Sparsity of the TSAR images is exploited with the aim to use the possibility of applying an under-sampling strategy as assumed by the compressive sensing approach. The signal sparsity is a desirable property that need...
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ISBN:
(纸本)9781509022212
Sparsity of the TSAR images is exploited with the aim to use the possibility of applying an under-sampling strategy as assumed by the compressive sensing approach. The signal sparsity is a desirable property that needs to be satisfied in order to reconstruct the signals and images from the compressive sensed data. It is assumed that certain amount of radar data is not available and the idea is to reconstruct the radar imagefrom the rest of the data. The signal samples are observed in the spatial domain, and the reconstruction is based on the total variation minimization. The procedure is tested on both, synthetic and real TSAR image, showing satisfactory reconstruction quality with a small set of acquired samples.
The author presents the maximum a posteriori (MAP) estimation method to estimate irradiance elemental images and reconstruct 3D images using photon-counting integral imaging. Elemental images are captured using the sy...
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ISBN:
(纸本)9780819482969
The author presents the maximum a posteriori (MAP) estimation method to estimate irradiance elemental images and reconstruct 3D images using photon-counting integral imaging. Elemental images are captured using the synthetic aperture integral imaging (SAII) technique. Photon-counting elemental images are generated using the Poisson distribution. The method can reconstruct 3D images more accurately than the one using maximum likelihood (MLE) estimation. This may be important in medical imaging as well as other photon-level applications.
Airflow over mountainous terrain can produce stationary atmospheric waves in the lee of the mountains that have large vertical air velocities. These waves are used as sources of lift by sailplane pilots. Methods are d...
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ISBN:
(纸本)0819455008
Airflow over mountainous terrain can produce stationary atmospheric waves in the lee of the mountains that have large vertical air velocities. These waves are used as sources of lift by sailplane pilots. Methods are developed for inverting flight data of airspeed and GPS-derived position to obtain estimates of the vector windspeed in mountain waves. datafrom flight path segments with significantly different ground velocities within a region of constant windspeed give a well-determined solution for the windspeed. The methods are applied to flight datafrom a Perlan Project flight in lee waves of the Sierra Nevada Mountains in California.
We introduce a volumetric space-time technique for the reconstruction of moving and deforming objects from point data. The output of our method is a four-dimensional space-time solid, made up of spatial slices, each o...
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We introduce a volumetric space-time technique for the reconstruction of moving and deforming objects from point data. The output of our method is a four-dimensional space-time solid, made up of spatial slices, each of which is a three-dimensional solid bounded by a watertight manifold. The motion of the object is described as an incompressible flow of material through time. We optimize the flow so that the distance material moves from one time frame to the next is bounded, the density of material remains constant, and the object remains compact. This formulation overcomes deficiencies in the acquired data, such as persistent occlusions, errors, and missing frames. We demonstrate the performance of our flow-based technique by reconstructing coherent sequences of watertight models fromincomplete scanner data.
Single-photon emission computed tomography (SPECT) is a method of choice for imaging spatial distributions of radioisotopes. Applications of this method are found in medicine, biomedical research and nuclear industry....
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Single-photon emission computed tomography (SPECT) is a method of choice for imaging spatial distributions of radioisotopes. Applications of this method are found in medicine, biomedical research and nuclear industry. This paper deals with improving spatial resolution in SPECT by applying correction for the point-spread function (PSF) in the reconstruction algorithm and optimizing the collimator. Several approaches are considered: the use of a depth-dependent PSF model for a parallel-beam collimator derived from experimental data, the extension of this model to a fan-beam collimator, a triangular approximation of the PSF for reconstruction acceleration, and a method for optimal fan-beam collimator design. An unmatched projector/backprojector ordered subsets expectation maximization (OSEM) algorithm is used for imagereconstruction. Experimental results with simulated and physical phantom data of a micro-SPECT system show a significant improvement of spatial resolution with the proposed methods.
The optical instrument function is used as the basis to develop optical system theory for imaging applications. The detection of optical signals is conveniently described as the overlap integral of the Wigner distribu...
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ISBN:
(纸本)9781628417661
The optical instrument function is used as the basis to develop optical system theory for imaging applications. The detection of optical signals is conveniently described as the overlap integral of the Wigner distribution functions of instrument and optical signal. Based on this framework various optical imaging systems, including plenoptic cameras, phase-retrieval algorithms, and Shack-Hartman sensors are shown to acquire information about a domain in phase-space, with finite extension and finite resolution. It is demonstrated how phase space optics can be used both to analyze imaging systems, as well as for designing methods for imagereconstruction.
We address the reconstruction of a 3D imagefrom a set of incomplete X-ray tomographic data. In the case where the image is composed of one or several objects lying in a uniform background, we define a sparse paramete...
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ISBN:
(纸本)0780391349
We address the reconstruction of a 3D imagefrom a set of incomplete X-ray tomographic data. In the case where the image is composed of one or several objects lying in a uniform background, we define a sparse parameterization by considering the active voxels, i.e., the voxels that do not lay inside the background. Estimation of the active voxel densities is performed using the maximum a posteriori (MAP) estimator. In order to implement sparse parameter estimation, we design an original multiresolution scheme, which handles coarse to fine resolution images. This scheme affords automatic selection of active voxels at each resolution level, and provides a drastic decrease of the computation time. We finally show the performance of our method on synthetic data.
Inpainting is an image interpolation problem, with broad applications in image processing andthe digital technology. This paper presents our recent efforts in developing inpainting models based on the Bayesian and var...
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ISBN:
(纸本)0819445592
Inpainting is an image interpolation problem, with broad applications in image processing andthe digital technology. This paper presents our recent efforts in developing inpainting models based on the Bayesian and variational principles. We discuss several geometric image (prior) models, their role in the construction of variational inpainting models, the resulting Euler-Lagrange differential equations, and their numerical implementation.
3D geometric models obtained by using laser scanners are often incomplete due to the equipment limitations. In this paper we propose a novel hybrid reconstruction algorithm, which integrates stereo image pairs to over...
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ISBN:
(纸本)9780769529394
3D geometric models obtained by using laser scanners are often incomplete due to the equipment limitations. In this paper we propose a novel hybrid reconstruction algorithm, which integrates stereo image pairs to overcome these limitations. This work focuses on a category of scenes that can be approximated by planes (such as manmade scenes). The scan data are first segmented into planar patches, many of which may be incomplete. Stereo image pairs are then incorporated to retrieve the missing data. Specifically, we decide each plane's extension in the image domain via segment-based stereo matching with disparity layers extracted from scan data. Then, points in the missing area are interpolated by calculating ray-plane intersections. All procedures are automatic except for the range to image registration. The validity of our approach is demonstrated by experiments on real data.
In this paper we discuss imagereconstruction algorithms in super-short-scan fan-beam and cone-beam computed tomography (CT). We propose a new fan-beam filtered back-projection algorithm which can obtain exact region ...
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ISBN:
(纸本)0819455008
In this paper we discuss imagereconstruction algorithms in super-short-scan fan-beam and cone-beam computed tomography (CT). We propose a new fan-beam filtered back-projection algorithm which can obtain exact region of interest (ROI) reconstruction if and only if every projecting line passing through the ROI intersects the source trajectory, even if the scanning range is smaller than the half-scan. And we prove the algorithm is approximate when the projections are truncated. Furthermore, we expand the algorithm to cone-beam reconstruction. Then we simulate the algorithm on the computer and evaluate the noise properties of the new algorithm and the other algorithms. Numerical results in our work suggest that the new algorithm is generally less susceptible to data noise and less artifacts than the before algorithms. In particular, the new algorithm is easily and successfully expanded to cone-beam tomography when the source trajectory is a short-arc on the single circle or on the helical trajectory.
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