This paper describes reconfigurable geometries for image sensors based on a concentric cartesian multiresolution lattice modified by four configuration parameters. They allow one, without moving the image sensor, to e...
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This paper describes reconfigurable geometries for image sensors based on a concentric cartesian multiresolution lattice modified by four configuration parameters. They allow one, without moving the image sensor, to examine any region of the field of view with the highest available resolution, as well as to select the acuity profile for the regions surrounding the fovea. The efficient processing of the multiresolution images obtained requires discrete shifts of fovea and rings whose magnitudes are calculated. Real time foveal images have been preprocessed and examples are given.
We applied a maximum likelihood expectation maximization (ML-EM) method to the reconstruction in coded aperture emission computed tomography (CECT) for the measurement of 3D distribution of a radioactive isotope, wher...
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We applied a maximum likelihood expectation maximization (ML-EM) method to the reconstruction in coded aperture emission computed tomography (CECT) for the measurement of 3D distribution of a radioactive isotope, where the projection data have a statistical fluctuation obeying a Poisson distribution (Poisson noise). The problem to be solved for CECT is to improve the depth resolution. We made some numerical simulations to confirm that the improvement of depth resolution and the reduction of noise were remarkable. For a point emitter at a distance of 35 cm from the aperture, the depth resolution was about 4 mm even when the average number of photons per pixel in the projection was 10. The quality of images for some 3D objects reconstructed by ML-EM was much better than that by conventional methods.
An accurate method recovering the 3D object function g(X,Y,D) from an image sequence of continuous focus series is proposed. Not only the depth map D(x,y) but also a pan-focused brightness map g/sub p/(X,Y) (a clear t...
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An accurate method recovering the 3D object function g(X,Y,D) from an image sequence of continuous focus series is proposed. Not only the depth map D(x,y) but also a pan-focused brightness map g/sub p/(X,Y) (a clear texture image observed by an ideal pinhole camera) are obtained. The depth map (2 1/2-D sketch) of the scene is evaluated by detecting that a distinct maximum of the point spread function exists in the focal plane. To estimate the maximum, a local variance of the brightness distribution is computed as a function of the focus location. A clear texture of the scene (object) is composed by collecting the brightness values from the respective focused 128 (or 256) frames. Reconstruction of the 3-D sketch is tested by mapping the texture on the depth map. The usefulness of a polarized filter is also demonstrated to recover an accurate depth map in the presence of specular reflection.
An orthogonal fitting technique for spline approximation is introduced. The technique takes into account the fact that there is uncertainty in both sides of the input-output relationship. In least squares (LS) spline ...
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An orthogonal fitting technique for spline approximation is introduced. The technique takes into account the fact that there is uncertainty in both sides of the input-output relationship. In least squares (LS) spline approximation a computationally costly iterative process is required to refine the parameterization such that the error is orthogonal to the signal. This process may be avoided by using the total LS (TLS) fitting in case the nature of the error in parameterization is random instead of systematic. A lower rank approximation of the signal may be used as an input to the spline fitting process. In particular, if adaptive parameterization based on distances among observations is used a more reliable parameterization can be obtained. The TLS technique yields a lower bias than LS fitting whereas the LS has a lower variance. However, the difference in variance is not significant.
A method to improve the quality of acoustic images obtained by systems based on beamforming is described. The specific goal is to eliminate two additive spurious terms present in the beam signals. The first effect is ...
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A method to improve the quality of acoustic images obtained by systems based on beamforming is described. The specific goal is to eliminate two additive spurious terms present in the beam signals. The first effect is due to side lobes and the second one is due to the nonlinear effects introduced by the modulus extractor present at the output of the beamformer. The relative importance of these two terms is assessed, showing that the term due to modulus extraction has a strong negative incidence on the final image quality. The Gaussian distribution of these spurious terms is discussed and verified in the case of punctiform scenes. Owing to the Gaussianity of the spurious terms, a method to eliminate them from the beam signals, based on higher order spectra analysis, is proposed, resulting in an evident image quality and reliability improvement.
This paper proposes a method for identifying and classifying a target from its foveal imagery using a neural network. The method39;s criterion for identifying a target is based on finding the global minimum of an en...
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This paper proposes a method for identifying and classifying a target from its foveal imagery using a neural network. The method's criterion for identifying a target is based on finding the global minimum of an energy function. This energy function is characterized by matching the candidate target and a library of target models at several levels of resolution of nonuniformly sampled foveal image data. For this purpose, a top-down and bottom-up (concurrent) matching procedure is implemented via a multi-layer Hopfield neural network. The corresponding energy function supports not only connections between cells at the same resolution level, but also interconnections between two sets of nodes at two different resolution levels. The proposed method also utilizes a feature analysis at the higher resolution levels of the target to relocate the center of the fovea to a more salient region of the target (gaze control). The results of an experimental scenario for foveal target recognition are presented.
This paper presents a unified algorithm of blind source separation based on the "Independent Component Analysis"(ICA) principle. The algorithm can separate all sources provided there is at most one Gaussian ...
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This paper presents a unified algorithm of blind source separation based on the "Independent Component Analysis"(ICA) principle. The algorithm can separate all sources provided there is at most one Gaussian distributed source. The key point is to find a matrix by which the estimates of the original signals are pairwise independent in the absence of noises. If the observed signals are corrupted by noises, minimum-variance unbiased estimates are obtained. In comparison with the algorithm proposed previously by the authors, this algorithm has a parallel pipeline structure, and will not need a preset threshold if both of the 3rd- and 4th-order cumulants of any non-Gaussian distributed source are not zero. This algorithm has significant advantages over existing algorithms.
A self-consistent model of coupling in an active twin-ridge waveguide coupler is presented, based on the beam propagation method. The coupler structure is assumed to be fabricated in double-heterostructure material wh...
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A self-consistent model of coupling in an active twin-ridge waveguide coupler is presented, based on the beam propagation method. The coupler structure is assumed to be fabricated in double-heterostructure material which is electrically pumped to provide distributed gain. Stimulated recombination in the active region perturbs the complex refractive index of the structure and this results in nonlinear coupling.
The K-distributed clutter is the product model of a texture variable. An ideal CFAR scheme enable the radar targets embedded in this clutter to be detected. The performance of the ideal CFAR defines an upper bound to ...
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The K-distributed clutter is the product model of a texture variable. An ideal CFAR scheme enable the radar targets embedded in this clutter to be detected. The performance of the ideal CFAR defines an upper bound to the detection probability in K-distributed clutter, but it is purely theoretical since the knowledge of the texture variable is not available in practice. In the present work, two estimators of the local texture value are derived based on the echoes received from the N range cells closest to the cell under test and use the estimated texture value to set the detection threshold. These two estimators distinguish from using or not some prior information about the texture distribution. By comparing the performances of the two estimators, the importance of the ideal CFAR is evaluated.
This paper deals with the control of battlefield radio communications. The particular properties of battlefield communications in modern warfare make a distributed access control highly desirable. Inputs for such a co...
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This paper deals with the control of battlefield radio communications. The particular properties of battlefield communications in modern warfare make a distributed access control highly desirable. Inputs for such a control are approximate descriptions of the status of the network. The control rules are heuristic because the controlled process does not have a set point. On the other hand, the network nodes have ample computing power that can be used to analyze the input and exercise access control algorithms. These circumstances suggest the use of fuzzy-logic control procedures. The author has developed such control procedures and tested their behavior on a computer model of battlefield communications.
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