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15th IEEE International conference on image Processing (ICIP 2008)

作者： Lo, v. L. Millane, R. P. Kingston, R. L. Univ Canterbury Computat Imaging Grp Dept Elect & Comp Eng Private Bag 4800 Christchurch 1 New Zealand Univ Auckland Sch Biolog Sci Auckland 92019 New Zealand

ISBN: (纸本)9781424417650

The envelope problem in macromolecular x-ray crystallography involves determining the boundary of a molecule from measurements of amplitudes of x-rays diffracted from a crystalline specimen. This represents a highly underdetermined image reconstruction problem with a large number of degrees of freedom. We regularize the problem by applying binary and connectivity constraints to the image, and seek the solution using the method of iterated projections. However, since the constraints are highly non-convex, the usual methods of generalized projections are not effective. We use the difference map projection algorithm and show that this is effective with simulated diffraction data from a protein envelope.

关键词： X-ray crystallography phase retrieval iterative projection algorithms image reconstruction

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The application of compressed sensing method in photoacoustic image reconstruction 4

The application of compressed sensing method in photoacousti...

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2014 4th IEEE International conference on Information Science and Technology, ICIST 2014

作者： Hu, Danfeng Wang, Jiajun Fang, Erxi Zhou, Wei Zhou, Yue School of Electronics and Information Soochow University Suzhou Jiangsu China

ISBN: (纸本)9781479948086

Full-scanned photoacoustic data of the sample are needed to achieve better quality of the reconstructed photoacoustic image with filtered back projection algorithm. However, such a requirement is usually difficult to be satisfied due to the restrictions of the hardware conditions and spatial size. To tackle such a problem, a compressed sensing based method was proposed to recover the full-scanned photoacoustic data from the incomplete measurements. The results from the numerical simulation demonstrates that both the mean squared error and the peak signal-to-noise ratio(PSNR) of the image can significantly improved with our proposed method. © 2014 IEEE.

关键词： image reconstruction

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Deconvolution in line scanners using a-priori information

Deconvolution in line scanners using a-priori information

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2nd conference on image reconstruction from incomplete data

作者： Wirnitzer, B Spraggon-Hernandez, T Univ Appl Sci Mannheim D-68163 Mannheim Germany

ISBN: (纸本)0819445592

In a digital camera the MTF of the optical system must comprise a low-pass filter in order to avoid aliasing. The MTF of incoherent imaging usually and in principle is far from an ideal low-pass. Theoretically a digital ARMA-Filter can be used to compensate for this drawback. In praxis such deconvolution filters suffer from instability because of time-variant noise and space-variance of the MTF. In addition in a line scanner the MTF in scan direction slightly differs in each scanned image. Therefore inverse filtering will not operate satisfactory in an unknown environment. A new concept is presented which solves both problems using a-priori information about an object, e.g. that parts of it are known to be binary. This information is enough to achieve a stable space and time-variant ARMA-deconvolution filter. Best results are achieved using non linear filtering and pattern feedback. The new method was used to improve the bit-error-rate (BER) of a high-density matrix-code scanner by more than one order of magnitude. An audio scanner will be demonstrated, which reads 12 seconds of music in CD-quality from an audio coded image of 18mmx55mm size.

关键词： image deconvolution decision feedback non-linear filter two dimensional adaptive filter

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Advanced photoacoustic image reconstruction using the k-Wave toolbox

Advanced photoacoustic image reconstruction using the k-Wave...

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conference on Photons Plus Ultrasound - Imaging and Sensing

作者： Treeby, B. E. Jaros, J. Cox, B. T. UCL Dept Med Phys & Biomed Engn London WC1E 6BT England Brno Univ Technol Fac Informat Technol CS-61090 Brno Czech Republic

ISBN: (纸本)9781628419429

Reconstructing images from measured time domain signals is an essential step in tomography-mode photoacoustic imaging. However, in practice, there are many complicating factors that make it difficult to obtain high-resolution images. These include incomplete or undersampled data, filtering effects, acoustic and optical attenuation, and uncertainties in the material parameters. Here, the processing and image reconstruction steps routinely used by the Photoacoustic Imaging Group at University College London are discussed. These include correction for acoustic and optical attenuation, spatial resampling, material parameter selection, image reconstruction, and log compression. The effect of each of these steps is demonstrated using a representative in vivo dataset. All of the algorithms discussed form part of the open-source k-Wave toolbox (available from http://***).

关键词： Signal attenuation image compression Acoustics image processing reconstruction algorithms visibility In vivo imaging Photoacoustic imaging 3D image reconstruction image filtering image quality Tomography

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PET image reconstruction from Finite Linogram via Direct Fourier and Logarithmic Barrier Method

PET Image Reconstruction from Finite Linogram via Direct Fou...

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IEEE Nuclear Science Symposium/Medical Imaging conference (NSS/MIC)/18th International Workshop on Room-Temperature Semiconductor X-Ray and Gamma-Ray Detectors

作者： Deng, Zhenzhou Xie, Qingguo Duan, Zhiwen Wuhan Natl Lab Optoelect Wuhan Hubei Peoples R China

ISBN: (纸本)9781467301206

Dual-head PET (Positron Emission Tomography) and PEM (Positron Emission Mammography) are encountered in many biological imaging and medical diagnosis applications. Since the data produced by flat-panel detectors are more closed to the linogram, and rebinning to the sinogram causes errors of the interpolation, image reconstruction based on the linogram is superior to keep the feature of the raw data for dual-head. Length of the linogram produced by actual PET or PEM systems is finite in practice. The projection views of the data are incomplete, and then the finite linogram reconstruction is a limited-view problem in mathematics. Conventional algorithms cannot achieve the exact reconstruction of the limited-view problem. In this work, we propose a half-analytic and half-iterative method named DF/LBM (Direct Fourier and Logarithmic Barrier Method) to solve the limited-view problem. The least square solution is obtained via DFM (Direct Fourier Method), and then a convex optimization method named logarithmic barrier method is employed to correct the least square solution. The substance of the convex optimization is defining the components in the null-space to satisfy some prior information, as the least square solution has no components in the null-space. Applying this method to Hoffman brain phantom, the artifact generated by the least square solution is eliminated, and PSNR is 90.2112, 94.8699 and 99.0507 when the tangent of the half allowable angle is 1.0, 1.5 and 2.0 respectively.

关键词： Barrier Contraception image reconstruction Logarithmic Finite Fourier sinogram Convex function optimization method

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Mining massively incomplete data sets by conceptual reconstruction 01

Mining massively incomplete data sets by conceptual reconstr...

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Proceedings of the Seventh ACM SIGKDD International conference on Knowledge Discovery and data Mining (KDD-2001)

作者： Aggarwal, Charu C. Parthasarathy, Srinivasan IBM T. J. Watson Research Center Yorktown Heights NY 10598 United States Ohio State university Columbus OH United States

ISBN: (纸本)158113391X

incomplete data sets have become almost ubiquitous in a wide variety of application domains. Common examples can be found in climate and image data sets, sensor data sets and medical data sets. The incompleteness in these data sets may arise from a number of factors: in some cases it may simply be a reflection of certain measurements not being available at the time;in others the information may be lost due to partial system failure;or it may simply be a result of users being unwilling to specify attributes due to privacy concerns. When a significant fraction of the entries are missing in all of the attributes, it becomes very difficult to perform any kind of reasonable extrapolation on the original data. For such cases, we introduce the novel idea of conceptual reconstruction, in which we create effective conceptual representations on which the data mining algorithms can be directly applied. The attraction behind the idea of conceptual reconstruction is to use the correlation structure of the data in order to express it in terms of concepts rather the original dimensions. As a result, the reconstruction procedure estimates only those conceptual aspects of the data which can be mined from the incomplete data set, rather than force errors created by extrapolation. We demonstrate the effectiveness of the approach on a variety of real data sets.

关键词： data mining

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RECOvERY OF SUBSPACE STRUCTURE from HIGH-RANK data WITH MISSING ENTRIES 26

RECOVERY OF SUBSPACE STRUCTURE FROM HIGH-RANK DATA WITH MISS...

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26th IEEE International conference on image Processing (ICIP)

作者： Carvalho, Joao Marques, Manuel Costeira, Joao P. Univ Lisbon Inst Super Tecn LARSyS Inst Syst & Robot Lisbon Portugal

ISBN: (纸本)9781538662496

We propose a method to reconstruct and cluster incomplete high-dimensional data lying in a union of low-dimensional subspaces. Exploring the sparse representation model, we jointly estimate the missing data while imposing the intrinsic subspace structure. Although we have a non-convex problem, we propose an algorithm robust to initialization. Extensive experiments with synthetic and real data show that our approach leads to significant improvements in the reconstruction and segmentation, outperforming current state of the art for both low and high-rank data.

关键词： Motion Segmentation Subspace Clustering Missing data Matrix Completion Sparse Representation

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MEGAlib - The Medium Energy Gamma-ray Astronomy Library

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NEW ASTRONOMY REvIEWS 2006年第7-8期50卷 629-632页

作者： Zoglauer, A. Andritschke, R. Schopper, F. Univ Calif Berkeley Space Sci Lab Berkeley CA 94720 USA Max Planck Inst Extraterr Phys D-37075 Garching Germany MPI Halbleiterlab Munich Germany

The Medium Energy Gamma-ray Astronomy Library MEGAlib is a set of software tools designed to analyze data of the next generation of Compton telescopes. The library comprises all necessary data analysis steps from data acquisition or simulation via event reconstruction to image reconstruction. (c) 2006 Elsevier B.v. All rights reserved.

关键词： gamma-ray telescopes and instrumentation data reduction techniques image processing

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Correlation-optics approach for holographic associative memories problem 15

Correlation-optics approach for holographic associative memo...

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15th International conference on Correlation Optics

作者： Bogatyryova, G., v Felde, Ch, v Natl Tech Univ Ukraine Kyiv Politech Inst Kiev Ukraine Chernivtsy Natl Univ Correlat Opt Dept Kiev Ukraine

ISBN: (纸本)9781510651296;9781510651289

The problem of holographic associative memory in the framework of the correlation-optical approach is discussed. Analysis of models of referenceless holograms and nonlinearly registered off-axis holograms, reconstructed in associative method, shows a wide range of useful properties of such holograms. Not only to reconstruct the missing part of the stored data set but also to detect small changes ("errors") in the recorded picture an array of data with error correction for an incomplete version of the array as well as for the implementation of high-performance heteroassociative reconstruction based on the non-interference mechanism of partial signals. It is shown that the visually assessed quality of the reconstructed associative response can approach the image quality achieved in conventional off-axis holography.

关键词： holography associative memory ghost image phase conjugation second-order holography

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Possible effects of misidentified mode number on Rayleigh wave inversion

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JOURNAL OF APPLIED GEOPHYSICS 2003年第1期53卷 17-29页

作者： Zhang, SX Chan, LS Univ Hong Kong Dept Earth Sci Hong Kong Hong Kong Peoples R China

Surface wave dispersion data obtained in field surveys are inherently incomplete. Poorly constrained dispersion curves and inclusion of data from higher-mode dispersion curves can be shown to produce erroneous inversion results. The present study evaluates the effects of cross-mode data mixing, and limited data and frequency range on inversion models. Multimodal dispersion curves were generated from synthetic velocity profiles using the forward modeling method. Subsets of the data points obtained by sampling the resulting dispersion curves using different sample intervals, frequency ranges, and by mixing fundamental-mode data with portion of the data from the higher-mode dispersion curves were inverted. The inversion results show that small sample intervals over a wide frequency range and an unambiguous identification of the fundamental-mode dispersion curve are essential factors for the reconstruction of accurate inversion models. The penetration range and accuracy of the inversion models are particularly sensitive to phase velocities at low frequencies of the dispersion curve. The theoretical results were tested with data from a roadbed survey in northern China. Ground model obtained from dispersion data derived by using the F-K method, which contained many cross-mode data points, was found to deviate substantially from the borehole record. A better agreement with the geotechnical record was obtained by inverse modeling of the dispersion data obtained from the fundamental-mode curve of the MASW spectral image. (C) 2003 Elsevier Science B.v. All tights reserved.

关键词： Rayleigh waves inversion cross-mode data mixing misfit analysis

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