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检索条件"任意字段=Conference on Image Reconstruction from Incomplete Data V"

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Sampling, radiometry, and image reconstruction for polar and geostationary meteorological remote sensing systems

Sampling, radiometry, and image reconstruction for polar and...

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2nd conference on image reconstruction from incomplete data

作者： Abrams, MC Cain, SC ITT Industries Inc. (United States) Indiana Univ.-Purdue Univ./Fort Wayne (United States)

ISBN: (纸本)0819445592

In this paper, a Bayesian-based image reconstruction scheme is utilized for estimating a high resolution temperature map of the top of the earth's atmosphere using the GOES-8 (Geostationary Operational Environmental Satellite) imager infrared channels. By simultaneously interpolating the image while estimating temperature, the proposed algorithm achieves a more accurate estimate of the sub-pixel temperatures than could be obtained by performing these operations independently of one another. The proposed algorithm differs from other Bayesian-based image interpolation schemes in that it estimates brightness temperature as opposed to image intensity and incorporates a detailed optical model of the GOES multi-channel imaging system. The temperature estimation scheme is compared to deconvolution via pseudo-inverse filtering using two metrics. One metric is the mean squared temperature error. This metric describes the radiometric accuracy of the image estimate. The second metric is the recovered Modulation Transfer Function (MTF) of the image estimate. This method has traditionally been used to evaluate the quality of image recovery techniques. It will be shown in this paper that there is an inconsistency between these two metrics in that an image with high spatial frequency content can be reconstructed with poor radiometric, accuracy. The ramifications of this are discussed in order to evaluate the two metrics for use in quantifying the performance of image reconstruction algorithms.

关键词： Imaging systems image restoration reconstruction algorithms Sensors image resolution Modulation transfer functions Radiometry data modeling Satellite imaging Satellites

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Super-resolution in image restoration of wide area images viewed through atmospheric turbulence

Super-resolution in image restoration of wide area images vi...

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2nd conference on image reconstruction from incomplete data

作者： Lambert, A Fraser, D Jahromi, MRS Hunt, BR Univ New S Wales Univ Coll Kensington NSW 2033 Australia

ISBN: (纸本)0819445592

We postulate that under anisoplanatic imaging conditions involving imaging through turbulent media over a wide-area there exists the possibility of spatial frequency content that is normally lost outside the aperture of an imaging instrument under unperturbed viewing conditions, being aliased into the aperture. Simulation is presented that reinforces this premise. We apply restoration algorithms that were designed to correct non-uniform distortions, to a real image sequence to the effect of noticing the de-aliased super-frequency content. We claim this to be super-resolution, and that it is only possible under anisoplanatic imaging scenarios, where the point spread function of the image is position dependent as a result of the atmospheric turbulence.

关键词： wide-area image restoration super-resolution surveillance imaging astronomical imaging

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Fast segmentation method for SAR images

Fast segmentation method for SAR images

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2nd conference on image reconstruction from incomplete data

作者： Bratsolis, E Sigelle, M Ecole Natl Super Telecommun Bretagne Dept Traitement Signal & Images F-75013 Paris France

ISBN: (纸本)0819445592

An iterative optimization algorithm which can be used for speckle reduction and segmentation of synthetic aperture radar (SAR) images is presented here. This method contains as a first step a fast restoration and as a second one the segmentation. We have worked in 3-look simulated and real ERS-1 amplitude images. The iterative filter is based on a membrane model Markov random field (MRF) approximation optimized by a synchronous local iterative method (SLIM). The final form of restoration gives a total sum preserving regularization (TSPR).

关键词： image segmentation speckle reduction restoration Markov random field (MRF) synchronous local iterative method (SLIM) synthetic aperture radar (SAR) total sum preserving regularization (TSPR)

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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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Multi-frame blind deconvolution and bispectrum processing of atmospherically-degraded data: a comparison

Multi-frame blind deconvolution and bispectrum processing of...

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2nd conference on image reconstruction from incomplete data

作者： Matson, CL Schulze, KJ Billings, P Tyler, DW Directed Energy Directorate/Air Force Research Lab. (United States) KJS Consulting (United States) Textron Systems Corp. (United States) Univ. of New Mexico (United States)

ISBN: (纸本)0819445592

We analyze the quality of reconstructions obtained when using the multi-frame blind deconvolution (MFBD) algorithm and the bispectrum algorithm to reconstruct images from atmospherically-degraded data that are corrupted by detector noise. In particular, the quality of reconstructions is analyzed in terms of the fidelity of the estimated Fourier phase spectra. Both the biases and the mean square phase errors of the Fourier spectra estimates are calculated and analyzed. The reason that the comparison is made by looking at the Fourier phase spectra is because both the MFBD and bispectrum algorithms can estimate Fourier phase information from the image data itself without requiring knowledge of the system transfer function, and because Fourier phase plays a dominant role in image quality. Computer-simulated data is used for the comparison in order to be able to calculate true biases and mean square errors in the estimated Fourier phase spectra. For the parameters in this study, the bispectrum algorithm produced less-biased phase estimates in all cases than the MFBD algorithm. The MFBD algorithm produced mean square phase errors comparable to or lower than the bispectrum algorithm for good seeing and few data frames, while the converse is true for many data frames and poor seeing.

关键词： speckle imaging multi-frame blind deconvolution MFBD bispectrum

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Inverse scattering of strongly scattering targets using redundant data sets

Inverse scattering of strongly scattering targets using redu...

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2nd conference on image reconstruction from incomplete data

作者： Semichaevsky, Av Ghogomu, P Al Ababneh, N Testorf, ME Fiddy, MA Univ Massachusetts Lowell Dept Elect & Comp Engn Lowell MA 01854 USA

ISBN: (纸本)0819445592

For weakly scattering permittivities, each measurement of the scattered far field can be interpreted as a sampling point of the Fourier transformation of the object. Furthermore, each sampling point can be accessed by more than one combination of wavelength, propagation direction, and polarization of the incident field. This means, a set of measurements which access the same sampling point can be regarded as being redundant. For strongly scattering objects the Fourier diffraction slice theorem does not apply. We show that measurements which are redundant in the weakly scattering case can be exploited to resolve difficulties associated with imaging of the strongly scattering objects. One dimensional geometries are investigated to estimate the potential redundant data sets offer for addressing the inverse scattering problem of strongly and multiply scattering objects. In addition, we discuss preliminary results for solving 2D imaging problems.

关键词： nonlinear inverse scattering strongly scattering objects multiple scattering polarimetric information diffraction tomography synthetic aperture radar

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Can broad-band image restoration rival speckle restoration?

Can broad-band image restoration rival speckle restoration?

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2nd conference on image reconstruction from incomplete data

作者： Fraser, D Lambert, A Jahromi, MRS Clyde, D Donaldson, N Univ New S Wales Univ Coll Sch Elect Engn Canberra ACT 2600 Australia

ISBN: (纸本)0819445592

The restoration of images formed through atmospheric turbulence is usually attempted through operating on a sequence of speckle images. The reason is that high spatial frequencies in each speckle image are effectively retained though reduced in magnitude and distorted in phase. However, speckle imaging requires that the light is quasi-monochromatic. An alternative possibility, discussed here, is to capture a sequence of images through a broadband filter, correct for any local warping due to position-dependent tip-tilt effects, and average over a large number of images. In this preliminary investigation, we simulate several optical transfer functions to compare the signal levels in each case. The investigation followed encouraging results that we obtained recently using a blind-deconvolution approach. The advantages of such a method are that narrow-band filtering is not required, simplifying the equipment and allowing more photons for each short exposure image, while the method lends itself to restoration over fields of view wider than the isoplanatic patch without the need to mosaic. The preliminary conclusions are that, so long as the ratio of the telescope objective diameter, D, to Fried parameter, r(0), is less than about 5, the method may be a simple alternative to speckle imaging.

关键词： digital image restoration speckle restoration blind deconvolution astronomical imaging surveillance imaging atmospheric turbulence optical flow image registration

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Multi-frame blind deconvolution with linear equality constraints

Multi-frame blind deconvolution with linear equality constra...

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2nd conference on image reconstruction from incomplete data

作者： Löfdahl, MG Royal Swedish Acad Sci AlbaNova Univ Ctr Inst Solar Phys SE-10691 Stockholm Sweden

ISBN: (纸本)0819445592

\The Phase Diverse Speckle (PDS) problem is formulated mathematically as Multi Frame Blind Deconvolution (MFBD) together with a set of Linear Equality Constraints (LECs) on the wavefront expansion parameters. This MFBD-LEC formulation is quite general and, in addition to PDS, it allows the same code to handle a variety of different data collection schemes specified as data, the LECs, rather than in the code. It also relieves us from having to derive new expressions for the gradient of the wavefront parameter vector for each type of data set. The idea is first presented with a simple formulation that accommodates Phase Diversity, Phase Diverse Speckle, and Shack-Hartmann wavefront sensing. Then various generalizations are discussed, that allows many other types of data sets to be handled. Background: Unless auxiliary information is used, the Blind Deconvolution problem for a single frame is not well posed because the object and PSF information in a data frame cannot be separated. There are different ways of bringing auxiliary information to bear on the problem. MFBD uses several frames which helps somewhat, because the solutions are constrained by a requirement that the object be the same, but is often not enough to get useful results without further constraints. One class of MFBD methods constrain the solutions by requiring that the PSFs correspond to wavefronts over a certain pupil geometry, expanded in a finite basis. This is an effective approach but there is still a problem of uniqueness in that different phases can give the same PSF. Phase Diversity and the more general PDS methods are special cases of this class of MFBD, where the observations are usually arranged so that in-focus data is collected together with intentionally defocused data, where information on the object is sacrificed for more information on the aberrations. The known differences and similarities between the phases are used to get better estimates.

关键词： wavefront sensing deconvolution phase diversity inverse problems image restoration Shack-Hartmann

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Near-lossless image compression by adaptive prediction: new developments and comparison of algorithms

Near-lossless image compression by adaptive prediction: new ...

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conference on Mathematics of data/image Coding, Compression and Encryption v, with Applications

作者： Aiazzi, B Alparone, L Baronti, S CNR IFAC Inst Appl Phys N Carrara I-50127 Florence Italy

ISBN: (纸本)0819445606

This paper describes state-of-the-art approaches to near-lossless image compression by adaptive causal DPCM and presents two advanced schemes based on crisp and fuzzy switching of predictors, respectively. The former relies on a linear-regression prediction in which a different predictor is employed for each image block. Such block-representative predictors are calculated from the original data set through an iterative relaxation-labeling procedure. Coding time are affordable thanks to fast convergence of training. Decoding is always performed in real time. The latter is still based on adaptive MMSE prediction in which a different predictor at each pixel position is achieved by blending a number of prototype predictors through adaptive weights calculated from the past decoded samples. Quantization error feedback loops are introduced into the basic lossless encoders to enable user-defined upper-bounded reconstruction errors. Both schemes exploit context modeling of prediction errors followed by arithmetic coding to enhance entropy coding performances. A thorough performance comparison on a wide test image set show the superiority of the proposed schemes over both up-to-date encoders in the literature and new/upcoming standards.

关键词： adaptive DPCM classified DPCM differential pulse code modulation (DPCM) entropy coding fuzzy logic image compression near-lossless compression adaptive prediction relaxation labeling statistical context modeling

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Limited view thermoacoustic tomography

Limited view thermoacoustic tomography

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Proceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS)

作者： Xu, Yuan Wang, Lihong v. Biomedical Engineering Program Texas A and M University College Station TX 77843-3120 United States

Truncated conjugate gradient method was applied to study the limited view problem in thermoacoustic tomography, and the results were compared with those of modified backprojection method, which is the backprojection of the first order time derivative of acoustic signals. Our numerical simulations showed that there is complete data for a stable and perfect reconstruction in a 2-D π-view problem, where the least angle acquired by the detection curve is π when viewed from the imaged region of interest. On the contrary, in a problem where the view is less than π, data is incomplete, and artifacts and quantitative errors were obvious in the reconstructed images. It was pointed out that the result after one iteration in truncated conjugate gradient method is equivalent to that of modified backprojection, which can restore the high frequency information of imaged objects. The low frequency information can be recovered significantly in the next ten iterations of truncated conjugate gradient method.

关键词： Tomography

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