Results 1  10
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16
Attributed scattering centers for SAR ATR
 IEEE Transactions on Image Processing
, 1997
"... Abstract — Highfrequency radar measurements of manmade targets are dominated by returns from isolated scattering centers, such as corners and flat plates. Characterizing the features of these scattering centers provides a parsimonious, physically relevant signal representation for use in automatic ..."
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Cited by 40 (5 self)
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Abstract — Highfrequency radar measurements of manmade targets are dominated by returns from isolated scattering centers, such as corners and flat plates. Characterizing the features of these scattering centers provides a parsimonious, physically relevant signal representation for use in automatic target recognition (ATR). In this paper, we present a framework for feature extraction predicated on parametric models for the radar returns. The models are motivated by the scattering behavior predicted by the geometrical theory of diffraction. For each scattering center, statistically robust estimation of model parameters provides highresolution attributes including location, geometry, and polarization response. We present statistical analysis of the scattering model to describe feature uncertainty, and we provide a leastsquares algorithm for feature estimation. We survey existing algorithms for simplified models, and derive bounds for the error incurred in adopting the simplified models. A model order selection algorithm is given, and an wary generalized likelihood ratio test is given for classifying polarimetric responses in spherically invariant random clutter. I.
Iterative tomographic image reconstruction using Fourierbased forward and back projectors
 IEEE Trans. Med. Imag
, 2004
"... Fourierbased reprojection methods have the potential to reduce the computation time in iterative tomographic image reconstruction. Interpolation errors are a limitation of Fourierbased reprojection methods. We apply a minmax interpolation method for the nonuniform fast Fourier transform (NUFFT) t ..."
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Cited by 23 (4 self)
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Fourierbased reprojection methods have the potential to reduce the computation time in iterative tomographic image reconstruction. Interpolation errors are a limitation of Fourierbased reprojection methods. We apply a minmax interpolation method for the nonuniform fast Fourier transform (NUFFT) to minimize the interpolation errors. Numerical results show that the minmax NUFFT approach provides substantially lower approximation errors in tomographic reprojection and backprojection than conventional interpolation methods.
Resampling of data between arbitrary grids using convolution interpolation
 IEEE Trans. Med. Imag
, 1999
"... Abstract—For certain medical applications resampling of data is required. In magnetic resonance tomography (MRT) or computer tomography (CT), e.g., data may be sampled on nonrectilinear grids in the Fourier domain. For the image reconstruction a convolutioninterpolation algorithm, often called grid ..."
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Cited by 19 (0 self)
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Abstract—For certain medical applications resampling of data is required. In magnetic resonance tomography (MRT) or computer tomography (CT), e.g., data may be sampled on nonrectilinear grids in the Fourier domain. For the image reconstruction a convolutioninterpolation algorithm, often called gridding, can be applied for resampling of the data onto a rectilinear grid. Resampling of data from a rectilinear onto a nonrectilinear grid are needed, e.g., if projections of a given rectilinear data set are to be obtained. In this paper we introduce the application of the convolution interpolation for resampling of data from one arbitrary grid onto another. The basic algorithm can be split into two steps. First, the data are resampled from the arbitrary input grid onto a rectilinear grid and second, the rectilinear data is resampled onto the arbitrary output grid. Furthermore, we like to introduce a new technique to derive the sampling density function needed for the first step of our algorithm. For fast, samplingpatternindependent determination of the sampling density function the Voronoi diagram of the sample distribution is calculated. The volume of the Voronoi cell around each sample is used as a measure for the sampling density. It is shown that the introduced resampling technique allows fast resampling of data between arbitrary grids. Furthermore, it is shown that the suggested approach to derive the sampling density function is suitable even for arbitrary sampling patterns. Examples are given in which the proposed technique has been applied for the reconstruction of data acquired along spiral, radial, and arbitrary trajectories and for the fast calculation of projections of a given rectilinearly sampled image. Index Terms—Arbitrary grids, convolution interpolation, density function, Voronoi diagram. I.
Overview of methods for image reconstruction from projections in emission computed tomography
 PROC. IEEE
, 2003
"... Emission computed tomography (ECT) is a technology for medical imaging whose importance is increasing rapidly. There is a growing appreciation for the value of the functional (as opposed to anatomical) information that is provided by ECT and there are significant advancements taking place, both in t ..."
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Cited by 17 (1 self)
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Emission computed tomography (ECT) is a technology for medical imaging whose importance is increasing rapidly. There is a growing appreciation for the value of the functional (as opposed to anatomical) information that is provided by ECT and there are significant advancements taking place, both in the instrumentation for data collection, and in the computer methods for generating images from the measured data. These computer methods are designed to solve the inverse problem known as “image reconstruction from projections.” This paper uses the various models of the data collection process as the framework for presenting an overview of the wide variety of methods that have been developed for image reconstruction in the major subfields of ECT, which are positron emission tomography (PET) and singlephoton emission computed tomography (SPECT). The overall sequence of the major sections in the paper, and the presentation within each major section, both proceed from the more realistic and general models to those that are idealized and application specific. For most of the topics, the description proceeds from the threedimensional case to the twodimensional case. The paper presents a broad overview of algorithms for PET and SPECT, giving references to the literature where these algorithms and their applications are described in more detail.
On An Offline Signature Verification System
 Proceedings of the 9th annual South African Workshop on Pattern Recognition
, 1998
"... We investigate the feasibility of using the Radon transform and a dynamic programming algorithm to authenticate handwritten signatures on checks. Since there no dynamic information is available as in the case of the online problem where signatures are typically captured by means of a digitising tabl ..."
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Cited by 8 (1 self)
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We investigate the feasibility of using the Radon transform and a dynamic programming algorithm to authenticate handwritten signatures on checks. Since there no dynamic information is available as in the case of the online problem where signatures are typically captured by means of a digitising tablet, the offline problem poses serious challenges. Our present system achieves an equal error rate of approximately 23% when only very high quality forgeries (skilled forgeries) are considered and an equal error rate of approximately 10% in the case of only casual forgeries. 1 Introduction Although handwritten signatures are by no means the most reliable means of personal identification, it remains one of the most widely acceptable means of personal identification. It is also non intrusive, inexpensive and one of the most commonly used personal identification systems. . A number of reasonably reliable online signature verification systems exist, see for example [9, 2]. These systems find p...
Image Reconstruction Techniques for PET
"... this report lies on the reconstruction of PET images. Therefore we start, in x2, with a statistical description of the PET measurement process. The algorithms used to reconstruct these images depend on the medical scanner and on the noise in the data. They are subdivided into three major groups. Ana ..."
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Cited by 2 (1 self)
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this report lies on the reconstruction of PET images. Therefore we start, in x2, with a statistical description of the PET measurement process. The algorithms used to reconstruct these images depend on the medical scanner and on the noise in the data. They are subdivided into three major groups. Analytical algorithms [2] are based on a continuous description of the image and the data. They formulate a continuous solution which is discretized before being implemented as a computer program. These algorithms assume that the measurement space has been uniformly sampled by the scanner and that the noise in the data can be neglected. Sometimes the available data do not satisfy these constraints, or sometimes the measurement space has been sampled too sparsely to obtain an adequate discretisation of the continuous solution. In these cases one needs to use iterative algorithms [3]. Iterative algorithms start from a discretized description of the image as a linear combination of a limited set of basis functions. They try to find the most appropriate weights according to the available data. Iterative algorithms are further subdivided into two groups, depending on whether or not the reconstruction is based on a statistical description of the measurement process. In x3 we are interested in the discretisation of images for the use of iterative reconstruction algorithms. We define constraints on the basis functions in the spatial and in the frequency domain. We find that for PET and CT spatially limited and for MRI frequency limited basis functions result in the most efficient implementations. For PET and CT we also find that the basis functions should decay as fast as possible in the frequency domain, and that for MRI the basis functions should decay as fast as possible in the spati...
Lower Bounds on the Mean Square Error in Emission Tomography for Different Image Approximations
, 1996
"... A lower bound on the mean square error (MSE) of image reconstruction in emission tomography is obtained and used in the evaluation of different image approximations. One component of the lower bound on the MSE is the Cram'erRao (CR) bound on the error variance. The CR bound for different image appr ..."
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Cited by 1 (0 self)
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A lower bound on the mean square error (MSE) of image reconstruction in emission tomography is obtained and used in the evaluation of different image approximations. One component of the lower bound on the MSE is the Cram'erRao (CR) bound on the error variance. The CR bound for different image approximations is derived by knowing how the CR bound is modified when one is interested in some functions of the model parameters. The other component of the lower bound on the MSE is the square of the bias. The study of the lower bound on the MSE for different image approximations is the study of the tradeoff between bias and error variance. It is shown that the relative contribution of the two components changes for different image approximations, total number of counts and emission densities. I. Introduction Accuracy and precision are important quality criteria in many engineering problems. They are also vital in emission tomography, where image quality is governed in part by the statistic...
Direct Fourier Tomographic Reconstruction ImagetoImage Filter Release 1.0
, 2007
"... We present an opensource ITK implementation of a direct Fourier method for tomographic reconstruction, applicable to parallelbeam xray images. Direct Fourier reconstruction makes use of the centralslice theorem to build a polar 2D Fourier space from the 1D transformed projections of the scanned ..."
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Cited by 1 (0 self)
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We present an opensource ITK implementation of a direct Fourier method for tomographic reconstruction, applicable to parallelbeam xray images. Direct Fourier reconstruction makes use of the centralslice theorem to build a polar 2D Fourier space from the 1D transformed projections of the scanned object, that is resampled into a Cartesian grid. Inverse 2D Fourier transform eventually yields the reconstructed image. Additionally, we provide a complex wrapper to the BSplineInterpolateImageFunction to overcome ITK’s current lack for image interpolators dealing with complex data types. A sample application is presented and extensively illustrated on the SheppLogan head phantom. We show that appropriate input zeropadding and 2DDFT oversampling rates together with radial cubic bspline interpolation improve 2DDFT interpolation quality and are efficient remedies to reduce reconstruction artifacts.
Algebraic Reconstruction Algorithms for Remote Sensing Image Enhancement
, 2000
"... by majority vote has been found to be satisfactory. ..."
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Cited by 1 (0 self)
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by majority vote has been found to be satisfactory.