作者：
BURT, PJImage Processing Laboratory
Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute Troy New York 12181
A common task in image analysis is that of measuring image properties within local windows. Often usefulness of these property estimates is determined by characteristics of the windows themselves. Critical factors inc...
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A common task in image analysis is that of measuring image properties within local windows. Often usefulness of these property estimates is determined by characteristics of the windows themselves. Critical factors include the window size and shape, and the contribution the window makes to the cost of computation, A highly efficient procedure for computing property estimates within Gaussian-like windows is described. Estimates are obtained within windows of many sizes simultaneously.
In this paper, the problem of multi-view embedding from different visual cues and modalities is considered. We propose a unified solution for subspace learning methods using the Rayleigh quotient, which is extensible ...
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In this paper, the problem of multi-view embedding from different visual cues and modalities is considered. We propose a unified solution for subspace learning methods using the Rayleigh quotient, which is extensible for multiple views, supervised learning, and nonlinear embeddings. Numerous methods including canonical correlation analysis, partial least square regression, and linear discriminant analysis are studied using specific intrinsic and penalty graphs within the same framework. Nonlinear extensions based on kernels and (deep) neural networks are derived, achieving better performance than the linear ones. Moreover, a novel multi-view modular discriminant analysis is proposed by taking the view difference into consideration. We demonstrate the effectiveness of the proposed multi-view embedding methods on visual object recognition and cross-modal image retrieval, and obtain superior results in both applications compared to related methods.
A new experimental method for determining the secondary electron yield for plasma exposed surfaces is described. From the measurement of the plasma condition and the total current generated when a voltage pulse is app...
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A new experimental method for determining the secondary electron yield for plasma exposed surfaces is described. From the measurement of the plasma condition and the total current generated when a voltage pulse is applied to a target material exposed to a plasma, the dependence of the secondary electron yield of that target on ion energy can be extracted. The secondary electron yield Is determined by an analytical model of the plasma ion, electron, and displacement currents. Experimental results for an aluminum target correlate well with previous secondary electron measurements which used a traditional technique, Secondary electrons yield data of other materials: single crystal silicon, aluminum, titanium nitride, and silicon dioxide are also extracted.
The inverse problem of reconstructing the resistivity of the earth, varying both laterally and with depth, from direct current measurements is considered. The problem is formulated as a multidimensional inverse scatte...
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The inverse problem of reconstructing the resistivity of the earth, varying both laterally and with depth, from direct current measurements is considered. The problem is formulated as a multidimensional inverse scattering problem and solved using a layer stripping algorithm. This algorithm recursively reconstructs the resistivity and electrical potential on horizontal planes of increasing depth by downward continuation. This is the first exact solution to the inverse resistivity problem for resistivity varying laterally as well as with depth. The algorithm is an extension of an algorithm proposed by Levy for resistivity varying in one dimension.
This paper describes the UIcluster software tool, which partitions expressed sequence tag (EST) sequences and other genetic sequences into "clusters" based on sequence similarity. Ideally, each cluster will ...
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A 1.5V resistive fuse for image smoothing and segmentation using bulk-driven MOSFETs is presented. The circuit switches on only if the differential voltage applied across its input terminals is less than a set voltage...
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A 1.5V resistive fuse for image smoothing and segmentation using bulk-driven MOSFETs is presented. The circuit switches on only if the differential voltage applied across its input terminals is less than a set voltage;it switches off if the differential voltage is higher than the set value. The useful operation range of the circuit is 0.4V with a supply voltage of 1.5V and threshold voltages of V-Tn = 0.828V and V-Tp = -0.56V for n and g channel MOSFETs, respectively.
A fast algorithm for recovering profiles of density and compressional (P) and shear-vertical (SV) wave speeds as functions of depth for the inverse seismic problem in a continuous layered elastic medium is obtained. T...
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A fast algorithm for recovering profiles of density and compressional (P) and shear-vertical (SV) wave speeds as functions of depth for the inverse seismic problem in a continuous layered elastic medium is obtained. This algorithm differs from previous fast algorithms for this problem since it requires only the compressional wave P-P reflection response at the surface of the medium, for three different slownesses or angles of incidence. Previous algorithms have required shear stress data in the form of the P-SV and SV-SV reflection responses, making them unsuitable for an ocean environment. This algorithm is thus much more suitable for reconstructing the ocean floor from pressure data taken in the ocean. The algorithm is exact, and it includes the effects of multiple reflections and mode conversions. A computer run illustrates the performance of the algorithm on synthetic data.
Increasingly, feedback of measured run-time information is being used in the optimization of computation execution. Because of this, the need for a model relating the static view of a computation to its runtime varian...
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Several state-of-the-art mathematical models useful in image processing are considered. These models include the traditional fast unitary transforms, autoregessive and state variable models as well as two-dimensional ...
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Several state-of-the-art mathematical models useful in image processing are considered. These models include the traditional fast unitary transforms, autoregessive and state variable models as well as two-dimensional linear prediction models. These models introduced earlier [51], [52] as low-order finite difference approximations of partial differential equations are generalized and extended to higher order in the framework of linear prediction theory. Applications in several image processing problems, including image restoration, smoothing, enhancement, data compression, spectral estimation, and filter design, are discussed and examples given.
The popular class of synchronizers that consist of a quadratic nonlinearity followed by a phase-lock loop is investigated, and it is shown that the optimum design of the quadratic transformation is characterized in te...
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The popular class of synchronizers that consist of a quadratic nonlinearity followed by a phase-lock loop is investigated, and it is shown that the optimum design of the quadratic transformation is characterized in terms of a spectral correlation function for the signal to be synchronized to. It is also shown that the SNR performance of this quadratic transformation, and the mean-square phase jitter of the phaselock loop are both characterized in terms of spectral correlation functions. The conditions under which the optimum quadratic transformations, for symbol synchronization of BPSK, QPSK, SQPSK, and MSK, and for carrier synchronization of BPSK, reduce to the well-known matched-filter-squarer are identified. In addition, the well-known zeromean-square-phase-jitter condition is generalized from PAM to all synchronizable signals, and is characterized in terms of the spectral correlation function. The low-SNR maximum-likelihood synchronizer for all quadratically synchronizable signals is characterized in terms of a multiplicity of maximum-SNR quadratic spectral-line generators. A closed form implementation in terms of a matched filter, squarer, and symbol-rate-synchronized averager is obtained for BPSK and QPSK signals.
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