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检索条件"任意字段=Conference on Image Processing and Pattern Recognition in Remote Sensing"

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Multisensor data fusion based on the second generation curvelet transform

Multisensor data fusion based on the second generation curve...

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5th International Symposium on Multispectral image processing and pattern recognition

作者： Xiao, Moyan He, Zhibiao Wuhan Univ Sch Remote Sensing & Informat Engn 129 Loyu Rd Wuhan 430079 Peoples R China Wuhan Univ GPS Ctr Wuhan 430079 Peoples R China

ISBN: (纸本)9780819469519

This paper aims to describe an improved method for integrating the SAR features into multispectral(MS) images based on the second generation curvelet transform. Curvelet transform(CT),as a special member of the emerging family of multiscale geometric transform, overcomes inherent limitation of traditional multiscale representation and owns very high directional sensitivity and anisotropy. It represents edges and singularities along curves much more efficiently than the traditional wavelet transform. To get more information in fusion image, the curvelet transform is introduced. The proposal of the second generation curvelet theory makes it understood and implemented more easily. SAR image has higher spatial resolution, but MS images have more spectral information. In order to get maximal integration of SAR features and the maximal preservation of the spectral content, two kinds of images may be implemented by different scales curvelet decomposition. And these decomposed curvelet coefficients can be processed according to certain fusion regular. Then detail information of SAR and approximate information of MS will be extracted by inverse curvelet transform respectively. At last fused image is obtained by injecting SAR's detail information into the MS's approximate information. Landsat TM and SAR images covering a region of sanshui in Guangdong province are used to evaluate the effect of the proposed method and some other fusion methods in terms of spectral preservation and spatial resolution improvement. The results show that the proposed method can provide richer information in the spatial and spectral domain.

关键词： multispectral (MS) image SAR image fusion curvelet transform fast discrete curvelet transform (FDCT) Multiscale Geometric Analysis (MGA)

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OSIRIS: a European project using a High Altitude Platform for forest fire monitoring

OSIRIS: a European project using a High Altitude Platform fo...

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2nd International conference Safety and Security Engineering

作者： Lewyckyj, N. Biesemans, J. Everaerts, J. Flemish Inst Technol Res VITO TAP Remote Sensing & Earth Observ Proc Unit Mol Belgium

ISBN: (纸本)9781845640682

Within the framework of the European FP6 IST-5 project OSIRIS, a High Altitude Platform (HAP) will be used for the first time for surveying forest fires in the South of France. The HAP used will be the Mercator-1 Unmanned Aerial Vehicle (UAV) acquired by the Flemish Institute for Technological Research (VITO) in Belgium. Mercator-1, a solar aircraft able to remain for days at stratospheric altitudes (14 to 20 km), will be used as a platform for a high resolution camera (GSD of a few meters). The platform will be controlled directly by an operator at a mobile Ground Control Station (GCS) or execute pre-defined flight planning (way points), which can be updated during flight. This will allow the end-users to optimize the image acquisition pattern as a function of the fire evolution. Because of its low airspeed, the platform is able to hover above a small region. Unprocessed data (level 0) will be down linked in real-time to the GCS for further processing (up to level 3 if required). Decision makers and/or the commanding officer of the fire brigades will thus have rapid access to up-to-date information at the intervention place. Furthermore, by means of a satellite uplink, the imagery will also be forwarded to a Central Data processing Centre which is plugged into the OSIRIS Sensor Web. During the OSIRIS demonstration activities the benefits of the Sensor Web concept with respect to faster and/or better decision making will be evaluated. The unmanned character of the platform does not put any pilots at risk and its long endurance allows the HAP to be used for the different phases of a disaster (from preparedness to recovery). Furthermore, the system will provide high resolution combined with frequent image update. A live demonstration is planned for spring 2009.

关键词： disaster management forest fire remote sensing real-time high resolution HAP UAV PEGASUS OSIRIS

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Research of 3D model construction and visualization of complicated objects in 3D cyber-city - art. no. 67880J

Research of 3D model construction and visualization of compl...

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conference on pattern recognition and Computer Vision

作者： Chen, Peng Meng, Linkui Wuhan Univ Sch Remote Sensing Informat Engn Wuhan 430079 Peoples R China

ISBN: (纸本)9780819469526

In order to settle the conflict of the visualization efficiency and the great amount data in digital city in 3d GIS system, the author put forward a 3D data model with LOD ability especially for the complex 3d object such as buildings in 3d city GIS system. In this paper, the author described the components of the complex 3d object, then explained that we can settle the conflict mentioned above by designing a new model that has the capability of describing levels of details. The author expound the basic theory of the model with LOD ability related with the vision point, and then defined several key conceptions, at same time, the author analyzed the principles and the visualization process of the model in 3d space. In the end of the paper, the author verified data model through an experiment, the results of the experiment showed that the model put forward is effective and high efficiency.

关键词： 3D data model LOD 3D visualization

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Detection of weak laser pulses by full waveform stacking

Detection of weak laser pulses by full waveform stacking

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Photogrammetric image Analysis, PIA 2007

作者： Stilla, U. Yao, W. Jutzi, B. Photogrammetry and Remote Sensing Technische Universitaet Muenchen Arcisstr. 21 80290 Munich Germany FGAN-FOM Research Institute for Optronics and Pattern Recognition 76275 Ettlingen Germany

Pulse detection is a fundamental task of processing data of pulsed laser systems for extracting features of the illuminated object. Weak pulses below the threshold are discarded by classic methods and the involved information will get lost. In this paper we present an approach for detecting weak pulses from waveform laser data based on analyzing neighbourhood relations given by coplanarity constraint. Waveform stacking technique is used to improve the signal to noise ratio (SNR) of object with poor surface response by means of mutual information accumulation, thus hypotheses for planes of different slopes are generated and verified. Each signal is assessed by a likelihood value with respect to accepted hypotheses. At last signals will be classified according to likelihood values using two thresholds and visualized by the traffic-light paradigm. The presented method was applied as a low-level operation to a whole waveform cuboid of an urban area and shows promising results. Results contain detected pulses reflected from objects, which can not be predicted by the previously detected point cloud.

关键词： Signal to noise ratio

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Three-dimensional reconstruction from the method of CAD-based Photogrammetry

Three-dimensional reconstruction from the method of CAD-base...

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MIPPR 2007: pattern recognition and Computer Vision

作者： Ling, Yang Shunyi, Zheng School of Remote Sensing and Information Engineering Wuhan University Wuhan City 430079 China

ISBN: (纸本)9780819469526

The three-dimensional (3D) reconstruction has become a hot research field of Photogrammetry and computer vision. This paper presents a measurement method of CAD-based Photogrammetry to do 3D reconstruction. CAD models and images which the exterior orientation is known are used. The visible edges of a volumetric CAD model with an initial pose are projected back into images after a hidden line analysis. This analysis determines which edges (or parts of edges) of the object are visible, and computes the edges of the object. Observation equations are formulated that establish the relationship between the parameterized CAD models and position of the edges in the images. The flow of this paper is as fellows. Firstly, parameterized CAD models are used to describe 3D objects, object models can be described in various ways, and this paper uses CSG models combined with B-rep. Secondly, fitting models to images. Manually select an appropriate model and approximate parameters, the parameterized models are projected back into the images, and then compute the optimal fitting automatically. Thirdly, calculate the parameters of the model. Experiments were done to box, sphere and column, which are the base primitive of some objects. The results of these experiments show that the method used in this paper are effective and have high precision. All primitives used in these experiments are well reconstructed.

关键词： image reconstruction

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Automatic structure detection in a point-cloud of buildings obtained by terrestrial laser scanning

Automatic structure detection in a point-cloud of buildings ...

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5th International Symposium on Multispectral image processing and pattern recognition

作者： Zhan, Qingming Pang, Qiancong Shi, Wenzhong Wuhan Univ Sch Urban Design 8 Dong Hu Nan Lu Wuhan 430072 Peoples R China Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430072 Peoples R China Wuhan Univ Res Ctr Digital City Wuhan 430072 Peoples R China Hong Kong Polytech Univ Adv Res Ctr Spatial Informat Technol Dept Land Surveying & Geo Informat Hong Kong Peoples R China

ISBN: (纸本)9780819469502

In recent years, terrestrial laser scanner (TLS) has become a popular data acquisition tool for producing irregularly-spaced point clouds as well as airborne laser scanning (ALS). Automated detection of structures (roof and ground etc.) based on the point cloud analysis of buildings has become increasingly important. One of the most demanding tasks in TLS is the filtering of the ground and roofs in TLS point clouds. This paper proposes a method for detecting buildings' structures from an irregularly-spaced point-cloud. This method is consisted of segmentation and classification. As the previously developed the segmentation methods can not be applied to it directly, it has to perform twice pre-filtration so as to proceed to further calculation for segmentation and classification. More importantly the algorithm is extensible and future work will further strengthen the algorithm.

关键词： point clouds classification segmentation reconstruction

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Use of binary logistic regression technique with Modis data to estimate Wild Fire Risk

Use of binary logistic regression technique with Modis data ...

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5th International Symposium on Multispectral image processing and pattern recognition

作者： Fan, Hong Di, Liping Yang, Wenli Bonnlander, Brian Li, Xiaoyan George Mason Univ CSISS 6301 Ivy LaneSuite 620 Greenbelt MD 20770 USA Wuhan Univ Natl Lab Informat Engn Surveying Mapping & Remote Sensing Wuhan 430079 Peoples R China Florida Inst Human & Machine Cognit Pensacola FL 32502 USA

ISBN: (纸本)9780819469502

Many forest fires occur across the globe each year, which destroy life and property, and strongly impact ecosystems. In recent years, wildland fires and altered fire disturbance regimes have become a significant management and science problem affecting ecosystems and wildland/urban interface cross the United States and global. In this paper, we discuss the estimation of 504 probability models for forecasting fire risk for 14 fuel types, 12 months, one day/week/month in advance, which use 19 years of historical fire data in addition to meteorological and vegetation variables. MODIS land products are utilized as a major data source, and a logistical binary regression was adopted to solve fire forecast probability. In order to better modeling the change of fire risk along with the transition of seasons, some spatial and temporal stratification strategies were applied. In order to explore the possibilities of real time prediction, the Matlab distributing computing toolbox was used to accelerate the prediction. Finally, this study give an evaluation and validation of predict based on the ground truth collected. Validating results indicate these fire risk models have achieved nearly 70% accuracy of prediction and as well MODIS data are potential data source to implement near real-time fire risk prediction.

关键词： fire risk forecast binary logistic regression ROC evaluation MODIS distributed computing

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Noninvasive forward-scattering system for rapid detection, characterization, and identification of bacterial colonies

Noninvasive forward-scattering system for rapid detection, c...

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conference on Chemical and Biological sensing VIII

作者： Rajwa, Bartek Bayraktar, Bulent Banada, Padmapriya P. Huff, Karleigh Bae, Euiwon Hirleman, E. Daniel Bhunia, Arun K. Robinson, J. Paul Purdue Univ Bindley Biosci Ctr W Lafayette IN 47907 USA Purdue Univ Dept Elect & Comp Engn W Lafayette IN 47907 USA Purdue Univ Mol Food Microbiol Lab W Lafayette IN 47907 USA Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA Purdue Univ Sch Vet Med Dept Basic Med Sci W Lafayette IN 47907 USA Purdue Univ Weldon Sch Biomed Engn W Lafayette IN 47907 USA

ISBN: (纸本)9780819466761

Bacterial contamination of food products puts the public at risk and also generates a substantial cost for the food-processing industry. One of the greatest challenges in the response to these incidents is rapid recognition of the bacterial agents involved. Only a few currently available technologies allow testing to be performed outside of specialized microbiological laboratories. Most current systems are based on the use of expensive PCR or antibody-based techniques, and require complicated sample preparation for reliable results. Herein, we report our efforts to develop a non-invasive optical forward-scattering system for rapid, automated identification of bacterial colonies grown on solid surfaces. The presented system employs computer-vision and pattern-recognition techniques to classify scatter patterns produced by bacterial colonies irradiated with laser light. Application of Zernike and Chebyshev moments, as well as Haralick texture descriptors for image feature extraction, allows for a very high recognition rate. An SVM algorithm was used for classification of patterns. Low error rates determined by cross-validation, reproducibility of the measurements, and robustness of the system prove that the proposed technology can be implemented in automated devices for bacterial detection.

关键词： Pathogens Laser scattering Organisms Computing systems Bacteria Detection and tracking algorithms Feature extraction image classification Contamination Solids

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A FCM algorithm for remote-sensing image classification considering spatial relationship and its parallel implementation

A FCM algorithm for remote-sensing image classification cons...

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International conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Xue-Jing Gong Lin-Lin Ci Kang-Ze Yao Academy of Equipment Command슠and슠Technology Beijing China Beijing Institute of Technology Beijing China

Fuzzy C-Means clustering is one of the most perfective and widely used algorithms based on objective function for unsupervised classification. Considering the spatial relationship of pixels when it is used in remote sensing imagery, Neighbor-based FCM algorithm is put forward with the method of modifying the value of fuzzy membership degrees with the neighbor information during the clustering iterations. We use dominant class, if it can be determined in a fixed neighbor region, or the weighted parameters based on the distance of neighbors to perfect the membership degrees of central pixel. Then parallel implement for the algorithm is also proposed by taking account into the communication complexity and the spatial relationship for image partition. In the end, the experimental data indicate the efficiency of the algorithm in decreasing the amount of clustering iterations and increasing the classified precision; the parallel algorithm also achieves the satisfied linear speedup.

关键词： remote sensing image classification Clustering algorithms Pixel Partitioning algorithms Wavelet analysis pattern analysis Algorithm design and analysis pattern recognition

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An Attractive Leader Approach Based Clustering for Non-Symmetric Proximity

An Attractive Leader Approach Based Clustering for Non-Symme...

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International conference on Signal processing, Communication and Networking (ICSCN)

作者： Bapu B. Kiranagi D.S. Guru Department of Studies in Computer Science University of Mysore India

In this paper, the importance of non-symmetric proximity between symbolic data is discussed and a new algorithm for clustering is proposed. The proposed algorithm works directly on the non-symmetric proximity matrices and is based on the leader oriented incremental approach. Experiments on the standard symbolic data sets have been conducted in order to study the efficacy of the proposed methodology

关键词： Clustering algorithms Symmetric matrices Data engineering Object oriented modeling pattern analysis image analysis pattern recognition image processing remote sensing Biomedical imaging

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