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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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Spectral features recognition based on data mining algorithms

Spectral features recognition based on data mining algorithm...

引用

15th International conference on Geoinformatics

作者： Du, Peijun Su, Hongjun Zhang, Wei China Univ Min & Technol Dept Remote Sensing & Geog Informat Sci Xuzhou 22100 Jiangsu Prov Peoples R China Univ Nottingham Ctr Geospat Sci Nottingham NG7 2RD England Nanjing Normal Univ Minist Educ Key Lab Virtual Geog Environm Nanjing 210046 Jiangsu Peoples R China

ISBN: (纸本)9780819469120

In order to discover those significant spectral features that are of effectiveness to target identification, some Data Mining algorithms were used to the data sets from USGS spectral library and OMIS hyperspectral remote sensing image. The candidate feature sets were generated by traditional spectral feature extraction approaches at first, and then clustering, statistical analysis and decision tree were used to characterized feature recognition and target identification model design. Derivative spectrum has the superiority of enhancing the characteristic spectral features in contrast with other algorithms. The recognition decision tree based on the knowledge and rules can identify and discriminate targets using the discovered spectral features. The experiment showed that the proposed characterized spectral features recognition approach based on Data Mining algorithm was suitable to hyperspectral remote sensing information processing.

关键词： hyperspectral remote sensing characteristic spectral features clustering decision tree data mining

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Integration of motion cues in optical and sonar videos for 3-D positioning

Integration of motion cues in optical and sonar videos for 3...

引用

IEEE conference on Computer Vision and pattern recognition

作者： Negahdaripour, S. Pirsiavash, H. Sekkati, H. Univ Miami Dept Elect & Comp Engn Coral Gables FL 33124 USA

ISBN: (纸本)9781424411795

Target-based positioning and 3-D target reconstruction are critical capabilities in deploying submersible platforms for a range of underwater applications, e.g., search and inspection missions. While optical cameras provide high-resolution and target details, they are constrained by limited visibility range. In highly turbid waters, target at up to distances of 10s of meters can be recorded by high-frequency (MHz) 2-D sonar imaging systems that have become introduced to the commercial market in recent years. Because of lower resolution and SNR level and inferior target details compared to optical camera in favorable visibility conditions, the integration of both sensing modalities can enable operation in a wider range of conditions with generally better performance compared to deploying either system alone. In this paper, estimate of the 3-D motion of the integrated system and the 3-D reconstruction of scenefeatures are addressed. We do not require establishing matches between optical and sonar features, referred to as opti-acoustic correspondences, but rather matches in either the sonar or optical motion sequences. In addition to improving the motion estimation accuracy, advantages of the system comprise overcoming certain inherent ambiguities of monocular vision, e.g., the scale-factor ambiguity, and dual interpretation of planar scenes. We discuss how the proposed solution provides an effective strategy to address the rather complex opti-acoustic stereo matching problem. Experiment with real data demonstrate our technical contribution.

关键词： image matching image reconstruction image sequences inspection motion estimation sonar signal processing stereo image processing 2D sonar imaging systems 3D motion estimation 3D scene features reconstruction 3D target reconstruction inspection mission mo

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Study on the retrieval of the at-surface radiances for thermal infrared channels by using NOAA-AVHRR data

Study on the retrieval of the at-surface radiances for therm...

引用

5th International Symposium on Multispectral image processing and pattern recognition

作者： Zhu, Shanyou Zhang, Guixin Chen, Jian Nanjing Univ Sci & Technol Remote Sensing Sch Nanjing 210044 Peoples R China

ISBN: (纸本)9780819469519

The at-surface radiances of a thermal infrared channel relates to the land materials characters, which is composed of the thermal radiance of the land itself and the atmospheric downwelling radiance reflected by the land surface. This parameter is very important for thermal infrared remote sensing, but the researches about its retrieving from the remote sensors with a wider spectral range are less. This paper discussed a method to retrieve the parameter by using the NOAA-AVHRR image itself. The method was firstly theoretically deduced based on the thermal radiance transmission theory. According to the deduction, the atmospheric transmittance and the upwelling radiance of the imaging time can be expressed by the relation of two channels at-sensor radiances, which are used to calculate the at-surface radiances. Then the simulated data were used to determine the model's coefficients and prove the feasibility of the theoretical retrieval method. The relative root mean square error for the research method was about 5.0 percent by comparing with the validation data, which showed that the method could simply and effectively compute the at-surface radiance of the two thermal infrared channels by the image itself for the AVHRR sensors. Even if lacking of the synchronous atmospheric parameters, a higher retrieval precision also exist.

关键词： the at-surface radiances the at-sensor radiances retrieve NOAA-AVHRR the thermal radiance transmission theory

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Research of detection range of LWIR dispersive imaging spectrometer

Research of detection range of LWIR dispersive imaging spect...

引用

5th International Symposium on Multispectral image processing and pattern recognition

作者： Xu, Hong Wang, Xiangjun Tianjin Univ Natl Lab Precis Measurement Technol & Instruments Coll Precis Instrument & Optoelect Engn Tianjin 300072 Peoples R China

ISBN: (纸本)9780819469502

Among various types of long-wave infrared spectrometers, dispersive spectrometer has the simplist structure and has shown good service behavior in all kinds of imaging spectroscopy applications. For the technology of infrared remote imaging spectroscopy, an excellent designed imaging spectrometer is the key factor. Of all the designing factors, the tradeoff between the detection performance and the structure size is always the main topic. In this paper, according to the performance parameters of the used infrared sensor, characteristic of energy transmission of dispersive spectrometer, characteristic of target radiation and the effect of atmospheric transmission, a comprehensive research is done to construct a perfect receiving radiation model of LWIR dispersive spectrometer, providing theoretical foundations for accurately determining the relationship between instrumental structure parameters and the detection range. A designing model with an uncooled microbolometer as its detector is calculateded to analyse its potential in the application of long-wave remote imaging spectroscopy.

关键词： LWIR imaging spectrometer dispersive spectrometer detection range hyperspectral remote sensing

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A perturbation suppressing segmentation technique based on adaptive diffusion

A perturbation suppressing segmentation technique based on a...

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8th International conference on Adaptive and Natural Computing Algorithms (ICANNGA)

作者： Middelmann, Wolfgang Ebert, Alfons Deissler, Tobias Thoennessen, Ulrich FGAN-FOM Research Institute for Optronics and Pattern Recognition Germany

ISBN: (纸本)9783540715900

Segmentation is a fundamental task in pattern recognition and basis for high level applications like scene reconstruction, change detection, or object classification. The performance of these tasks suffers from a distorted segmentation. In this contribution an adaptive diffusion-based segmentation method is proposed suppressing perturbations in the segmentation with focusing on small regions with high contrast to their surrounding. The algorithm determines in each step the diffusion tensor. It is re-weighted with respect to an assessment stage. A comparative study uses high-resolution remote sensing data.

关键词： image segmentation

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Hyperspectral image fusion using empirical mode decomposition

Hyperspectral image fusion using empirical mode decompositio...

引用

conference on Medical Imaging, Parallel processing of images, and Optimization Techniques

作者： Xu, Yiping Hu, Kaoning Han, Jianxin Huazhong Univ Sci & Technol Dept Elect & Informat Engn Wuhan 430074 Peoples R China Shandong Univ Finance Sch Stat & Math Jinan 250014 Peoples R China

ISBN: (纸本)9780819469533

The technology of hyperspectral remote sensing, as an advanced technology in remote sensing, has been found wide application in many fields. However, the massive and high dimension data produce a challenge during its processing and analysis. Hyperspectral image fusion is rising as a new method which results from this background. The fused image would have enhanced information which is more understandable and decipherable for object recognition accurately. In this paper, we propose a novel method for image fusion and enhancement, using Empirical Mode Decomposition (EMD). EMD is a new data analysis method which expresses the. tendency of signals at different scales by decomposing any complicated signal into a set of Intrinsic Mode Functions (IMFs). In this method, we decompose images from different hyperspectral band into their IMFs, and perform image fusion at the decomposition level. Based on an empirical understanding of the nature of the IMF, we devise adaptive weighting schemes which emphasize features from different band image, thereby increasing the information and visual content of the fused image.

关键词： hyperspectral image image fusion empirical mode decomposition

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Nitrogen content estimation using Hyperion hyperspectral image based on normalized band depth method

Nitrogen content estimation using Hyperion hyperspectral ima...

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5th International Symposium on Multispectral image processing and pattern recognition

作者： Yuan, Jinguo Niu, Zheng Long, Limin Li, Shihua Hebei Normal Univ Coll Resource & Environm Sci 113 Yuhua E Rd Shijiazhuang 050016 Peoples R China Chinese Acad Sci Inst Remote Sensing Applicat State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China

ISBN: (纸本)9780819469519

Canopy nitrogen content has strong relationship with net primary productivity, litter nitrogen and nitrogen mineralization rate, so the estimation of nitrogen content can provide valuable understanding of large-scale terrestrial carbon and nitrogen cycle. Hyperspectral remote sensing technology demonstrates the capacity for accurate biochemical component estimation of vegetation. This paper employed Hyperion hyperspectral data acquired over Xishuangbanna tropical area in Yunnan province, China to estimate nitrogen content based on normalized band depth (BNC) method. Hyperion data geometric and radiometric corrections were first made, and then Hyperion reflectance of 56 samples in 35 plots was extracted. Continuum removal was applied to the selected absorption features related to nitrogen. The BNC of 56 samples were calculated. Relationships between BNC values in Hyperion image and in situ field measured nitrogen content were analyzed using stepwise multiple linear regression. Results showed that central wavelengths in the model predicting nitrogen were 650.67nm, 2213.93nm, 2173.53nm and 671.02nm, and coefficient of determination (R) was 0.505. Bands 650.67nm and 671.02nm coincided with chlorophyll absorption features highly related to nitrogen;2213nm and 2173nm corresponded to protein and nitrogen absorption features. Correlation analysis showed that the biggest correlation coefficient between nitrogen and BNC was -0.573, which was at 650.67nm.

关键词： hyperion hyperspectral data nitrogen content estimation continuum removal normalized band depth method regression analysis

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Building detection from LIDAR and images in urban areas

Building detection from LIDAR and images in urban areas

引用

conference on pattern recognition and Computer Vision

作者： Guan, Haiyan Deng, Fei Zhang, Jianqing Wuhan Univ Sch Remote Sensing Informat Engn 129 Luoyu Rd Wuhan 430079 Peoples R China Wuhan Univ Sch Geodesy & Geomat Wuhan 430079 Peoples R China

ISBN: (纸本)9780819469526

Rapid texture mapping of buildings is a key aspect for reconstruction of 3D city landscapes. An effective approach by the way of coarse-to-fine 3D building model generation by integration of LIDAR and multiple overlap images is proposed. Classification and segmentation can be processed by combined multi-spectral information which is provided by color aerial image and geometric information from multi-return laser scanned data. A connected graph of the segment label image has to be created to derive the neighborhood relation of the planar segments. A line segment matching, based on geometry and chromatic constraint, is applied for automatically getting the corresponding line features in multi target images. Hypotheses for polyhedral surfaces are selected using topological relations and verified using geometry.

关键词： LIDAR building detection modelling pattern recognition

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Scale-adaptive segmentation and recognition of individual trees based on LiDAR data 1

引用

4th International conference on image Analysis and recognition

作者： Palenichka, Roman M. Zaremba, Marek B. Univ Quebec Outaouais Quebec City PQ Canada

ISBN: (数字)9783540742609

ISBN: (纸本)9783540742586

A scale-adaptive method for tree segmentation and recognition based on the LiDAR height data is described. The proposed method uses an isotropic matched filtering operator optimized for the fast and reliable detection of local and multiple objects. Sequential local maxima of this operator indicate the centers of potential objects of interest such as the trees. The maxima points also represent the seed pixels for the region-growing segmentation of tree crowns. The tree verification (recognition) stage consists of tree feature estimation and comparison with reference values. Various non-uniform tree characteristics are taken into account when making decision about a tree presence in the found location. Experimental examples of the application of this method for the tree detection in LiDAR images of forests are provided.

关键词： remote sensing LiDAR data Digital Surface Model (DSM) image segmentation tree recognition multi-scale isotropic matched filtering (MIMF) local scale feature estimation

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Algorithm research on extracting terrain parameters using data of multi-return signal LiDAR

Algorithm research on extracting terrain parameters using da...

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5th International Symposium on Multispectral image processing and pattern recognition

作者： Li, Shuiming Zhi, Xiaodong Su, Guozhong Wuhan Univ Sch Remote Sensing Informat Engn 129 Luoyu Rd Wuhan 430079 Peoples R China Chinese Acad Sci Acad Optoelect Beijing 100080 Peoples R China

ISBN: (纸本)9780819469519

Through analyzing on data acquisition mechanism of LiDAR's multi-return signal, we deduce the relational model of microtopography and corresponding return signal, further research the rapid extract algorithms about terrain slopes, roughness and others terrain parameters. And then validate them by consecutive return signal data of GLAS, and field. experiment.

关键词： LiDAR multi-return signal terrain

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