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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012"

共 282 条记录，以下是211-220 订阅

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Reduced memory multiscale fusion for combined topographic and bathymetric data

Reduced memory multiscale fusion for combined topographic an...

引用

Conference on multisensor, multisource information fusion

作者： Cheung, S Jhee, H Slatton, KC Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

ISBN: (纸本)0819457981

The multiscale Kalman smoother (MKS) is a globally optimal estimator for fusing remotely sensed data. The MKS algorithm can be readily parallelized because it operates on a Markov tree data structure. However, such an implementation requires a large amount of memory to store the parameters and estimates at each scale in the tree. This becomes particularly problematic in applications where the observations have very different resolutions and the finest scale data are sparse or aggregated. Such cases commonly arise when fusing data to capture both regional and local structure. In this work, we develop an efficient MKS algorithm and apply it to the fusion of topographic and bathymetric elevation data.

关键词： data fusion multiscale estimation topography and bathymetry

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Architecture of triple sensitive colour digital sensors with the integration of image fusion techniques

Architecture of triple sensitive colour digital sensors with...

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Conference on multisensor, multisource information fusion

作者： Zhang, Y Univ New Brunswick Dept Geodesy & Geomat Engn Fredericton NB E3B 5A3 Canada

ISBN: (纸本)0819457981

High resolution and highly sensitive colour digital sensors are desired for many applications, including military and civilian missions. Due to the limitation of spectral bandwidth, the sensitivity of a digital colour sensor is usually three times lower than that of a digital panchromatic sensor with a spectral bandwidth of the entire visible range or a range from visible to near infrared. This paper introduces a conceptual architecture for producing a triple sensitive colour digital frame sensor. Automatic image fusion techniques are involved to integrate colour and panchromatic images to increase the sensitivity of the colour sensor. Available satellite colour and panchromatic images are tested to prove the concept. The test results demonstrate that the introduced architecture is promising for developing real triple sensitive colour digital sensors.

关键词： digital sensor colour high sensitivity high resolution image fusion

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Effect of algorithm fusion and aggregation methodologies on the performance of a corrosion detection algorithm

Effect of algorithm fusion and aggregation methodologies on ...

引用

Conference on multisensor, multisource information fusion

作者： Nelson, BN Slebodnick, P Groeninger, W Lemieux, EJ GEO CENTERS INC Newton Ctr MA 02459 USA

ISBN: (纸本)0819457981

Over the last several years, the Naval Research Laboratory has been developing corrosion detection algorithms for assessing coatings conditions in tank and voids on US Navy Ships. The corrosion detection algorithm is based on four independent algorithms;two edge detection algorithms, a color algorithm and a grayscale algorithm. Of these four algorithms, the color algorithm is the key algorithm and to some extent drives overall algorithm performance. The four independent algorithm results are fused with other features to first generate an image level assessment of coatings damage. The image level results are next aggregated across a tank or void image set to generate a single coatings damage value for the tank or void being inspected. The color algorithm, algorithm fusion methodology and aggregation algorithm components are key to the overall performance of the corrosion detection algorithm. This paper will describe modifications that have been made in these three algorithm components to increase the corrosion detection algorithmis overall operating range, to improve the algorithmis ability to assess low coatings damage and to improve the accuracy of coatings damage classification at both the individual image as well as at the whole tank level.

关键词： information fusion image processing algorithm fusion corrosion detection algorithms

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Multispectral sensor fusion using the projection-slice theorem

Multispectral sensor fusion using the projection-slice theor...

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Conference on multisensor, multisource information fusion

作者： Riasati, VR Ro, S Sci Applicat Int Corp San Diego CA 92121 USA

ISBN: (纸本)0819457981

In this paper we discuss the utilization of the Projection-Slice Theorem, PST, to reduce a data set that display each multiple spectral band representation of an image and to extract variant features from those representation. Noise is removed from each of the one-dimensional projections of the images via PST and a wavelet transform thresholding process. The extracted features emphasize differences in spectral information from the same image and are combined through synthesis via the inverse PST. This sensor fusion method facilitates the design of filters to recognize an image with characteristics similar to the relevant features from each of the bands that have been incorporated in a combined multispectral/fused image. We present our method of feature extraction, wavelet noise removal, and data synthesis.

关键词： projection-slice theorem wavelet transforms data fusion multispectral components

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Using correlation-based measures to select classifiers for decision fusion

Using correlation-based measures to select classifiers for d...

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Conference on multisensor, multisource information fusion

作者： Goebel, K Yan, WZ GE Global Res Ctr Niskayuna NY 12309 USA

ISBN: (纸本)0819457981

This paper explores classifier fusion problems where the task is selecting a subset of classifiers from a larger set with the goal to achieve optimal performance. To aid in the selection process we propose the use of several correlation-based diversity measures. We define measures that capture the correlation for n classifiers as opposed to pairs of classifiers only. We then suggest a sequence of steps in selecting classifiers. This method avoids the exhaustive evaluation of all classifier combinations which can become very large for larger sets of classifiers. We then report on observations made after applying that method to a data set from a real-world application. The classifier set chosen achieves close to optimal performance with a drastically reduced set of evaluation steps.

关键词： classification diversity correlation accuracy decision fusion

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A perceptual quality metric for image fusion based on regional information

A perceptual quality metric for image fusion based on region...

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Conference on multisensor, multisource information fusion

作者： Chen, H Varshney, PK Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819457981

Comparative evaluation of fused images is a critical step to evaluate the relative performance of different image fusion algorithms. Human visual inspection is often used to assess the quality of fused images. In this paper, we propose some variants of a new image quality metric based on the human vision system (HVS). The proposed measures evaluate the quality of a fused image by comparing its visual differences with the source images and require no knowledge of the ground truth. First, the images are transformed to the frequency domain. Second, the difference between the images in frequency domain is weighted with a human contrast sensitivity function (CSF). Finally, the quality of a fused image is obtained by computing the MSE of the weighted difference images obtained from the fused image and source images. Our experimental results show that these metrics are consistent with perceptually obtained results.

关键词： image fusion image quality measure human vision system(HVS) contrast sensitivity function (CSF)

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Add prior knowledge to speaker recognition

Add prior knowledge to speaker recognition

引用

Conference on multisensor, multisource information fusion

作者： Li, DD Yang, YC Wu, ZH Huang, T Zhejiang Univ Dept Comp Sci & Tech Hangzhou 310027 Peoples R China

ISBN: (纸本)0819457981

Prior knowledge helps to make the speaker recognition system more reliable and robust. This paper presents a uniform framework of feature-level fusion to incorporate the prior knowledge for speaker recognition using gender information based on dynamic Bayesian network (DBN). DBNs are a new statistical approach, with the ability to handle hidden variables and missing data in a principled way with high extensibility. And thus, DBNs can describe the prior knowledge conveniently. Our contribution is to apply DBNs to construct a general feature-level fusion to combine the general acoustic feature like MFCC and prior information like gender into a single DBN for speaker identification. In our framework, gender information become additional observed data to influence both hidden variables and observed acoustic data. Experimental evaluation over a subnet of YOHO corpus show promising results.

关键词： feature-level fusion DBN prior knowledge gender

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Evaluating algorithmic techniques in supporting situation awareness

Evaluating algorithmic techniques in supporting situation aw...

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Conference on multisensor, multisource information fusion

作者： Salerno, J Blasch, E Hinman, M Boulware, D USAF AFRL IFEA Res Lab Rome NY 13440 USA

ISBN: (纸本)0819457981

How well does an algorithm support its purpose and user base? Has automation provided the user with the ability to augment their production, quality or responsiveness? In a number of systems today these questions can be answered by either Measures of Performance (MOP) or Measures of Effectiveness (MOE). However, the fusion community has not yet developed sufficient measures and has only recently devoted a concerted effort to address this deficiency. In this paper, we will summarize work in metrics for the lower levels of fusion (object ID, tracking, etc) and discuss whether these same metrics still apply to the higher levels (Situation Awareness), or if other approaches are necessary. We conclude this paper with a set of future activities and direction.

关键词： situation awareness metrics evaluation precision recall misassignment rate evidence recall cost utility timeliness data to information ratio

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Reduced data projection slice image fusion using principal component analysis

Reduced data projection slice image fusion using principal c...

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Conference on multisensor, multisource information fusion

作者： Riasati, VR Zhou, H Sci Applicat Int Corp San Diego CA 92121 USA

ISBN: (纸本)0819457981

In this paper we discuss the utilization of Principal Component Analysis, PCA, with projection slice synthetic discriminant function (PSDF) filters to reduce a data set that represents images from different sensor systems in order to extract relative information and features from the image set. The PCA helps to emphasize the differences in each of the training images in a given class. These differences are encoded into the PSDF filters. The PSDF filters provide a premise for data fusion by utilization of the projection-slice theorem. The PSDF is implemented with a few training images generated from the PCA, containing relevant information from all of the training images. The data in the principle components that are used to represent the entire data set can be emphasized by conditioning the eigen-values of the basis vectors used to corroborate important data packets in the entire data set. ne method of data fusion, and preferred data emphasis in conjunction with the PST is discussed and the fused images are presented.

关键词： sensor fusion projection slice theorem principal component analysis synthetic discriminant functions

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A controllable sensor management algorithm capable of learning

A controllable sensor management algorithm capable of learni...

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Conference on multisensor, multisource information fusion

作者： Osadciw, L Veeramacheneni, K Syracuse Univ Syracuse NY 13244 USA

ISBN: (纸本)0819457981

Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network's operation as deter-mined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.

关键词： sensor networks sensor management data fusion swarm algorithms Bayesian networks

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