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

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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...

引用

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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Self Tuning Kalman Filter Estimation of Atmospheric Warp

Self Tuning Kalman Filter Estimation of Atmospheric Warp

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conference on image reconstruction from incomplete data V

作者： Tahtali, Murat Lambert, Andrew Fraser, Donald UNSW ADFA Sch Aerosp Civil & Mech Engn Canberra ACT 2600 Australia UNSW ADFA Sch Informat Technol & Elect Engn Canberra ACT 2600 Australia

ISBN: (纸本)9780819472960

In our previous work we have demonstrated that the perceived wander of image intensities as seen through the windows" of each pixel due to atmospheric turbulence can be modelled as a simple oscillator pixel-by-pixel and a linear Kalman filter (KF) can be finetuned to predict to a certain extent short term future deformations. In this paper, we are expanding the Kalman filter into a Hybrid Extended Kalman filter (HEKF) to fine tune itself by relaxing the oscillator parameters at each individual pixel. Results show that HEKF performs significantly better than linear KF.

关键词： Kalman filter image registration shiftmaps atmospheric warp image restoration

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JSR-NET: A DEEP NETWORK FOR JOINT SPATIAL-RADON DOMAIN CT reconstruction from incomplete data 44

JSR-NET: A DEEP NETWORK FOR JOINT SPATIAL-RADON DOMAIN CT RE...

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44th IEEE International conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Zhang, Haimiao Dong, Bin Liu, Baodong Peking Univ Beijing Peoples R China Chinese Acad Sci Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781479981311

CT image reconstruction from incomplete data, such as sparse views and limited angle reconstruction, is an important and challenging problem in medical imaging. This work proposes a new deep convolutional neural network (CNN), called JSR-Net, that jointly reconstructs CT images and their associated Radon domain projections. JSR-Net combines the traditional model based approach with deep architecture design of deep learning. A hybrid loss function is adopted to improve the performance of the JSR-Net making it more effective in protecting important image structures. Numerical experiments demonstrate that JSR-Net outperforms some latest model based reconstruction methods, as well as a recently proposed deep model.

关键词： Joint spatial-Radon domain reconstruction Sparse-view CT Limited angle CT Convolutional neural networks Deep learning

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Unified imaging theory for X-ray and acoustic computerized tomography

Unified imaging theory for X-ray and acoustic computerized t...

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conference on image reconstruction from incomplete data III

作者： Liu, PY Wang, G Boyer, A Stanford Univ Dept Radiat Oncol Stanford CA 94305 USA

ISBN: (纸本)0819455008

X-ray computerized tomography (CT) and acoustic CT are two main medical imaging modalities based on two intrinsically different physical phenomena. X-ray CT is based on xray's attenuation when x-ray passes through medium. It has been well known that the Radon transform is the imaging theory for x-ray CT. Photoacoustic CT is a type of acoustic CT, which is based on differentiating electromagnetic energy absorption among media. In 1998 a new 3D reconstruction concept, the P-transform, was proposed to serve the imaging theory for photoacoustic CT. In this paper it was rigorously proved that both x-ray CT and photoacoustic CT are governed by a unified imaging theory. 3D data acquisition can be completed in 2pi stereoangle. This new imaging theory realized, in part, the dream of all physicists, including Albert Einstein, who have long believed that our world is ultimately governed by few simple rules.

关键词： image reconstruction P-transform Radon transform

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TOMOGRAPHIC image reconstruction from incomplete INFORMATION BY CONVEX PROJECTIONS AND DIRECT FOURIER INVERSION: SUGGESTED APPLICATIONS TO SPOTLIGHT-MODE SYNTHETIC APERTURE RADAR (SAR) IMAGING.

TOMOGRAPHIC IMAGE RECONSTRUCTION FROM INCOMPLETE INFORMATION...

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Proceedings of the 1984 conference on Information Sciences and Systems.

作者： Sezan, M.Ibrahim Stark, Henry Rensselaer Polytechnic Inst Troy NY USA Rensselaer Polytechnic Inst Troy NY USA

Spotlight-mode synthetic aperture radar (SAR) imaging has a close resemblance to tomographic image reconstruction from incomplete view data. A new algorithm (PRDF), designed for reconstructing tomographic imagery from incomplete view data, is described. The results of applying the PRDF algorithm to reconstruct a human thorax cross-section from simulated X-ray projection data are furnished. An algorithm which is basically a special case of PRDF is suggested for spotlight-mode SAR imaging.

关键词： image PROCESSING

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Oblique surface reconstruction to approximate cone-beam helical data in multi-slice CT

Oblique surface reconstruction to approximate cone-beam heli...

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conference on image reconstruction from incomplete data

作者： Chen, LG Heuscher, DJ Liang, Y Purdue Univ Sch Hlth Sci W Lafayette IN 47907 USA

ISBN: (纸本)0819437689

Multi-slice helical beam scanning involves cone-beam geometry. The primary advantages for use of divergent cone-beams include reduced data acquisition, improved image resolution and optimized photon utilization. Due to the complexity of 3-dimensional cone-beam reconstruction, approximate algorithms have been sought to handle the cone-beam reconstruction. This paper presents a new approximate algorithm termed as oblique surface reconstruction (OSR). Theoretical considerations as well as the reconstruction of simulated phantom data in comparison to the current standard 180 degrees LI are presented. OSR is shown to be effective and practical to generate images with diagnostic quality.

关键词： spiral CT multi-slice CT cone-beam reconstruction oblique surface reconstruction

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Obtaining three dimensional probability density functions from projected data

Obtaining three dimensional probability density functions fr...

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conference on image reconstruction from incomplete data

作者： Jaffe, JS Univ Calif San Diego Scripps Inst Oceanog Marine Phys Lab La Jolla CA 92093 USA

ISBN: (纸本)0819437689

In many experimental observation systems where the goal is to record a 3-dimensional observation of an object, or a set of objects, a lower dimensional projection of the intended subject is obtained. In some situations only the statistical properties of such objects is desired: the three dimensional probablility density function. This article demonstrates that under special symmetries this function can be obtained from a two dimensional probability density function which, has been obtained from the observed, projected data. Standard tomographic theorems can be used to guarantee the uniqueness of this function and a natural basis set can be used in computing the three dimensional function from the two dimensional projection. Here, the theory of this inversion is explored from a theoretical and numerical point of view with some examples of data functions taken from scientific experiments

关键词： tomography probability density function inverse theory

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3-D reconstruction OF OBJECTS from incomplete data AND A-PRIORI KNOWLEDGE.

3-D RECONSTRUCTION OF OBJECTS FROM INCOMPLETE DATA AND A-PRI...

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作者： Tsikos, Constantinos J. Bajcsy, Ruzena K.

The authors are interested in the reconstruction of 3-D objects from various sources of incomplete data as well as apriori knowledge about the object under reconstruction. As data sources use is made of conventional Xray projections as well as CAT scans perpendicular to the Xray planes. These data sources were chosen because they are complementary to each other, in the sense that information not found in one set can be found in the other.

关键词： image processing

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Restoration of nonuniformly warped images using accurate frame by frame shiftmap accumulation

Restoration of nonuniformly warped images using accurate fra...

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conference on image reconstruction from incomplete data IV

作者： Tahtali, Murat Lambert, Andrew J. Fraser, Don UNSW Sch Aerosp Civil & Mech Eng ADFA Canberra ACT Australia UNSW Sch Informat Technol & Elect Engn ADFA Canberra ACT Australia

ISBN: (纸本)0819463957

When imaging through the atmosphere, the resulting image contains not only the desired scene, but also the adverse effects of all the turbulent air mass between the camera and the scene. These effects are viewed as a combination of non-uniform blurring and random shifting of each point in the received short-exposure image. Corrections for both aspects of this combined distortion have been tackled reasonably successfully by previous efforts. A potentially more robust method of restoring the geometry is presented, which is also better suited to real-time implementation. The improvements were achieved by replacing the concept of prototype frame with the sequential registration of each frame with its nearest neighbour and the accurate accumulation of shiftmaps from any one frame to another without redundant calculations.

关键词： adaptive optics image registration image restoration

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INVERSE SURFACELET TRANSFORM FOR image reconstruction WITH PRIOR KNOWLEDGE

INVERSE SURFACELET TRANSFORM FOR IMAGE RECONSTRUCTION WITH P...

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ASME International Design Engineering Technical conferences and Computers and Information in Engineering conference (IDETC/CIE)

作者： Huang, Wei Wang, Yan Rosen, David W. Georgia Inst Technol Sch Mech Engn Atlanta GA 30332 USA

ISBN: (纸本)9780791855850

image reconstruction is the transformation process from some other data forms to image pixels. It can be utilized as a method to retrieve material composition information in materials characterization and design. In our previous work, a so-called surfacelet model was proposed to construct the geometric boundary and internal material distribution of heterogeneous materials at the same time. A surfacelet transform is able to efficiently represent boundary information in images of materials. In this paper, new constrained-conjugate-gradient-based image reconstruction methods are proposed as the inverse surfacelet transform. With geometric constraints on internal boundaries of materials, the proposed method is able to automatically identify the locations and orientations of the internal boundaries based on prior knowledge so as to reconstruct material composition with incomplete data.

关键词： image reconstruction

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