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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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Application of passive imaging polarimetry in the discrimination and detection of different color targets of identical shapes using color-blind imaging sensors

Application of passive imaging polarimetry in the discrimina...

引用

conference on Polarization - Measure, Analysis and remote sensing VII

作者： El-Saba, A. M. Alam, M. S. Surpanani, A. Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

ISBN: (纸本)0819462969

Important aspects of automatic pattern recognition systems are their ability to efficiently discriminate and detect proper targets with low false alarms. In this paper we extend the applications of passive imaging polarimetry to effectively discriminate and detect different color targets of identical shapes using color-blind imaging sensor. For this case of study we demonstrate that traditional color-blind polarization-insensitive imaging sensors that rely only on the spatial distribution of targets suffer from high false detection rates, especially in scenarios where multiple identical shape targets are present. On the other hand we show that color-blind polarization-sensitive imaging sensors can successfully and efficiently discriminate and detect true targets based on their color only. We highlight the main advantages of using our proposed polarization-encoded imaging sensor.

关键词： passive imaging Stokes imaging polarimetry polarization-encoding optical processing target recognition

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Digital image processing of high resolution aerial photograph of Shallow Marine Sanctuary, Victoria, Australia

Digital image processing of high resolution aerial photograp...

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2006 International conference on Advances in Space Technologies, ICAST

作者： Saeed, Fawad

ISBN: (纸本)1424405149

In this paper the potential of remote sensing as a tool to study Marine Sanctuary has been explored. There are two main methods that can be used to extract information from the aerial photograph / satellite imagery;visual interpretation and digital image processing. Visual interpretation takes advantage of the human skills to recognize data "content" by combining several elements of image interpretation. It relies on experience, a prior knowledge and skilled analysts qualities to produce excellent results. Alternatively, digital image classification employs computer techniques which are mostly based on the reflection values of individual pixels and use statistical pattern recognition methods. In the current study, the main area of interest was distribution of sand, rocky reef, rocky rubble and sea grass in the sanctuary. The study showed that the supervised classification approach was a superior technique to employ for such studies as compare to other traditional approaches. Here, the higher degree of interaction between the analyst and the machine complements the limitations of each other. Furthermore, the analyst is also given the opportunity to "control" which digital signatures best qualify to represent a certain resource class considering the fact that the analyst has access to ground truth data to fine tune the classification. © 2006 IEEE.

关键词： Antennas

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Tropospheric aerosols remote sensing over the water surface of Penang Island

Tropospheric aerosols remote sensing over the water surface ...

引用

conference on Signal processing, Sensor Fusion, and Target recognition XV

作者： Hashim, S. A. MatJafri, M. Z. Abdullah, K. Lim, H. S. Wong, C. J. Salleh, N. Mohd. Univ Sains Malaysia Sch Phys Minden 11800 Pulau Pinang Malaysia

ISBN: (纸本)0819462918

Tropospheric aerosols play an important role in climate change. Aerosols are typically studied over deep clear water, due to the relatively constant reflectance of water and the ability to easily separate surface and atmospheric contributions on the satellite signal. A methodology based on multi-spectral approach was employed to map tropospheric aerosols concentrations over the water areas surrounding Penang Island. The aim of this study was to estimate the pollutants concentrations using remote sensing techniques. In this study, we attempted to derive AOT(Aerosol Optical Thickness) values from the sky transmittance measurements in the visible spectrum. The transmittance values were measured at the sea surface using a handheld spectroradiometer. The correspond PM10 readings were taken simultaneously during the transmittance measurements acquisition of the imageries using a Dust Trak(TM) meter. The PCI Geomatica version 9.1 digital image processing software was used in all image-processing analyses. The results produced a linear relationship between PM10 and AOT values over the water surface of Penang Island. Finally, The PM10 concentration map over the water surface of Penang Island was generated using Kriging interpolation technique. This study has indicated the potential use of a handheld spectroradiometer for air quality study.

关键词： tropospheric AOT transmittance PM10 spectroradiometer DustTrak (TM) meter

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Radar signal classification using PCA-based features

Radar signal classification using PCA-based features

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31st IEEE International conference on Acoustics, Speech and Signal processing

作者： Mishra, Amit Kumar Mulgrew, Bernard Univ Edinburgh IDCOM Edinburgh EH8 9YL Midlothian Scotland

ISBN: (纸本)9781424404681

Principal component analysis (PCA) has been used in many applications ranging from social science to space science, for the purpose of data compression and feature extraction. Usage of PCA for synthetic aperture radar (SAR) image classification, though widely reported by remote-sensing researchers, has not been exploited much by automatic target recognition (ATR) community. In the present paper, PCA has been used in SAR-ATR using the MSTAR data base, and comparison has been made with the conventional conditional Gaussian model based Bayesian classifier [1]. The results have been compared based on percentage of correct classification, receiver operating characteristics (ROC), and performance with limited amount of training data. By all standards of comparison, the PCA based classifier was observed to outperform the conditional Gaussian model based Bayesian classifier (CGBC) or at the worst it performs at par. And given the computational and algorithmic simplicity of PCA based classifier, the new algorithm was concluded to be a highly prospective candidate for real time ATR systems.

关键词： image classification

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pattern recognition in multiband imagery using stochastic expectation maximization

Pattern recognition in multiband imagery using stochastic ex...

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conference on Optical Information Systems IV

作者： Elbakary, M. I. Alam, M. S. Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

ISBN: (纸本)0819463906

Hyperspectral sensors can facilitate automatic pattern recognition in cluttered imagery since man made objects often differ considerably from the natural background in absorbing and reflecting the radiation at various wavelengths i.e., the identification of the objects is based on spectral signature of the objects in the scene. In this paper, a unified approach for pattern recognition with known object signature is formulated by generating Gaussian mixture model to effectively utilize the underlying statistics of the data cube. To estimate the model parameters, enhanced version of the stochastic expectation maximization (SEM) algorithm is employed, which is also used successfully for image classification by reducing the unwanted information in the data cube. In the proposed scheme, at first we used the modified SEM to identify the different classes in the scene including the desired object class. Then, the Mahalanobis distance between the desired object signature and distributions of the mixture model is employed to detect the object class. Finally, the maximum a posteriori (MAP) probability for each pixel is estimated and Bayesian decision law is applied in order to isolate object pixels. The proposed algorithm has been tested using real life hyperspectral imagery and the results show that the algorithm shows robust performance in noisy environment.

关键词： pattern recognition SEM algorithm Gaussian mixture model remote sensing data

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Optimization of multisource information fusion for resource management with remote sensing imagery: An aggregate regularization method with neural network implementation

Optimization of multisource information fusion for resource ...

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conference on Signal processing, Sensor Fusion, and Target recognition XV

作者： Shkvarko, Yuriy Butenko, Sergiy CINVESTAV Unidad Guadalajara Av Cient 1145Col El Bajio Guadalajara 45010 Jalisco Mexico Texas A&M Univ Dept Ind Engn College Stn TX 77843 USA

ISBN: (纸本)0819462918

We address a new approach to the problem of improvement of the quality of multi-grade spatial-spectral images provided by several remote sensing (RS) systems as required for environmental resource management with the use of multisource RS data. The problem of multi-spectral reconstructive imaging with multisource information fusion is stated and treated as an aggregated ill-conditioned inverse problem of reconstruction of a high-resolution image from the data provided by several sensor systems that employ the same or different image formation methods. The proposed fusion-optimization technique aggregates the experiment design regularization paradigm with neural-network-based implementation of the multisource information fusion method. The maximum entropy (ME) requirement and projection regularization constraints are posed as prior knowledge for fused reconstruction and the experiment-design regularization methodology is applied to perform the optimization of multisource information fusion. Computationally, the reconstruction and fusion are accomplished via minimization of the energy function of the proposed modified multistate Hopfield-type neural network (NN) that integrates the model parameters of all systems incorporating a priori information, aggregate multisource measurements and calibration data. The developed theory proves that the designed maximum entropy neural network (MENN) is able to solve the multisource fusion tasks without substantial complication of its computational structure independent on the number of systems to be fused. For each particular case, only the proper adjustment of the MENN's parameters (i.e. interconnection strengths and bias inputs) should be accomplished. Simulation examples are presented to illustrate the good overall performance of the fused reconstruction achieved with the developed MENN algorithm applied to the real-world multi-spectral environmental imagery.

关键词： remote sensing maximum entropy reconstruction system fusion neural network resource management

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Extraction of spatial and spectral scene statistics for hyperspectral scene simulation - art. no. 63650X

Extraction of spatial and spectral scene statistics for hype...

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conference on image and Signal processing for remote sensing XII

作者： Kennett, Rosemary Sundberg, Robert L. Gruninger, John Haren, Raymond Spectral Sci Inc Burlington MA 01803 USA

ISBN: (纸本)0819464600

A method for extracting statistics from hyperspectral data and generating synthetic scenes suitable for scene generation models is presented. Regions composed of a general surface type with a small intrinsic variation, such as a forest or crop field, are selected. The spectra are decomposed using a basis set derived from spectra present in the scene and the abundances of the basis members in each pixel spectrum found. Statistics such as the abundance means, covariances and channel variances are extracted. The scenes are synthesized using a coloring transform with the abundance covariance matrix. The pixel-to-pixel spatial correlations are modeled by an autoregressive moving average texture generation technique. Synthetic reflectance cubes are constructed using the generated abundance maps, the basis set and the channel variances. Enhancements include removing any pattern from the scene and reducing the skewness. This technique is designed to work on atmospherically-compensated data in any spectral region, including the visible-shortwave infrared HYDICE and AVIRIS data presented here. Methods to evaluate the performance of this approach for generating scene textures include comparing the statistics of the synthetic surfaces and the original data, using a signal-to-clutter ratio metric, and inserting sub-pixel spectral signatures into scenes for detection using spectral matched filters.

关键词： scene statistics remote sensing hyperspectral multispectral scene simulation

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A pixel-weighting method for discriminating objects of different sizes in an image captured from a single camera

A pixel-weighting method for discriminating objects of diffe...

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3rd Canadian conference on Computer and Robot Vision, CRV 2006

作者： Mookyung, Park Namsu, Moon Sangrim, Ryu Jeongpyo, Kong Yongjin, Lee Wangjin, Mun S1 Corporation S1 Bldg. 168 Soonhwa-Dong Jung-Gu Seoul 100-130 Korea Republic of

ISBN: (纸本)0769525423

A novel method of pixel-weighting is proposed to calculate the size of a detected object in an image captured using a single camera, The calculated object size does not vary significantly regardless of the location of the object in an image, which allows it to be effectively utilized in a vision-based surveillance sensing algorithm as a meaningful feature for discriminating human intruders from other objects. Experimental results show the feasibility of the proposed method. © 2006 IEEE.

关键词： Object recognition

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conference reports: International Symposium on Systems and Control in Aerospace and Astronautics

Conference reports: International Symposium on Systems and C...

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The First International Symposium on Systems and Control in Aerospace and Astronautics (ISCAA 2006) was held in Harbin, China on 19-21 January 2006, on the campus of the Harbin Institute of Technology (HIT). The first day of the conference was devoted to plenary talks on technological topics relating to aerospace control. The second day focused presentations on space missions, spacecraft avionics, image and signal processing, modeling and identification, complex system theory, communications and navigation, fuzzy systems and fuzzy control, launch vehicle systems, intelligent control architectures, robust control, discrete event systems, digital communications, pattern recognition and neural networks, variable structure control, evolutionary computing, remote sensing, computer networks, antenna systems, computer vision, diagnostics, prognostics, and health managements, adaptive control, and unmanned aerial vehicles systems. The last day of the conference was devoted to a tour for all conference participants of the HIT Space Control and Inertial Technology Research Center.

关键词： Space applications

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Active polarimetric and multispectral laboratory demonstrator: contrast enhancement for target detection

Active polarimetric and multispectral laboratory demonstrato...

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conference on Electro-Optical remote sensing II

作者： Alouini, Mehdi Goudail, Francois Grisard, Arnaud Bourderionnet, Jerome Dolfi, Daniel Baarstad, Ivar Loke, Trond Kaspersen, Peter Normandin, Xavier Thales Res & Technol France RD128 F-91767 Palaiseau France Inst Opt F-91403 Orsay France Norsk Elektro Opt AS N-1471 Lorenskog Norway Thales Optron SA F-78283 Guyancourt France

ISBN: (纸本)9780819464941

A compact laboratory demonstrator providing both active polarimetric and multispectral images is designed. Its buildings blocks include, at emission part, a multi-wavelength optical parametric oscillator and, at the reception part, a polarimetric hyperspectral imager. Some of the results obtained with this system are illustrated and discussed. In particular, we show that a multispectral polarimetric image brings additional information on the scene, especially when interpreted in conjunction with its counterpart intensity image, since these two images are complementary in most cases. Moreover, although hyperspectral imaging might be mandatory for recognition of small targets, we evidence that the number of channels can be limited to a set of few wavelengths as far as target detection is considered.

关键词： active imaging polarimetric imaging multispectral imaging hyperspectral imaging image processing target detection

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