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

共 419 条记录，以下是261-270 订阅

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Self Tuning Kalman Filter Estimation of Atmospheric Warp

Self Tuning Kalman Filter Estimation of Atmospheric Warp

引用

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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Spectral image Estimation for Coded Aperture Snapshot Spectral imagers

Spectral Image Estimation for Coded Aperture Snapshot Spectr...

引用

conference on image reconstruction from incomplete data V

作者： Wagadarikar, Ashwin A. Pitsianis, Nikos P. Sun, Xiaobai Brady, David J. Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA Duke Univ Dept Comp Sci Durham NC 27708 USA

ISBN: (纸本)9780819472960

This paper describes numerical estimation techniques for coded aperture snapshot spectral imagers (CASSI). In a snapshot, a CASSI captures a two-dimensional (2D) array of measurements that is an encoded representation of both spectral information and 2D spatial information of a scene. The spatial information is modulated by a coded aperture and the spectral information is modulated by a dispersive element. The estimation process decodes the 2D measurements to render a three-dimensional spatio-spectral estimate of the scene, and is therefore an indispensable component of the spectral imager. Numerical estimation results, are presented.

关键词： coded aperture snapshot spectral imager system modeling spectral image estimation

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Multi-spectral intensity diffraction tomography

Multi-spectral intensity diffraction tomography

引用

conference on image reconstruction from incomplete data V

作者： Anastasio, Mark A. Xu, Qiaofeng Shi, Daxin IIT Dept Biomed Engn Med Imaging Res Ctr Chicago IL 60616 USA Toshiba Med Res Inst USA Inc Vernon Hills IL USA

ISBN: (纸本)9780819472960

Intensity diffraction tomography (I-DT) is a, non-interferometric imaging method for reconstructing the complex-valued refractive index distribution of a, weakly scattering object. The original formulation of I-DT requires measurement of two in-line intensity measurements on parallel detector planes at each tomographic view angle. In this work, a reconstruction theory for multi-spectral is established and investigated for use with single material objects whose dispersion characteristics are known a priori. Unlike other I-DT methods, the temporal frequency of the illuminating plane-wave represents the degree-of-freedom of the imaging system that is varied to acquire two independent intensity measurements on a fixed detector-plane. Moreover, the proposed method accounts for object dispersion.

关键词： Diffraction tomography phase-contrast tomography three-dimensional image reconstruction

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Superresolution capabilities of 3D optical filters

Superresolution capabilities of 3D optical filters

引用

conference on image reconstruction from incomplete data V

作者： Fiddy, Michael A. Testorf, Markus E. Dartmouth Coll Thayer Sch Engn 8000 Cummings Hall Hanover NH 03755 USA Univ N Carolina Charlotte NC 28223 USA

ISBN: (纸本)9780819472960

Multichannel sampling strategies have been considered for a number of applications including feature specific imaging, and digital superresolution. Typically, channel coding is accomplished with a thin modulating mask, either in the focal plane, or in the aperture of the imaging system. In this contribution, we extend Hie concept of multichannel imaging to systems by suggesting the use of 3D structures for channel coding. A single pixel camera design and the single scattering approximation are used to obtain a Fourier space interpretation of 3D filters. The k-space analysis indicates that the dispersion relation of propagating plane wave modes set severe constraints if 3D filters are used for channel coding. We relate this to the broader questions about the fundamental limits of optical and computational imaging and propose 3D filters for wavelength coding and superresolution applications.

关键词： Computational Imaging Resolution Enhancement image reconstruction Multiple image Frames Volume Holograms

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incomplete points cloud data surface reconstruction based on neural network

Incomplete points cloud data surface reconstruction based on...

引用

4th International conference on Intelligent Information Hiding and Multimedia Signal Processing

作者： Wu Xue-mei Li Gui-xian Zhao Wei-min Harbin Inst Technol Sch Mech & Elect Harbin 150001 Heilongjiang Pr Peoples R China Daquing Univ Dept Engn Mech Daqing 163318 Heilongjiang Peoples R China

ISBN: (纸本)9780769532783

Neural network arithmetic was employed in incomplete points cloud data surface reconstruction, Radial basis function neural network and simulated annealing arithmetic was combined. The new arithmetic can approach any nonlinear function by arbitrary precision, and also keep the network from getting into local minimum. Global optimization feature of simulated annealing was employed to adjust the network weights. MATLAB program was compiled, experiments on incomplete points cloud data have been done employing this arithmetic, the result shows that this arithmetic can efficiently approach the surface with 10(-4) mm error precision, and also the learning speed is quick and the reconstruction surface is smooth. Different methods have been employed to do surface reconstruction in comparison, the results illustrate the error employed algorithmic proposed in the paper is little and converge speed is quick.

关键词： Surface reconstruction Artificial neural networks image reconstruction Simulated annealing Training Meteorology Radial basis function networks

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Realtime visualization of monocular data for 3D reconstruction

Realtime visualization of monocular data for 3D reconstructi...

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5th Canadian conference on Computer and Robot Vision

作者： Rachmielowski, Adam Birkbeck, Neil Jagersand, Martin Cobzas, Dana Univ Alberta CS Edmonton AB T6G 2M7 Canada

ISBN: (纸本)9780769531533

Methods for reconstructing photorealistic 3D graphics models from images or video are appealing applications of computer vision. Such methods rely on good input image data, but the lack-of user feedback during image acquisition often leads to incomplete or poorly sampled reconstruction results. We describe a video-based system that constructs and visualizes a coarse graphics model in real-time and automatically saves a set of images appropriate for later off-line dense reconstruction. Visualization of the model during image acquisition allows the operator to interactively verify that an adequate set of input images has been collected for the modeling task, while automatic image selection keeps storage requirements to a minimum. Our implementation uses real-time monocular SLAM to compute and continuously keep extending a 3D model, augments this with key-frame selection for storage, surface modelling, and on-line rendering of the current structure textured from a selection of key-frames. This rendering gives an immediate and intuitive view of both the geometry and if suitable viewpoints of texture images have already been captured.

关键词： image acquisition

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Inversion of strongly scattered data: shape and permittivity recovery

Inversion of strongly scattered data: shape and permittivity...

引用

conference on image reconstruction from incomplete data V

作者： Shahid, U. Fiddy, M. A. Testorf, M. E. Univ N Carolina Ctr Optoelect & Opt Commun Charlotte NC 28223 USA Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA

ISBN: (纸本)9780819472960

Reconstructing an object from scattered field data has always been very challenging, especially when dealing with strong scatterers. Several techniques have been proposed to address this problem but either they fail to provide a good estimate of the object or they are computationally very expensive. We have proposed a straightforward non-linear signal processing method in which we first process the scattered field data to generate a minimum phase function in the object domain. This is accomplished by adding a reference wave whose amplitude and phase satisfy certain conditions. Minimum-phase functions are causal transforms and their phase is continuous in the interval -pi and +pi, i.e. it is always unwrapped. Following this step, we compute the Fourier transform of the logarithm of this minimum phase function, referred to as its cepstrum. In this domain one can filter cepstral frequencies arising from the object from those of the scattered field. Cepstral data arc meaningless for non-minimum phase functions because of phase wraps. We apply low pass filters in the cepstral domain to isolate information about the object and then perform an inverse transform and exponentiation. We have applied this technique to measured data provided by Institut Fresnel (Marseille, France) and investigated in a systematic way the dependence of the approach on the properties of the reference wave and filter. We show that while being a robust method, one can identify optimal parameters for the reference wave that result in a good reconstruction of a penetrable, strongly scattering permittivity distribution.

关键词： inverse scattering minimum phase condition homomorphic filtering imaging

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Convex Ultrasound image reconstruction with Log-Euclidean Priors

Convex Ultrasound Image Reconstruction with Log-Euclidean Pr...

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30th Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Seabra, Jose Xavier, Joao Sanches, Joao Univ Tecn Lisboa Syst & Robot Inst Inst Super Tecn P-1049001 Lisbon Portugal

ISBN: (纸本)9781424418145

image reconstruction from noisy and incomplete observations is usually an ill-posed problem. A Bayesian framework may be adopted do deal with this such inverse task by well posing the reconstruction problem. In this approach, the ill poseness nature of the reconstruction is removed by minimizing a two-term energy function. The first term pushes the solution toward the data and the second regularizes the solution. A Bayesian algorithm for ultrasound image reconstruction and de-noising is proposed where an edge preserving prior is used to reduce the smoothing effect at the transitions. The prior distribution is based on log-Euclidean potential functions that are particular suitable in reconstruction problems under the constraint of positivity, that is, when the unknowns to be estimated should be positive, which is the case, where the noisy observations are modeled by a Rayleigh distribution. In this paper, the reconstruction procedure is formulated as the optimization of a convex function and a Newton method is adopted to obtain the minimizer. This strategy guarantees a convergence to the global minimum in a small number of iterations. Experimental results, using synthetic and real medical images are shown. The proposed method produces images where speckle noise is effectively suppressed and important clinical details (organ and tissue transitions) are preserved.

关键词： Newton-Raphson method

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Coregistered volumetric true 3D ultrasonography in image-guided neurosurgery

Coregistered volumetric true 3D ultrasonography in image-gui...

引用

Medical Imaging 2008 conference

作者： Ji, Songbai Hartov, Alex Fontaine, Kathryn Borsic, Andrea Roberts, David Paulsen, Keith Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA Norris Cotton Ctr Lebanon NH 03756 USA Hitchcock Med Ctr Dept Neurosurg Lebanon NH 03756 USA

ISBN: (纸本)9780819471024

Intraoperative ultrasound (iUS) has emerged as a practical neuronavigational tool in image-guided open cranial procedures because of its low cost, easy implementation and real time image acquisition. Two-dimensional iUS (2DiUS) is currently the most common ultrasonic imaging tool used in the operating room (OR). However, gaps between imaging planes and limited volumetric sampling with 2DiUS often result in incomplete imaging of the internal anatomical structures of interest (e.g., tumor). In this paper, we investigate and evaluate the use of coregistered volumetric true three-dimensional iUS (3DiUS) generated from a broadband matrix array transducer (X3-1) attached to a Phillips iU22 intelligent ultrasound system. This 3DiUS scheme is able to provide full 3D sampling over a frustum-shaped volume with high resolution dicom images directly recovered by the ultrasound system without the need for free-hand sweeps or 3D reconstruction. Volumetric 3DiUS images were co-registered with preoperative magnetic resonance (pMR) images by tracking the spatial location and orientation of an infrared light-emitting tracker rigidly attached to the US scan-head following a fiducial registration and an iUS scan-head calibration. The registration was further refined using an image-based scheme to maximize the inter-image normalized mutual information. In addition, we have utilized a coordinate system nomenclature and developed a set of static visualization techniques to present 3D US image data in the OR, which will be important for qualitative and quantitative analyses of the performance of 3DiUS in image-guided neurosurgery in the future. We show that 3DiUS significantly improves the imaging efficiency and enhances integration of iUS into the surgical workflow, making it appear to be promising for routine use in the OR.

关键词： ultrasound guidance multimodality display data integration for the clinic/OR intraoperative imaging

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Cone-beam artifact reduction using second pass radon space filling

Cone-beam artifact reduction using second pass radon space f...

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Klaus Erhard Philips Research Europe Hamburg Germany

Volume reconstruction from incomplete cone-beam data is prone to artifacts because of the insufficient amount of measured data. A second pass method is proposed which reduces these artifacts by extrapolating the measured data in order to simulate complete cone-beam data. To this end a first pass reconstruction is segmented and forward projected into a virtual geometry satisfying Tuy’s completeness condition. The resulting simulated data is then reconstructed together with the measured data using an exact cone-beam reconstruction algorithm. Numerical examples are given for both measured data of a physical head phantom and for simulated data using the Forbild head phantom.

关键词： Filling image reconstruction Head Imaging phantoms Geometry image segmentation Bones reconstruction algorithms Tomography Biological tissues

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