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 situation...
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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
The authors are interested in the reconstruction of 3-D objects fromvarious sources of incompletedata as well as apriori knowledge about the object under reconstruction. As data sources use is made of conventional X...
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The authors are interested in the reconstruction of 3-D objects fromvarious sources of incompletedata 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.
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 ...
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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.
imagereconstruction 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 o...
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ISBN:
(纸本)9780791855850
imagereconstruction 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 imagereconstruction 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 incompletedata.
Problems of reconstructing acoustic signals from unevenly spaced samples (sparse signal) and signals distorted by losses of adjacent samples (solid gaps) are considered. To solve these problems original algorithms are...
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Problems of reconstructing acoustic signals from unevenly spaced samples (sparse signal) and signals distorted by losses of adjacent samples (solid gaps) are considered. To solve these problems original algorithms are proposed: the Interpolation Method of Sequential Computation of the Fourier spectrum and the method of amplitude iterations. The effectiveness of these methods is compared with the method of projections onto convex sets and its modification, implemented using an evolutionary time-frequency transformation based on the basic functions of Slepian. In the case of continuous gaps, comparisons are made with a one-dimensional modification of the method, which is related to neural networks image inpainting. Evaluation of the effectiveness of the proposed methods according to objective criteria indicates their suitability for practical use.
Compressed sensing (CS) in imaging is essential in many practical situations and does need suitable algorithm for reconstructionfrom this highly incomplete observations/measurements. Measurements are also noisy in ma...
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ISBN:
(纸本)9781479986378
Compressed sensing (CS) in imaging is essential in many practical situations and does need suitable algorithm for reconstructionfrom this highly incomplete observations/measurements. Measurements are also noisy in majority of the cases. This paper addresses CS-reconstruction of images from multiple channel data acquisition with under sampling measurements. An adaptive filtering based stochastic approximation through a recursive system is explored to reconstruct images from CS-multichannel noisy measurements using fusion technique. A simple weighted averaging is done in fusion process where the weights are calculated based on estimation of noise level. A spatial domain adaptive Wiener filter is then used to diminish the noise and reveals new features from the degraded observations. Experimental results show that the proposed multichannel fusion based CS reconstruction scheme outperforms individual channels both in subjective and objective quality measures.
In this work, the concept of quasi-point source (qps) is used for the restoration of defocused images of extended objects detected with incoherent light. The method consists of the characterization of the optical syst...
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ISBN:
(纸本)9781628417661
In this work, the concept of quasi-point source (qps) is used for the restoration of defocused images of extended objects detected with incoherent light. The method consists of the characterization of the optical system by a qps illuminated with coherent light, its defocused image is then introduced in the restoration process, which is a deconvolution performed with a Wiener filter. The results of the restored images are shown and compared with those images restored when the qps is illuminated with incoherent light. Finally, a numerical evaluation using the RMSD (root mean square deviation method) about the quality of the restoration was made for both cases.
Myosin filaments are important components of striated muscle and pack in a semi-ordered, two-dimensional array. The array can be imaged by electron microscopy of thin cross-sections which indicates, for many species, ...
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ISBN:
(纸本)0819463957
Myosin filaments are important components of striated muscle and pack in a semi-ordered, two-dimensional array. The array can be imaged by electron microscopy of thin cross-sections which indicates, for many species, that the filaments adopt two orientations that are distributed with short-ranging order. We describe analysis and modelling of this substitution disorder based on the micrographs and an Ising model.
This paper explores the technique that employs Principal Component Analysis (PCA) for motion synthesis and incomplete motion datareconstruction. A low dimensional space of human motion patterns are generated from a l...
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Infrared images provide valuable information for many applications. However, compared to a visible image, the image quality is poor and its spatial resolution is limited due to the focal plane arrays cannot be made de...
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ISBN:
(纸本)9780819492173
Infrared images provide valuable information for many applications. However, compared to a visible image, the image quality is poor and its spatial resolution is limited due to the focal plane arrays cannot be made dense enough to yield a sufficiently high spatial sampling frequency, which consequently leads to image blurring. Optical micro-scanning technique has been proven to be an effective method to increase the resolution of images. This technique is able to produce high resolution (HR) images from a set of optically shifted images of low-resolution (LR). Over the last decade, optical micro-scanning technique has become one of the active topics of research, among this, the super-resolution (SR) reconstruction algorithms are the focus. This paper starts with the basic principle of SR reconstruction. Then several methods of high-precision movement registration algorithm and SR reconstruction algorithms were introduced. This study particularly focuses on the more recent development in motion estimation methods. Furthermore, an algorithm based on sub-pixel image registration that estimates the displacements of the LR image is presented. The critical steps in image registration are collecting feature points and estimating a spatial transformation especially when outliers are present. In this paper, the Harris corner detector is used to find the feature points and then the point feature is described by the neighborhood difference in order to reduce the sensitivity to illumination variations. Moreover, the Random Sample Consensus(RANSAC) algorithm is employed to build a transformation model. Simulation results demonstrate that the method can estimate the displacements accurately.
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