The influence of the measurement errors can be reduced using multi sensors fusion techniques. The competitive algorithms are one of the perspective class of sensor fusion (SF) algorithms, which are used in sensor fusi...
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ISBN:
(纸本)078037164X
The influence of the measurement errors can be reduced using multi sensors fusion techniques. The competitive algorithms are one of the perspective class of sensor fusion (SF) algorithms, which are used in sensor fusion techniques daring processing of sensor's measurements for receive more accurate measurement result than measurement results of each single sensor.
作者:
Keshava, NMIT
Lincoln Lab Lexington MA 02420 USA
In this paper, we explore the role of best bands algorithms in the context of maximizing the performance of hyperspectral algorithms. Specifically, we first focus on creating art intuitive framework for how metrics qu...
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ISBN:
(纸本)0780370414
In this paper, we explore the role of best bands algorithms in the context of maximizing the performance of hyperspectral algorithms. Specifically, we first focus on creating art intuitive framework for how metrics quantify the distance between two spectra. Focusing on the Spectral Angle Mapper (SAM) metric, we demonstrate how the separability of two spectra can be increased by choosing the bands that maximize the metric. This intuition about best bands analysis for SAM is extended to the Generalized Likelihood Ratio Test (GLRT) for a practical target/background detection scenario. Results are shown for a scene imaged by the HYDICE sensor demonstrating that the separability of targets and background can be increased by carefully choosing the bands for the test.
This paper analyzes the asymptotic performance of Maximum Likelihood (ML) channel estimation algorithms in wideband code division multiple access (WCDMA) scenarios. We concentrate on systems with periodic spreading se...
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ISBN:
(纸本)0780370414
This paper analyzes the asymptotic performance of Maximum Likelihood (ML) channel estimation algorithms in wideband code division multiple access (WCDMA) scenarios. We concentrate on systems with periodic spreading sequences (period larger than or equal to the symbol span) with high spreading factors, where the transmitted signal contains a code division multiplexed pilot for channel estimation purposes. Assuming randomized training and code sequences, we derive and compare the asymptotic covariances of the training-only (TO), semi-blind conditional ML (CML) and semi-blind Gaussian ML (GML) channel estimators.
In this paper, we bring local phase and multiresolution analysis to the texture segmentation problem. A Markov random field characterization is still employed, except it is used to model phase correlations rather than...
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ISBN:
(纸本)0780370414
In this paper, we bring local phase and multiresolution analysis to the texture segmentation problem. A Markov random field characterization is still employed, except it is used to model phase correlations rather than intensity correlations. Since statistical characteristics of phase are typically quite different to those of intensity, there exists the potential for creating greater discrimination in its feature space. We apply the Wreath Product Transform and use the phase at higher scales to initiate the segmentation process. For textures defined by homogeneous regions of dominant local edges, we see that the new algorithm yields better segmentation than that obtained through conventional multiresolution algorithms based on lowpass data.
We present a new multimodal system that combines stereoscopic and audio-based source localization to track the position of a flying bat. Also presented are novel algorithms for audio source localization. The bat was a...
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ISBN:
(纸本)0780370414
We present a new multimodal system that combines stereoscopic and audio-based source localization to track the position of a flying bat. Also presented are novel algorithms for audio source localization. The bat was allowed to fly in an anechoic room and monitored by two high-speed video cameras. The vocalizations of the bat were simultaneously recorded from six microphones. The data was then processed offline to localize the source and reconstruct the trajectory of the bat. We compare the performance of the localization algorithm with the position data obtained from stereoscopic pictures of the bat. The results confirm that the stereoscopic analysis and the audio localization are in good agreement. This system opens up new possibilities for performing multimodal research and developing more tightly integrated algorithms.
We present wavelet based video compression algorithms. The motion estimation and compensation, which is an essential part in the compression, is based on segment movements. The proposed based codec sequentially employ...
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ISBN:
(纸本)0780370414
We present wavelet based video compression algorithms. The motion estimation and compensation, which is an essential part in the compression, is based on segment movements. The proposed based codec sequentially employs the following steps: We first divide each frame in the sequence into blocks resulted from the block matching algorithm. The, we appply Hough transform, in order to group it into segments the blocks that have similar motion parameters. We estimate the motion parameters for each segment using several motion models and least-squares algorithm and apply motion compensation upon the frames in each group. In the wavelet domain an optimal vector bit allocation is being used to distribute the bit budget among consecutive frames. The manipulated frames in each group are quantized and coded using techniques from still image compression. The residual error of the compression is reduced by applying error correction in the wavelet domain to enhance the quality of the reconstructed sequence.
作者:
Tran, L.v.Lenz, R.Media Group
Dept. of Science and Engineering Linköping University Campus Norrköping 601-74 Norrköping Sweden
In many color based image retrieval systems the color properties of an image are described by the histogram of the colors in the image. Color histograms are insensitive to small object distortions and easy to compute....
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In many color based image retrieval systems the color properties of an image are described by the histogram of the colors in the image. Color histograms are insensitive to small object distortions and easy to compute. Histogram based search is however often inefficient for the large histogram @@@ needed to represent color distributions. Therefore we produce several new, PCA-based methods that provide efficient representations of color histograms and differences between two color histograms. We also investigate distance measures in the space of histograms which are defined by quadratic forms and which take into account the geometric structure of the underlying color space. We show that the combination of the quadratic forms based distance measure and the compression of the histogram information by difference based PCA-approximations provide new powerful and efficient retrieval algorithms for color based image retrieval.
This paper discusses several issues related to blind source separation in nonlinear models. Specifically, separability results show that separation in the general case is impossible, however, for specific nonlinear mo...
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ISBN:
(纸本)0780370414
This paper discusses several issues related to blind source separation in nonlinear models. Specifically, separability results show that separation in the general case is impossible, however, for specific nonlinear models the problem does have a solution. A specific set of parametric nonlinear mixtures is considered, this set has the Lie group structure. In the parameter set, a group operation is defined and a relative gradient is defined. The latter is applied to design stochastic algorithms for which the equivariance property is shown.
In recent years, there have been many researches being done throughout the world on the 3D image conversion of 2D image. However, 3D image conversion of 2D image has many problems on obtaining the optimal stereopsis. ...
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In recent years, there have been many researches being done throughout the world on the 3D image conversion of 2D image. However, 3D image conversion of 2D image has many problems on obtaining the optimal stereopsis. Stereopsis is dominated to relative position of several objects and depth information within image. Accordingly, in this paper, as a new adaptive scheme for stereoscopic image conversion of 2D image is suggested. Two input images acquired by Stereo Camera have different disparity information to each other. Disparity map, based on disparity information, presents mutually different occulusion region in the left/right image. These depend on the left view & right view and front & rear view of the virtual image plane. If arbitrary threshold values are applied to disparity map, we can get segmented objects from the input image. Using the principle of horizontal parallax, segmented objects are shifted with optimal screen disparity. In this case, we can improve stereopsis by differential shifting.
In this paper, the U.S. Air Force's Research Laboratory Space-Time Adaptive processing (RLSTAP) tool is used to demonstrate the impact of large sidelobe discretes on modem Synthetic Aperture Radar (SAR) signal and...
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ISBN:
(纸本)0819442658
In this paper, the U.S. Air Force's Research Laboratory Space-Time Adaptive processing (RLSTAP) tool is used to demonstrate the impact of large sidelobe discretes on modem Synthetic Aperture Radar (SAR) signal and imageprocessing. Sidelobe discretes may mask or even completely obscure weak target returns of interest in the immediate vicinity of these strong returns. Adaptive processing offers the potential to mitigate the effects of strong sidelobe discretes on image formation. In this paper, we characterize the severity of the problems caused by these discretes. RLSTAP can simulate high-fidelity airborne, spaceborne, or ground based multi-channel radar data in jamming and clutter environments, develop and evaluate new signal and imageprocessingalgorithms, and assess the performance of advanced radar systems. RLSTAP is a time domain simulation, updating object positions for every radar pulse and allowing modeling of realistic effects such as returns "walking" across range bins and Doppler filters. The site-specific clutter model uses terrain elevation and cover data to derive the line-of-site visibility, grazing angle, and clutter type for each range-angle cell. Spatial and temporal clutter statistics are applied to each cell and the signal strength at the receiver is calculated as a function of the backscatter coefficient, range, atmospheric attenuation, antenna gain, and system gains/losses. The scene generation capability in RLSTAP is unique in that it exploits Defense Terrain Elevation Data (DTED) and Land Use Land Cover Data (LULC) to create realistic clutter scenes (data cubes) for any given geographic location. As such, the application of adaptive multi-channel/multi-pulse processing to radar data that is characteristic of the area being imaged is now possible. Furthermore, the selection of waveform parameters, signal and imageprocessing techniques, and associated radar parameters may be improved upon.
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