order effects from atmospheric seeing and local index of refraction instabilities near the telescope. An image stabilizer is comprised of an electro-optical component and a sensor that are used in concert to lock the position of a wavefront or image centroid onto a camera. There are several commercial tip-tilt and sensing systems and components that can be used for image stabilization depending on the user's performance and cost requirements. We report on an inexpensive image stabilizer for use on astronomical telescopes developed as part of the NSF funded (AST-00-96741) UnISIS laser guide-star project at the Mount Wilson Observatory. The instrument uses inexpensive, commercial-off-the-shelf (COTS) components for beam steering, position sensing and the processor/control system. The limiting magnitude of the system depends on the properties of the light sensor used. The image stabilizer operates as a turnkey system with 2 main control modes to provide different performance capabilities for different operating conditions. The normal mode uses a proportional, integrating, differentiating (PID) controller and the second mode uses a more complex fuzzy logic based control scheme. We have examined other control methods and continue to experiment with different schemes. The simplicity of the system allows for many different control models to be implemented and evaluated in the laboratory and on the telescope. This flexibility and low cost provides an inexpensive system that can be used for both image stabilization and monitoring of the astronomical seeing at an observing site. Such systems are also invaluable for introducing astronomy students to instrumentation and engineering students to the innovative control aspects of telescope systems.

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-06-12

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

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

    PubMed

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

    2015-01-01

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

  11. 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-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.

  13. 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.

  14. 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%.

  15. Content-based vessel image retrieval

    NASA Astrophysics Data System (ADS)

    Mukherjee, Satabdi; Cohen, Samuel; Gertner, Izidor

    2016-05-01

    This paper describes an approach to vessel classification from satellite images using content based image retrieval methodology. Content-based image retrieval is an important problem in both medical imaging and surveillance applications. In many cases the archived reference database is not fully structured, thus making content-based image retrieval a challenging problem. In addition, in surveillance applications, the query image may be affected by weather or/and geometric distortions. Our approach of content-based vessel image retrieval consists of two phases. First, we create a structured reference database, then for each new query image of a vessel we find the closest cluster of images in the structured reference database, thus identifying and classifying the vessel. Then we update the closest cluster with new query image.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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).

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

    NASA Astrophysics Data System (ADS)

    Zhao, Yunji; Pei, Hailong

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

  4. 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.

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

    DOE PAGES

    Yuan, Jiangye; Cheriyadat, Anil M.

    2015-10-19

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

  6. 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.

  7. Concurrent aerial and ground-based optical turbulence measurements along a long elevated path

    NASA Astrophysics Data System (ADS)

    Nowlin, Scott R.; Hahn, Ila L.; Hugo, Ronald J.; Bishop, Kenneth P.

    1999-08-01

    We report concurrent ground-based scintillator/airborne constant-current anemometer (CCA) measurements made along a 51.4 km-long slant path between Salinas and North Oscura peaks, NM. Simultaneous path-averaged refractive index structure parameter (Cn2) measurements from the CCA and the scintillometer show good agreement, with deviations apparently due to localized effects of underlying topography and metrology. Statistics from both data sets are presented in the form of histograms and cumulative distribution functions. CCA Cn2 point measurements are compared to underlying surface topography. We discuss possible effects of instruments anomalies, analysis methods, and atmospheric velocity fluctuation levels. We present conclusions and made recommendations for future similar experimental efforts.

  8. 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

  9. 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

  10. Image-based Biomarkers in Clinical Practice

    PubMed Central

    Bayouth, John E.; Casavant, Thomas L.; Graham, Michael M.; Sonka, Milan; Muruganandham, Manickam; Buatti, John M.

    2014-01-01

    The growth of functional and metabolically informative imaging is eclipsing anatomic imaging alone, in clinical practice. The recognition that MR and PET-based treatment planning and response assessment are essential components of clinical practice and furthermore offer the potential of quantitative analysis is important. To extract the greatest benefit from these imaging techniques will require refining the best combinations of multimodality imaging through well designed clinical trials that employ robust image-analysis tools and require substantial computer based infrastructure. Through these changes and enhancements, image-based biomarkers will enhance clinical decision making and accelerate the progress that is made through clinical trial research. PMID:21356483

  11. 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.

  12. Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Wavelet based image visibility enhancement of IR images

    NASA Astrophysics Data System (ADS)

    Jiang, Qin; Owechko, Yuri; Blanton, Brendan

    2016-05-01

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

  19. 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.

  20. 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

  1. 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

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

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

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

  3. 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.

  4. 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.

  5. Looking for an old aerial photograph

    USGS Publications Warehouse

    ,

    1997-01-01

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

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  8. 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.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  11. 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.

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

    USGS Publications Warehouse

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

    1984-01-01

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

  13. 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.

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

    PubMed

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

    2015-01-13

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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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…

  1. 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

  2. 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.

  3. 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.

  4. Content Based Image Matching for Planetary Science

    NASA Astrophysics Data System (ADS)

    Deans, M. C.; Meyer, C.

    2006-12-01

    Planetary missions generate large volumes of data. With the MER rovers still functioning on Mars, PDS contains over 7200 released images from the Microscopic Imagers alone. These data products are only searchable by keys such as the Sol, spacecraft clock, or rover motion counter index, with little connection to the semantic content of the images. We have developed a method for matching images based on the visual textures in images. For every image in a database, a series of filters compute the image response to localized frequencies and orientations. Filter responses are turned into a low dimensional descriptor vector, generating a 37 dimensional fingerprint. For images such as the MER MI, this represents a compression ratio of 99.9965% (the fingerprint is approximately 0.0035% the size of the original image). At query time, fingerprints are quickly matched to find images with similar appearance. Image databases containing several thousand images are preprocessed offline in a matter of hours. Image matches from the database are found in a matter of seconds. We have demonstrated this image matching technique using three sources of data. The first database consists of 7200 images from the MER Microscopic Imager. The second database consists of 3500 images from the Narrow Angle Mars Orbital Camera (MOC-NA), which were cropped into 1024×1024 sub-images for consistency. The third database consists of 7500 scanned archival photos from the Apollo Metric Camera. Example query results from all three data sources are shown. We have also carried out user tests to evaluate matching performance by hand labeling results. User tests verify approximately 20% false positive rate for the top 14 results for MOC NA and MER MI data. This means typically 10 to 12 results out of 14 match the query image sufficiently. This represents a powerful search tool for databases of thousands of images where the a priori match probability for an image might be less than 1%. Qualitatively, correct

  5. 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.

  6. 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

  7. 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.

  8. 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

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

    NASA Astrophysics Data System (ADS)

    Rafiq, Talha

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Thermal light ghost imaging based on morphology

    NASA Astrophysics Data System (ADS)

    Chen, Zhipeng; Shi, Jianhong; Zeng, Guihua

    2016-12-01

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

  17. 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%.

  18. Light Field Imaging Based Accurate Image Specular Highlight Removal.

    PubMed

    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

  19. 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

  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. 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.

  2. Tensor scale-based image registration

    NASA Astrophysics Data System (ADS)

    Saha, Punam K.; Zhang, Hui; Udupa, Jayaram K.; Gee, James C.

    2003-05-01

    Tangible solutions to image registration are paramount in longitudinal as well as multi-modal medical imaging studies. In this paper, we introduce tensor scale - a recently developed local morphometric parameter - in rigid image registration. A tensor scale-based registration method incorporates local structure size, orientation and anisotropy into the matching criterion, and therefore, allows efficient multi-modal image registration and holds potential to overcome the effects of intensity inhomogeneity in MRI. Two classes of two-dimensional image registration methods are proposed - (1) that computes angular shift between two images by correlating their tensor scale orientation histogram, and (2) that registers two images by maximizing the similarity of tensor scale features. Results of applications of the proposed methods on proton density and T2-weighted MR brain images of (1) the same slice of the same subject, and (2) different slices of the same subject are presented. The basic superiority of tensor scale-based registration over intensity-based registration is that it may allow the use of local Gestalts formed by the intensity patterns over the image instead of simply considering intensities as isolated events at the pixel level. This would be helpful in dealing with the effects of intensity inhomogeneity and noise in MRI.

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

    NASA Astrophysics Data System (ADS)

    Leiva Lopez, Josue Nahun

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

  4. 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

  5. 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

  6. 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…

  7. 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

  8. 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

  9. Correlation-Based Image Reconstruction Methods for Magnetic Particle Imaging

    NASA Astrophysics Data System (ADS)

    Ishihara, Yasutoshi; Kuwabara, Tsuyoshi; Honma, Takumi; Nakagawa, Yohei

    Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function—defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction methods.

  10. 1. NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA ...

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

    1. NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA PATCH ISLAND. REMAINS OF SEA WALL VISIBLE IN FOREGROUND AND RIGHT OF IMAGE. - Fort Delaware, Sea Wall, Pea Patch Island, Delaware City, New Castle County, DE

  11. NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA PATCH ...

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

    NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA PATCH ISLAND. REMAINS OF SEA WALL VISIBLE IN FOREGROUND AND RIGHT OF IMAGE - Fort Delaware, Pea Patch Island, Delaware City, New Castle County, DE

  12. 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.

  13. 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.

  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. 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

  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.

  17. Image-based brachytherapy for cervical cancer.

    PubMed

    Vargo, John A; Beriwal, Sushil

    2014-12-10

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

  18. 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

  19. 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%).

  20. 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

  1. Aerial Photography Summary Record System

    USGS Publications Warehouse

    ,

    1998-01-01

    The Aerial Photography Summary Record System (APSRS) describes aerial photography projects that meet specified criteria over a given geographic area of the United States and its territories. Aerial photographs are an important tool in cartography and a number of other professions. Land use planners, real estate developers, lawyers, environmental specialists, and many other professionals rely on detailed and timely aerial photographs. Until 1975, there was no systematic approach to locate an aerial photograph, or series of photographs, quickly and easily. In that year, the U.S. Geological Survey (USGS) inaugurated the APSRS, which has become a standard reference for users of aerial photographs.

  2. GRAPHIE: graph based histology image explorer

    PubMed Central

    2015-01-01

    Background Histology images comprise one of the important sources of knowledge for phenotyping studies in systems biology. However, the annotation and analyses of histological data have remained a manual, subjective and relatively low-throughput process. Results We introduce Graph based Histology Image Explorer (GRAPHIE)-a visual analytics tool to explore, annotate and discover potential relationships in histology image collections within a biologically relevant context. The design of GRAPHIE is guided by domain experts' requirements and well-known InfoVis mantras. By representing each image with informative features and then subsequently visualizing the image collection with a graph, GRAPHIE allows users to effectively explore the image collection. The features were designed to capture localized morphological properties in the given tissue specimen. More importantly, users can perform feature selection in an interactive way to improve the visualization of the image collection and the overall annotation process. Finally, the annotation allows for a better prospective examination of datasets as demonstrated in the users study. Thus, our design of GRAPHIE allows for the users to navigate and explore large collections of histology image datasets. Conclusions We demonstrated the usefulness of our visual analytics approach through two case studies. Both of the cases showed efficient annotation and analysis of histology image collection. PMID:26330277

  3. Image colorization based on texture map

    NASA Astrophysics Data System (ADS)

    Liu, Shiguang; Zhang, Xiang

    2013-01-01

    Colorizing grayscale images so that the resulting image appears natural is a hard problem. Previous colorization algorithms generally use just the luminance information and ignore the rich texture information, which means that regions with the same luminance but different textures may mistakenly be assigned the same color. A novel automatic texture-map-based grayscale image colorization method is proposed. The texture map is generated with bilateral decomposition and a Gaussian high pass filter, which is further optimized using statistical adaptive gamma correction method. The segmentation of the spatial map is performed using locally weighted linear regression on its histogram in order to match the grayscale image and the source image. Within each of the spatial segmentation, a weighted color-luminance correspondence is achieved by the results of locally weighted linear regression. The luminance-color correspondence between the grayscale image and the source image can thus be used to colorize the grayscale image directly. By considering the consistency of both color information and texture information between two images, various plausible colorization results are generated using this new method.

  4. Magnetic Resonance Image Example Based Contrast Synthesis

    PubMed Central

    Roy, Snehashis; Carass, Aaron; Prince, Jerry L.

    2013-01-01

    The performance of image analysis algorithms applied to magnetic resonance images is strongly influenced by the pulse sequences used to acquire the images. Algorithms are typically optimized for a targeted tissue contrast obtained from a particular implementation of a pulse sequence on a specific scanner. There are many practical situations, including multi-institution trials, rapid emergency scans, and scientific use of historical data, where the images are not acquired according to an optimal protocol or the desired tissue contrast is entirely missing. This paper introduces an image restoration technique that recovers images with both the desired tissue contrast and a normalized intensity profile. This is done using patches in the acquired images and an atlas containing patches of the acquired and desired tissue contrasts. The method is an example-based approach relying on sparse reconstruction from image patches. Its performance in demonstrated using several examples, including image intensity normalization, missing tissue contrast recovery, automatic segmentation, and multimodal registration. These examples demonstrate potential practical uses and also illustrate limitations of our approach. PMID:24058022

  5. 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.

  6. [Accuracy of winter wheat identification based on multi-temporal CBERS-02 images].

    PubMed

    Qi, La; Zhao, Chun-Jiang; Li, Cun-Jun; Liu, Liang-Yun; Tan, Chang-Wei; Huang, Wen-Jiang

    2008-10-01

    Chinese-Brazil Earth Resources Satellite No. 2 (CBERS-02) has good spatial resolution and abundant spectral information, and a strong ability in detecting vegetation. Based on five CBERS-02 images in winter wheat growth season, the spectral distance between winter wheat and other ground targets was calculated, and then, winter wheat was classified from each individual image or their combinations by using supervised classification. The train and validation samples were derived from high resolution Aerial Images and SPOT5 images. The accuracies and analyses were evaluated for CBERS-02 images at early growth stages, and the results were compared to those of TM images acquired in the same phenological calendars. The results showed that temporal information was the main factor affecting the classification accuracy in winter wheat, but the characteristics of different sensors could affect the classification accuracy. The multi-temporal images could improve the classification accuracy, compared with the results derived from signal stage, with the producer accuracy of optimum periods combination improved 20.0% and user accuracy improved 7.83%. Compared with TM sensor, the classification accuracy from CBERS-02 was a little lower.

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

    NASA Astrophysics Data System (ADS)

    Wilburn, Brenton K.

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

  8. 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.

  9. 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.

  10. 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.

  11. Space-based optical image encryption.

    PubMed

    Chen, Wen; Chen, Xudong

    2010-12-20

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

  12. Corn tassel detection based on image processing

    NASA Astrophysics Data System (ADS)

    Tang, Wenbing; Zhang, Yane; Zhang, Dongxing; Yang, Wei; Li, Minzan

    2012-01-01

    Machine vision has been widely applied in facility agriculture, and played an important role in obtaining environment information. In this paper, it is studied that application of image processing to recognize and locate corn tassel for corn detasseling machine. The corn tassel identification and location method was studied based on image processing and automated technology guidance information was provided for the actual production of corn emasculation operation. The system is the application of image processing to recognize and locate corn tassel for corn detasseling machine. According to the color characteristic of corn tassel, image processing techniques was applied to identify corn tassel of the images under HSI color space and Image segmentation was applied to extract the part of corn tassel, the feature of corn tassel was analyzed and extracted. Firstly, a series of preprocessing procedures were done. Then, an image segmentation algorithm based on HSI color space was develop to extract corn tassel from background and region growing method was proposed to recognize the corn tassel. The results show that this method could be effective for extracting corn tassel parts from the collected picture and can be used for corn tassel location information; this result could provide theoretical basis guidance for corn intelligent detasseling machine.

  13. 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.

  14. 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

  15. 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.

  16. 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'.

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

    NASA Astrophysics Data System (ADS)

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

    1998-12-01

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

  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. 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.

  20. 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.

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2003-06-01

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

  3. 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

  4. Multi-Scale Validation of Forest Insect Mortality Using QuickBird and Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Meddens, A. J.; Hicke, J. A.; Vierling, L. A.

    2008-12-01

    Insects are major disturbances in forested ecosystems, affecting forest succession, carbon cycling, and fuel loads. Insect-caused tree mortality causes significant change in forest structure as dead trees lose their needles and eventually fall to the ground. To manage forests and establish natural resource policy, accurate estimates of the extent of insect disturbance are needed. Mountain pine beetles (Dendroctonus ponderosae Hopkins), one of the most damaging insect species, have affected large forested areas in the United States and Canada. Our goal is to map landscape-level tree mortality caused by insect outbreaks across the western United States using satellite remote sensing. Here we report on the methods we are developing and applying to an outbreak of mountain pine beetle in Colorado as well as the means of evaluating the classification using field measurements and finer spatial resolution aerial imagery. In August 2008, 36 forest inventory plots were established in an area affected by mountain pine beetle in the Arapaho National Forest in the Rocky Mountains of Colorado, USA. A digital aerial multispectral image with a spatial resolution of 30 cm and a QuickBird image with a spatial resolution of 2.4 m were acquired in the same area. We are employing a nested validation approach using the aerial imagery and QuickBird imagery to ultimately validate a Landsat-based insect disturbance detection product. Tree-level field measurements are used to evaluate classified the aerial imagery. The classified aerial imagery is subsequently used to evaluate classified QuickBird imagery, which in turn is used to evaluate the Landsat product. The outcomes of finer spatial level classification can be used to increase understanding of the coarser spatial image classification and provide means to investigate disturbance level thresholds for the detection of insect outbreaks using the coarser resolution imagery.

  5. 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

  6. 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.

  7. 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.

  8. 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…

  9. 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.

  10. 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.

  11. 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.

  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. Image-based systems biology of infection.

    PubMed

    Medyukhina, Anna; Timme, Sandra; Mokhtari, Zeinab; Figge, Marc Thilo

    2015-06-01

    The successful treatment of infectious diseases requires interdisciplinary studies of all aspects of infection processes. The overarching combination of experimental research and theoretical analysis in a systems biology approach can unravel mechanisms of complex interactions between pathogens and the human immune system. Taking into account spatial information is especially important in the context of infection, since the migratory behavior and spatial interactions of cells are often decisive for the outcome of the immune response. Spatial information is provided by image and video data that are acquired in microscopy experiments and that are at the heart of an image-based systems biology approach. This review demonstrates how image-based systems biology improves our understanding of infection processes. We discuss the three main steps of this approach--imaging, quantitative characterization, and modeling--and consider the application of these steps in the context of studying infection processes. After summarizing the most relevant microscopy and image analysis approaches, we discuss ways to quantify infection processes, and address a number of modeling techniques that exploit image-derived data to simulate host-pathogen interactions in silico.

  16. 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

  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. Content based retrieval of lesioned brain images

    NASA Astrophysics Data System (ADS)

    Batty, Stephen; Blandford, Ann; Clark, John; Fryer, Tim; Gao, Xiaohong

    2002-05-01

    HI-PACS enable more efficient data-management leading to increased operating efficiency and therefore better patient care, a content based pet image retrieval system would contribute to the development of a HI-PACS. A database of PET neuro-images has been created with a facility for retrieving via visual content. The adaptation of algorithms developed for alternate imaging modalities (eg-MRI) formed the basis of feature detection and measurement algorithms. The application of these algorithms to greyscale PET images results in data that is employed as database indices and similarity metrics. The feature detection and measurement algorithms can be split into two different methods. The first uses the extracted ideal mid sagittal symmetry line to detect differences between the two hemisphere of the brain, while the second utilizes Gabor filters to measure the texture of the whole brain.

  19. 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.

  20. 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

  1. 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)

  2. 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.

  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. Image based physiological monitoring of cardiac function

    NASA Astrophysics Data System (ADS)

    Maier, Corinna S.; Bock, Michael; Semmler, Wolfhard; Lorenz, Christine H.

    2008-03-01

    A new framework for image based physiological cardiac monitoring is proposed based on repeated imaging of critical slice locations in an interventional MRI environment. The aim of this work is to provide a method of detecting pathological changes in the left ventricular (LV) myocardial wall motion where the standard ECG methods are not possible due to distortions by the magnetic field. First MRI LV short axis images are acquired for different phases of the cardiac cycle over RR intervals. Then LV contours are detected based on an established segmentation algorithm. The contour's Fourier Descriptors are calculated to classify myocardial wall into two classes: contracted or not contracted. The classifier is trained during an initial observation period before a pathological change might occur during an intervention. A contour rejected by the classifier using the unconditional, predictive probability of the contour's observation vector as confidence measure is interpreted as a probably pathologic change in the LV myocardial wall motion. To evaluate the performance of the classifier a simple model is introduced for simulating the contours of a pathological, ischemic, LV myocardial wall. The overall performance of the classifier on 516 samples based on healthy volunteer images and 3096 simulated ischemic samples yielded a mean classification error for supervised training of 5.7% and for unsupervised training of 8.7%.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  7. Image-based panoramic virtual reality system

    NASA Astrophysics Data System (ADS)

    Ritchey, Kurtis J.

    1992-06-01

    An extensive family of advanced virtual reality-telepresence systems and components have been developed. The purpose of these systems and components is to facilitate recording, processing, display, and interaction with audio and video signal(s) representing a scene or subject of three-dimensions (3-D). An overview of the systems currently available for license includes: a color video camera with real-time simultaneous spherical FOV coverage; a similar camera for recording various sides of a 3-D subject; an image based system for real-time processing and distribution of said camera based images onto 3-D wireframes; resultant camcorders are generally referred to as virtual reality/telepresence 'VRT camcorders'TM; a 'VIDEOROOM'TM large theater display system in which the floor, walls, and ceiling form a continuous display about the viewer for display of said images; 'INaVISION'TM a HMD system for viewing the same said images; and interactive control devices for manipulating said 3-D image and audio signal(s). Applications, to include visual and auditory simulation, host vehicle control, remote vehicle control, video teleconferencing, and so on, are feasible applications for the above technology. Rough costs of systems and components, photographs of a prototype system, and component illustrations are provided. Future directions of R&D are presented (i.e., Project HEAVEN: Humankind Eternal-Life Artificial-Intelligence Virtual Environment Network).

  8. 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.

  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. 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).

  11. Shutter/aperture settings for aerial photography

    NASA Technical Reports Server (NTRS)

    Lockwood, H. E.; Perry, L.

    1976-01-01

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

  12. Metrically preserving the USGS aerial film archive

    USGS Publications Warehouse

    Moe, Donald; Longhenry, Ryan

    2013-01-01

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

  13. Laser Doppler velocimeter aerial spray measurements

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  14. Velocity measurements and changes in position of Thwaites Glacier/iceberg tongue from aerial photography, Landsat images and NOAA AVHRR data

    USGS Publications Warehouse

    Ferrigno, Jane G.; Lucchitta, Baerbel K.; Mullinsallison, A. L.; Allen, Robert J.; Gould, W. G.

    1993-01-01

    The Thwaites Glacier/iceberg tongue complex has been a significant feature of the Antarctic coastline for at least 50 years. In 1986, major changes began to occur in this area. Fast ice melted and several icebergs calved from the base of the iceberg tongue and the terminus of Thwaites Glacier. The iceberg tongue rotated to an east-west orientation and drifted westward. Between 1986 and 1992, a total of 140 km of drift has occurred. Remote digital velocity measurements were made on Thwaites Glacier using sequential Landsat images to try to determine if changes in velocity had occurred in conjunction with the changes in ice position. Examination of the morphology of the glacier/iceberg tongue showed no evidence of surge activity.

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

    SciTech Connect

    Heuze, F.E.

    1997-07-01

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

  16. 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.

  17. 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.

  18. A statistically based flow for image segmentation.

    PubMed

    Pichon, Eric; Tannenbaum, Allen; Kikinis, Ron

    2004-09-01

    In this paper we present a new algorithm for 3D medical image segmentation. The algorithm is versatile, fast, relatively simple to implement, and semi-automatic. It is based on minimizing a global energy defined from a learned non-parametric estimation of the statistics of the region to be segmented. Implementation details are discussed and source code is freely available as part of the 3D Slicer project. In addition, a new unified set of validation metrics is proposed. Results on artificial and real MRI images show that the algorithm performs well on large brain structures both in terms of accuracy and robustness to noise. PMID:15450221

  19. 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.

  20. 77 FR 35962 - Utilizing Rapidly Deployable Aerial Communications Architecture in Response to an Emergency

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-15

    ... deployment of any special user devices include unmanned aerial vehicles, weather balloons, and suitcase based...- effectiveness of unmanned aerial vehicles, weather balloons, and high altitude platforms. How does the cost... COMMISSION Utilizing Rapidly Deployable Aerial Communications Architecture in Response to an Emergency...

  1. 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...

  2. 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

  3. Diffusion-based spatial priors for imaging

    PubMed Central

    Harrison, L.M.; Penny, W.; Ashburner, J.; Trujillo-Barreto, N.; Friston, K.J.

    2007-01-01

    We describe a Bayesian scheme to analyze images, which uses spatial priors encoded by a diffusion kernel, based on a weighted graph Laplacian. This provides a general framework to formulate a spatial model, whose parameters can be optimized. The application we have in mind is a spatiotemporal model for imaging data. We illustrate the method on a random effects analysis of fMRI contrast images from multiple subjects; this simplifies exposition of the model and enables a clear description of its salient features. Typically, imaging data are smoothed using a fixed Gaussian kernel as a pre-processing step before applying a mass-univariate statistical model (e.g., a general linear model) to provide images of parameter estimates. An alternative is to include smoothness in a multivariate statistical model (Penny, W.D., Trujillo-Barreto, N.J., Friston, K.J., 2005. Bayesian fMRI time series analysis with spatial priors. Neuroimage 24, 350–362). The advantage of the latter is that each parameter field is smoothed automatically, according to a measure of uncertainty, given the data. In this work, we investigate the use of diffusion kernels to encode spatial correlations among parameter estimates. Nonlinear diffusion has a long history in image processing; in particular, flows that depend on local image geometry (Romeny, B.M.T., 1994. Geometry-driven Diffusion in Computer Vision. Kluwer Academic Publishers) can be used as adaptive filters. This can furnish a non-stationary smoothing process that preserves features, which would otherwise be lost with a fixed Gaussian kernel. We describe a Bayesian framework that incorporates non-stationary, adaptive smoothing into a generative model to extract spatial features in parameter estimates. Critically, this means adaptive smoothing becomes an integral part of estimation and inference. We illustrate the method using synthetic and real fMRI data. PMID:17869542

  4. Web-based document image processing

    NASA Astrophysics Data System (ADS)

    Walker, Frank L.; Thoma, George R.

    1999-12-01

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

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

    ERIC Educational Resources Information Center

    Zachary, John; Iyengar, S. S.

    2001-01-01

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

  6. MEMS FPI-based smartphone hyperspectral imager

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  7. Image-based spectroscopy for environmental monitoring

    NASA Astrophysics Data System (ADS)

    Bachmakov, Eduard; Molina, Carolyn; Wynne, Rosalind

    2014-03-01

    An image-processing algorithm for use with a nano-featured spectrometer chemical agent detection configuration is presented. The spectrometer chip acquired from Nano-Optic DevicesTM can reduce the size of the spectrometer down to a coin. The nanospectrometer chip was aligned with a 635nm laser source, objective lenses, and a CCD camera. The images from a nanospectrometer chip were collected and compared to reference spectra. Random background noise contributions were isolated and removed from the diffraction pattern image analysis via a threshold filter. Results are provided for the image-based detection of the diffraction pattern produced by the nanospectrometer. The featured PCF spectrometer has the potential to measure optical absorption spectra in order to detect trace amounts of contaminants. MATLAB tools allow for implementation of intelligent, automatic detection of the relevant sub-patterns in the diffraction patterns and subsequent extraction of the parameters using region-detection algorithms such as the generalized Hough transform, which detects specific shapes within the image. This transform is a method for detecting curves by exploiting the duality between points on a curve and parameters of that curve. By employing this imageprocessing technique, future sensor systems will benefit from new applications such as unsupervised environmental monitoring of air or water quality.

  8. Photogrammetric mapping using unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Graça, N.; Mitishita, E.; Gonçalves, J.

    2014-11-01

    Nowadays Unmanned Aerial Vehicle (UAV) technology has attracted attention for aerial photogrammetric mapping. The low cost and the feasibility to automatic flight along commanded waypoints can be considered as the main advantages of this technology in photogrammetric applications. Using GNSS/INS technologies the images are taken at the planned position of the exposure station and the exterior orientation parameters (position Xo, Yo, Zo and attitude ω, φ, χ) of images can be direct determined. However, common UAVs (off-the-shelf) do not replace the traditional aircraft platform. Overall, the main shortcomings are related to: difficulties to obtain the authorization to perform the flight in urban and rural areas, platform stability, safety flight, stability of the image block configuration, high number of the images and inaccuracies of the direct determination of the exterior orientation parameters of the images. In this paper are shown the obtained results from the project photogrammetric mapping using aerial images from the SIMEPAR UAV system. The PIPER J3 UAV Hydro aircraft was used. It has a micro pilot MP2128g. The system is fully integrated with 3-axis gyros/accelerometers, GPS, pressure altimeter, pressure airspeed sensors. A Sony Cyber-shot DSC-W300 was calibrated and used to get the image block. The flight height was close to 400 m, resulting GSD near to 0.10 m. The state of the art of the used technology, methodologies and the obtained results are shown and discussed. Finally advantages/shortcomings found in the study and main conclusions are presented

  9. The application of GPS precise point positioning technology in aerial triangulation

    NASA Astrophysics Data System (ADS)

    Yuan, Xiuxiao; Fu, Jianhong; Sun, Hongxing; Toth, Charles

    In traditional GPS-supported aerotriangulation, differential GPS (DGPS) positioning technology is used to determine the 3-dimensional coordinates of the perspective centers at exposure time with an accuracy of centimeter to decimeter level. This method can significantly reduce the number of ground control points (GCPs). However, the establishment of GPS reference stations for DGPS positioning is not only labor-intensive and costly, but also increases the implementation difficulty of aerial photography. This paper proposes aerial triangulation supported with GPS precise point positioning (PPP) as a way to avoid the use of the GPS reference stations and simplify the work of aerial photography. Firstly, we present the algorithm for GPS PPP in aerial triangulation applications. Secondly, the error law of the coordinate of perspective centers determined using GPS PPP is analyzed. Thirdly, based on GPS PPP and aerial triangulation software self-developed by the authors, four sets of actual aerial images taken from surveying and mapping projects, different in both terrain and photographic scale, are given as experimental models. The four sets of actual data were taken over a flat region at a scale of 1:2500, a mountainous region at a scale of 1:3000, a high mountainous region at a scale of 1:32000 and an upland region at a scale of 1:60000 respectively. In these experiments, the GPS PPP results were compared with results obtained through DGPS positioning and traditional bundle block adjustment. In this way, the empirical positioning accuracy of GPS PPP in aerial triangulation can be estimated. Finally, the results of bundle block adjustment with airborne GPS controls from GPS PPP are analyzed in detail. The empirical results show that GPS PPP applied in aerial triangulation has a systematic error of half-meter level and a stochastic error within a few decimeters. However, if a suitable adjustment solution is adopted, the systematic error can be eliminated in GPS

  10. Integrated paleontological data base and image library

    SciTech Connect

    Goodman, D.K. ); Becker, R.C. ); Van Couvering, J. ); Ford, L.N. Jr. ); Albert, N.R. )

    1991-03-01

    MICROBASE (MICROpaleontology data BASE) is an integrated data base and image retrieval system designed to increase the efficiency and precision with which paleontologists access and interpret paleontological and biostratigraphic data. The project is funded by a consortium of oil companies and coordinated by the American Museum of Natural History with assistance from the American Association of Stratigraphic Palynologists. MICROBASE is a PC-based MS DOS-compatible system operating under Microsoft Windows 3.0 that takes advantage of the latest developments in both analog (video) and digital technology. Images are captured using a video camera mounted on a microscope or using a high-resolution scanner for photographic source material. The image is saved either as a digital file or as an analog 'frame' on a Panasonic optical disk recorder (OMDR). The OMDR can store 108,000 images on one 12-in disk with a retrieval and display time of less than 0.15 second. Microfossil data (nomenclature, synonomy, descriptions, stratigraphic distribution, etc.) are stored as relational tables in an ORACLE DBMS (PALeontological CATalog, or PALCAT), and these textural data are linked to multiple images for each taxon. MICROBASE is the first integrated and widely supported system to electronically archive paleontological data, regardless of fossil group. It provides rapid, easy access to paleontological data, resulting in standardized taxonomy, more efficient identification procedures, substantially reduced learning curves for persons unfamiliar with particular groups, and more effective retention of the cumulative expertise of experienced paleontologists. The Ellis and Messina Catalog of Foraminifera is the first paleontological catalog available on the MICROBASE system.

  11. Imaging of skull base: Pictorial essay

    PubMed Central

    Raut, Abhijit A; Naphade, Prashant S; Chawla, Ashish

    2012-01-01

    The skull base anatomy is complex. Numerous vital neurovascular structures pass through multiple channels and foramina located in the base skull. With the advent of computerized tomography (CT) and magnetic resonance imaging (MRI), accurate preoperative lesion localization and evaluation of its relationship with adjacent neurovascular structures is possible. It is imperative that the radiologist and skull base surgeons are familiar with this complex anatomy for localizing the skull base lesion, reaching appropriate differential diagnosis, and deciding the optimal surgical approach. CT and MRI are complementary to each other and are often used together for the demonstration of the full disease extent. This article focuses on the radiological anatomy of the skull base and discusses few of the common pathologies affecting the skull base. PMID:23833423

  12. Somatostatin Receptor Based Imaging and Radionuclide Therapy

    PubMed Central

    Zhang, Hong

    2015-01-01

    Somatostatin (SST) receptors (SSTRs) belong to the typical 7-transmembrane domain family of G-protein-coupled receptors. Five distinct subtypes (termed SSTR1-5) have been identified, with SSTR2 showing the highest affinity for natural SST and synthetic SST analogs. Most neuroendocrine tumors (NETs) have high expression levels of SSTRs, which opens the possibility for tumor imaging and therapy with radiolabeled SST analogs. A number of tracers have been developed for the diagnosis, staging, and treatment of NETs with impressive results, which facilitates the applications of human SSTR subtype 2 (hSSTr2) reporter gene based imaging and therapy in SSTR negative or weakly positive tumors to provide a novel approach for the management of tumors. The hSSTr2 gene can act as not only a reporter gene for in vivo imaging, but also a therapeutic gene for local radionuclide therapy. Even a second therapeutic gene can be transfected into the same tumor cells together with hSSTr2 reporter gene to obtain a synergistic therapeutic effect. However, additional preclinical and especially translational and clinical researches are needed to confirm the value of hSSTr2 reporter gene based imaging and therapy in tumors. PMID:25879040

  13. Infrared Imaging for Inquiry-Based Learning

    NASA Astrophysics Data System (ADS)

    Xie, Charles; Hazzard, Edmund

    2011-09-01

    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 discussed by Vollmer et al. in 2001.1-3 IR cameras were then too expensive for most schools. Thanks to the growing need of home energy inspection using IR thermography, the price of IR cameras has plummeted and they have become easy to use. As of 2011, the price of an entry-level handheld IR camera such as the FLIR I3 has fallen below 900 for educators. A slightly better version, FLIR I5, was used to take the IR images in this paper. As easy to use as a digital camera, the I5 camera automatically generates IR images of satisfactory quality with a temperature sensitivity of 0.1°C. The purpose of this paper is to demonstrate how these affordable IR cameras can be used as a visualization, inquiry, and discovery tool. As the prices of IR cameras continue to drop, it is time to give teachers an update about the educational power of this fascinating tool, especially in supporting inquiry-based learning.

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

    NASA Astrophysics Data System (ADS)

    Lin, T.; Laporte, N. T.

    2003-12-01

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

  15. [Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

    PubMed

    Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

    2015-05-01

    This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

  16. [Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

    PubMed

    Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

    2015-05-01

    This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest. PMID:26571671

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

    PubMed

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

    2011-12-01

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

  18. Content-Based Image Retrieval in Medicine

    PubMed Central

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

    2009-01-01

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

  19. Design and implementation of semantics-based image retrieval system

    NASA Astrophysics Data System (ADS)

    Ni, Chundi; Liu, Shenkui; Pan, Ligong; Yin, Xiaowei

    2015-07-01

    Through the study of the existing image retrieval technology, in this paper, a new design scheme of semantics-based image retrieval system is presented. Based on the establishment of mapping relationship between the low-level image features and the low layer of semantic image, this scheme associates the low layer of semantic image with high-level semantics, thus realizing hierarchical semantics description structure, to improve the high-level semantic image recognition accuracy rate.

  20. Success with Web-based image access.

    PubMed

    Harrison, Sean W

    2003-01-01

    The University of Mississippi Medical Center in Jackson, Miss., is the only medical school in the state. We performed 235,000 procedures in the 2001-02 fiscal year. All imaging services within the radiology department are networked to a PACS and are filmless. The elimination of film required that we decentralize our traditional file room to allow easy access to our radiology network across the campus. In our facility, there are three levels of image access: Diagnostic Quality, Review Quality and Web Access. Diagnostic Quality requires top-of-the-line workstations and monitors and is the most expensive. Review Quality workstations represent some savings over Diagnostic and are used in the ICU, orthopedics and surgery. Web Access appears to satisfy most areas outside the main diagnostic department. The account set-up procedure is simple because it uses our intranet email system. Images are easily pasted into presentation applications for articles and conferences. However, the main advantage of Web Access is the low cost. The downside of Web Access is that the images are for review only and are limited by the quality of the monitor in use. It is also somewhat cumbersome to retrieve old or comparison images via this method. The Web only holds approximately 45 days of the most recent images, therefore older studies may not be available. The deployment of this Web-based service has aided in our efforts to reduce the amount of film we print and has also been beneficial in improving patient care through faster service. PMID:12800563

  1. Research on effect of Kell coefficient on the quality of aerial photography

    NASA Astrophysics Data System (ADS)

    Fan, Yue; Ma, Wenli

    2010-10-01

    The method of Spatial convolution is applied to analyze the imaging process of the CCD imaging system, which involves optical imaging process and CCD integral sampling process, and the ratio between GRD and GSD that is called Kell coefficient is introduced, based on which, analysis of effect of Kell coefficient on the quality of aerial photography is educed. Imaging process of the target is simulated with different Kell coefficient values by matlab. The method of the gray difference between the target and the image on CCD which is regarded as the evaluation criteria is proposed to evaluate the image quality. The simulation results show that when Kell coefficient equals 2.8, the target characteristics can be distinguished.

  2. Evaluation of aerial photography for predicting trends in structural attributes of Australian woodland including comparison with ground-based monitoring data.

    PubMed

    Fensham, Roderick J; Bray, Steven G; Fairfax, Russell J

    2007-06-01

    The accurate assessment of trends in the woody structure of savannas has important implications for greenhouse accounting and land-use industries such as pastoralism. Two recent assessments of live woody biomass change from north-east Australian eucalypt woodland between the 1980s and 1990s present divergent results. The first estimate is derived from a network of permanent monitoring plots and the second from woody cover assessments from aerial photography. The differences between the studies are reviewed and include sample density, spatial scale and design. Further analyses targeting potential biases in the indirect aerial photography technique are conducted including a comparison of basal area estimates derived from 28 permanent monitoring sites with basal area estimates derived by the aerial photography technique. It is concluded that the effect of photo-scale; or the failure to include appropriate back-transformation of biomass estimates in the aerial photography study are not likely to have contributed significantly to the discrepancy. However, temporal changes in the structure of woodlands, for example, woodlands maturing from many smaller trees to fewer larger trees or seasonal changes, which affect the relationship between cover and basal area could impact on the detection of trends using the aerial photography technique. It is also possible that issues concerning photo-quality may bias assessments through time, and that the limited sample of the permanent monitoring network may inadequately represent change at regional scales. PMID:16828220

  3. Blending zone determination for aerial orthimage mosaicking

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

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

    PubMed

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

    2016-08-19

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  7. Locating buildings in aerial photos

    NASA Technical Reports Server (NTRS)

    Green, James S.

    1994-01-01

    Algorithms and techniques for use in the identification and location of large buildings in digitized copies of aerial photographs are developed and tested. The building data would be used in the simulation of objects located in the vicinity of an airport that may be detected by aircraft radar. Two distinct approaches are considered. Most building footprints are rectangular in form. The first approach studied is to search for right-angled corners that characterize rectangular objects and then to connect these corners to complete the building. This problem is difficult because many nonbuilding objects, such as street corners, parking lots, and ballparks often have well defined corners which are often difficult to distinguish from rooftops. Furthermore, rooftops come in a number of shapes, sizes, shadings, and textures which also limit the discrimination task. The strategy used linear sequences of different samples to detect straight edge segments at multiple angles and to determine when these segments meet at approximately right-angles with respect to each other. This technique is effective in locating corners. The test image used has a fairly rectangular block pattern oriented about thirty degrees clockwise from a vertical alignment, and the overall measurement data reflect this. However, this technique does not discriminate between buildings and other objects at an operationally suitable rate. In addition, since multiple paths are tested for each image pixel, this is a time consuming task. The process can be speeded up by preprocessing the image to locate the more optimal sampling paths. The second approach is to rely on a human operator to identify and select the building objects and then to have the computer determine the outline and location of the selected structures. When presented with a copy of a digitized aerial photograph, the operator uses a mouse and cursor to select a target building. After a button on the mouse is pressed, with the cursor fully within

  8. Aerial views of the San Andreas Fault

    USGS Publications Warehouse

    Moore, M.

    1988-01-01

    These aerial photographs of the San Andreas fault were taken in 1965 by Robert E. Wallace of the U.S Geological Survey. The pictures were taken with a Rolliflex camera on 20 format black and white flim; Wallace was aboard a light, fixed-wing aircraft, flying mostly at low altitudes. He photographed the fault from San Francisco near its north end where it enters by the Salton Sea. These images represent only a sampling of the more than 300 images prodcued during this project. All the photographs reside in the U.S Geological Survey Library in Menlo Park, California. 

  9. USGS Earth Explorer Client for Co-Discovery of Aerial and Satellite Data

    NASA Astrophysics Data System (ADS)

    Longhenry, R.; Sohre, T.; McKinney, R.; Mentele, T.

    2011-12-01

    The United States Geological Survey (USGS) Earth Resources Observation Science (EROS) Center is home to one of the largest civilian collections of images of the Earth's surface. These images are collected from recent satellite platforms such as the Landsat, Terra, Aqua and Earth Observer-1, historical airborne systems such as digital cameras and side-looking radar, and digitized historical aerial photography dating to the 1930's. The aircraft scanners include instruments such as the Advanced Solid State Array Spectrometer (ASAS). Also archived at EROS are specialized collections of aerial images, such as high-resolution orthoimagery, extensive collections over Antarctica, and historical airborne campaigns such as the National Aerial Photography Program (NAPP) and the National High Altitude Photography (NHAP) collections. These collections, as well as digital map data, declassified historical space-based photography, and variety of collections such as the Global Land Survey 2000 (GLS2000) and the Shuttle Radar Topography Mission (SRTM) are accessible through the USGS Earth Explorer (EE) client. EE allows for the visual discovery and browse of diverse datasets simultaneously, permitting the co-discovery and selection refinement of both satellite and aircraft imagery. The client, in use for many years was redesigned in 2010 to support requirements for next generation Landsat Data Continuity Mission (LDCM) data access and distribution. The redesigned EE is now supported by standards-based, open source infrastructure. EE gives users the capability to search 189 datasets through one interface, including over 8.4 million frames of aerial imagery. Since April 2011, NASA datasets archived at the Land Processes Distributed Active Archive Center (LP DAAC) including the MODIS land data products and ASTER Level-1B data products over the U.S. and Territories were made available via the EE client enabling users to co-discover aerial data archived at the USGS EROS along with USGS

  10. Image superresolution of cytology images using wavelet based patch search

    NASA Astrophysics Data System (ADS)

    Vargas, Carlos; García-Arteaga, Juan D.; Romero, Eduardo

    2015-01-01

    Telecytology is a new research area that holds the potential of significantly reducing the number of deaths due to cervical cancer in developing countries. This work presents a novel super-resolution technique that couples high and low frequency information in order to reduce the bandwidth consumption of cervical image transmission. The proposed approach starts by decomposing into wavelets the high resolution images and transmitting only the lower frequency coefficients. The transmitted coefficients are used to reconstruct an image of the original size. Additional details are added by iteratively replacing patches of the wavelet reconstructed image with equivalent high resolution patches from a previously acquired image database. Finally, the original transmitted low frequency coefficients are used to correct the final image. Results show a higher signal to noise ratio in the proposed method over simply discarding high frequency wavelet coefficients or replacing directly down-sampled patches from the image-database.

  11. The DOE ARM Aerial Facility

    SciTech Connect

    Schmid, Beat; Tomlinson, Jason M.; Hubbe, John M.; Comstock, Jennifer M.; Mei, Fan; Chand, Duli; Pekour, Mikhail S.; Kluzek, Celine D.; Andrews, Elisabeth; Biraud, S.; McFarquhar, Greg

    2014-05-01

    The Department of Energy Atmospheric Radiation Measurement (ARM) Program is a climate research user facility operating stationary ground sites that provide long-term measurements of climate relevant properties, mobile ground- and ship-based facilities to conduct shorter field campaigns (6-12 months), and the ARM Aerial Facility (AAF). The airborne observations acquired by the AAF enhance the surface-based ARM measurements by providing high-resolution in-situ measurements for process understanding, retrieval-algorithm development, and model evaluation that are not possible using ground- or satellite-based techniques. Several ARM aerial efforts were consolidated into the AAF in 2006. With the exception of a small aircraft used for routine measuremen