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conference on image reconstruction from incomplete data IV

作者： Testorf, Markus E. Fiddy, Michael Dartmouth Coll Thayer Sch Engn 8000 Cummings Hall Hanover NH 03755 USA Univ N Carolina Ctr Optoelect & Opt Commun Charlotte NC USA

ISBN: (纸本)0819463957

A method is described for reconstructing images from incomplete data sets if subsets of the data are obtained with different data acquisition systems. The proposed method is able to incorporate prior information about the object into the reconstruction process. The general scheme is applied to construct improved images from multiple low resolution frames of the same scene, where each frame is obtained with an imaging system characterized by a different response function. The working principle is demonstrated with synthetic data for a set of generic imaging systems. Additional attention is given to the potential of the inherent superresolution capabilities of this method in the context of compressed image representations.

关键词： computational imaging resolution enhancement image reconstruction multiple image frames

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Generalized support constraint for three-dimensional reconstruction from incomplete Fourier spectra

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JOURNAL OF ELECTRONIC IMAGING 1997年第4期6卷 426-438页

作者： Payot, E Preteux, FJ Trousset, Y Guillemaud, R CEA LETI DSYS F-38054 Grenoble 9 France Inst Natl Telecommun F-91011 Evry France G E Med Syst F-78533 Buc France

Many imaging systems involve a loss of information that requires the incorporation of prior knowledge in the restoration/reconstruction process. We focus on the typical case of 30 reconstruction from an incomplete set of projections. An approach based an constrained optimization is introduced This approach provides a powerful mathematical framework for selecting a specific solution from the set of feasible solutions;this is done by minimizing some criteria depending on prior densitometric information that can be interpreted through a generalized support constraint. We propose a global optimization scheme using a deterministic relaxation algorithm based on Bregman's algorithm associated with half-quadratic minimization techniques. When used for 30 vascular reconstruction from 2D digital subtracted angiography (DSA) data, such an approach enables the reconstruction of a well-contrasted 30 vascular network in comparison with results obtained using standard algorithms. (C) 1997 SPIE and IS&T.

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Dictionary Learning from incomplete data for Efficient image Restoration 25

Dictionary Learning from Incomplete Data for Efficient Image...

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25th European Signal Processing conference (EUSIPCO)

作者： Naumova, Valeriya Schnass, Karin Simula Res Lab Sect Comp & Software Martin Linges 25 Fornebu Norway Univ Innsbruck Dept Math Technikerstr 13 A-6020 Innsbruck Austria

ISBN: (纸本)9780992862671

In real-world image processing applications, the data is high dimensional but the amount of high-quality data needed to train the model is very limited. In this paper, we demonstrate applicability of a recently presented method for dictionary learning from incomplete data, the so-called Iterative Thresholding and K residual Means for Masked data, to deal with high-dimensional data in an efficient way. In particular, the proposed algorithm incorporates a corruption model directly at the dictionary learning stage, also enabling reconstruction of the low-rank component again from corrupted signals. These modifications circumvent some difficulties associated with the efficient dictionary learning procedure in the presence of limited or incomplete data. We choose an image inpainting problem as a guiding example, and further propose a procedure for automatic detection and reconstruction of the low-rank component from incomplete data and adaptive parameter selection for the sparse image reconstruction. We benchmark the efficacy and efficiency of our algorithm in terms of computing time and accuracy on colour, 3D medical, and hyperspectral images by comparing it to its dictionary learning counterparts.

关键词： image reconstruction

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image reconstruction using symmetry

Image reconstruction using symmetry

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conference on image reconstruction from incomplete data VI

作者： Lo, V. L. Millane, R. P. Univ Canterbury Dept Elect & Comp Engn Computat Imaging Grp Christchurch 1 New Zealand

ISBN: (纸本)9780819482969

Symmetry provides a source of redundancy which can be exploited in image reconstruction. In particular, internal symmetries in molecules can help to compensate for the loss of Fourier phase information in macromolecular x-ray crystallography. Symmetry projections are incorporated into iterative projection algorithms for reconstruction of macromolecular electron densities from x-ray diffraction amplitudes from crystals. The effects of interpolation are studied and the algorithms are applied to reconstruction of an icosahedral virus.

关键词： image reconstruction symmetry x-ray crystallography phase retrieval

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Three-dimensional image reconstruction in variable density acoustic tomography

Three-dimensional image reconstruction in variable density a...

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conference on image reconstruction from incomplete data IV

作者： Anastasio, Mark A. Shi, Daxin IIT Dept Biomed Engn Chicago IL 60616 USA

ISBN: (纸本)0819463957

Diffraction tomography (DT) is an established imaging technique for use with diffracting wavefields, which represents a generalized form of x-ray tomography. In this work, we revisit the three-dimensional reconstruction problem of DT for variable density acoustic media. Novel reconstruction algorithms are developed for reconstructing separate images that depict a weakly scattering object's compressibility and density variations. If tomographic measurement data are acquired at four distinct temporal frequencies, we demonstrate that the effects of object dispersion can be accounted for completely by use of analytic reconstruction formulas. Computer-simulation studies are conducted to demonstrate the developed image reconstruction methods.

关键词： ultrasound tomography acoustic dispersion diffraction tomography image reconstruction

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Research on improved image reconstruction algorithms of OCT based on incomplete projection data - art. no. 68321H

Research on improved image reconstruction algorithms of OCT ...

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conference on Holography and Diffractive Optics III

作者： Tang, Xiaochun Gao, Yiqing Nanchang Hangkong Univ Minist Educ China Key Lab Nondestruct Test Nanchang 330063 Jiangxi Peoples R China

ISBN: (纸本)9780819470072

In order to improve the quality and solve the problem of low speed of image reconstruction in the traditional optical computerized tomography (OCT) when the data acquired is incomplete projection, the multiple constrained of genetic algorithm based on algebraic iterative was proposed. Generally speaking, under the condition of multiple-objective optimization, the common extreme point for all the objective functions doesn't exist. So we can achieve the preferable compromise in the contradictions of multiple objectives. In this article, there are three constrained conditions. The first one is the maximum entropy criterion which is used mostly to solve the problem of OCT image reconstruction when the data acquired is incomplete projection recently. The second one is the minimum criteria of peak value which is introduced to suppress noise effectively and ensure the gliding property of the image reconstruction, because of the first one leading to noise amplification during the iterative process. The last constrained condition is the minimum criteria of the difference between the projection again of image reconstruction and the original projection. The concept of penalize-function is introduced into the genetic algorithm, which would transform the constrained optimization problem to unconstrained. It is clearly demonstrated from the experiment results that the algorithm reconstruction technique can efficiently improve the quality of images reconstruction of the incomplete projection data.

关键词： incomplete projection data image reconstruction multiple constrained genetic algorithm

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3D image reconstruction algorithms for cryo electron microscopy images of virus particles

3D image reconstruction algorithms for cryo electron microsc...

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conference on image reconstruction from incomplete data

作者： Doerschuk, PC Johnson, JE Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

A statistical model for the object and the complete image formation process in cryo electron microscopy of viruses is presented. Using this model, maximum likelihood reconstructions of the 3D structure of viruses are ... 详细信息

ISBN: (纸本)0819437689

关键词： cryo electron microscopy expectation-maximization algorithm statistical inverse problems viruses

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Continuous Surface Fitting to Spatial Optical Interferometer data

Continuous Surface Fitting to Spatial Optical Interferometer...

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conference on image reconstruction from incomplete data VI

作者： Rasheed, Sarbast Hajian, Arsen R. Tycner, Christopher Vu, Linda Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada Cent Michigan Univ Dept Phys Mt Pleasant MI 48859 USA

ISBN: (纸本)9780819482969

In this paper, we describe a practical implementation of an image reconstruction method designed to generate a map of the brightness distribution from data consisting of squared visibilities and complex closure amplitudes resulting from observations of an astronomical target with a broadband, multichannel, spatial optical interferometer. Given the data, the method estimates the true brightness distribution with a model sampled on a rectangular grid of discrete positions on the sky with the assumption that the model intensities in the region not defined by the discrete positions being described by bilinear interpolation of the discrete intensities. The developed image reconstruction method has been applied to real observational data obtained from existing optical interferometer facilities.

关键词： image reconstruction modelling optical interferometry optimization

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image reconstruction by Phase Retrieval with Transverse Translation Diversity

Image Reconstruction by Phase Retrieval with Transverse Tran...

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conference on image reconstruction from incomplete data V

作者： Guizar-Sicairos, Manuel Fienup, James R. Univ Rochester Inst Opt Rochester NY 14627 USA

ISBN: (纸本)9780819472960

Measuring a series of far-field intensity patterns from an object, taken after a, transverse translation of the object with respect to a known illumination pattern, has been shown to make the problem of image reconstruction by phase retrieval much more robust. However, previously reported reconstruction algorithms [Phys. Rev. Lett. 93, 023903 (2004)] rely oil an accurate knowledge of the translations and illumination pattern for a successful reconstruction. We developed a nonlinear optimization algorithm that allows optimization over the translations and illumination pattern, dramatically improving the reconstructions if the system parameters are inaccurately known [Opt. Express 16, 7264 (2008)]. In this paper we compare reconstructions obtained with these algorithms under realistic experimental scenarios.

关键词： Phase retrieval image reconstruction techniques inverse scattering coherent x-ray imaging

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3-D signal reconstruction from noisy projection data for stochastic objects as a generalization of Gaussian mixture parameter estimation

3-D signal reconstruction from noisy projection data for sto...

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conference on image reconstruction from incomplete data VI

作者： Zheng, Yili Doerschuk, Peter C. Univ Calif Berkeley Lawrence Berkeley Lab Computat Res Div Berkeley CA 94720 USA

A statistical estimation problem for determining 3-D reconstructions from a single 2-D projection image of each of multiple objects when the objects are heterogeneous is described. The method is based on a Gaussian mi... 详细信息

ISBN: (纸本)9780819482969

关键词： statistical inverse problem statistical signal reconstruction tomography cryo electron microscopy virus structure

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