Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 33 for “"deblurring"”.
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Optical flow using phase information for deblurring
… When accurate 2D velocities are provided, the deblurring process generates sharp results for most types of motion. The magnitude error proved to be a larger problem than the angular error, due to the averaging process involved in creating the 2D velocity vectors from the component velocities. …
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Image enhancement methods and applications in computational photography
… focus stacking, super-resolution, motion deblurring and so on. Although extensive work has been done to explore image enhancement techniques in each subfield of computational photography, attention has seldom been given to study of the image enhancement technique of simultaneously …
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Architectures for computational photography
… low light enhancement, panorama stitching, image deblurring and light field photography. These techniques have so far been software based, which leads to high energy consumption and typically no support for real-time processing. This work focuses on hardware architectures for two algorithms - (a) …
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Programmable Aperture Photography: An investigation into applications and methods
… for use in various applications such as defocus deblurring, depth estimation and light field acquisition. Traditional coded aperture masks are constructed from static materials such as cardboard and cannot be altered once their shapes have been defined. These masks are then physically inserted …
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Modeling and Analysis of Optical Blur for Everyday Photography
… such information --- optical calibration, image deblurring, and depth estimation -- is of great interest to computer vision. Existing approaches make impractical assumptions about the camera and the scene, and are therefore restricted to lab settings. In this thesis, we propose novel optical blur …
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Automatic Computational Techniques for Image Processing Problems
… (TV) method for image denoising and deblurring problems. In traditional TV-based models, it is not easy to systemically provide a choice of parameters for the system. Inspired by the ideas from machine learning, we design a new learning-based TV model where the parameters can be …
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Energy-efficient circuits and systems for computational imaging and vision on mobile devices
… range (HDR) imaging, panorama stitching, image deblurring and low-light imaging that compensate for camera limitations, and a number of deep learning based vision algorithms such as face recognition, object recognition and scene understanding that make inference on these images for a variety of …
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Computation tools for the Fourier transform infrared (FT-IR) spectroscopic imaging
… This thesis focuses on denoising and deblurring absorbance images of the Fourier transform infrared spectroscopy for improved spatial resolution while maintaining spectral quality. In addition, it aims to speed up data-acquisition by deploying state-of-the-art computational tools such …
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Deconvolution and sparsity based image restoration
… these two modalities. Image restoration, such as deblurring, dnoising, and in-painting belongs to the class of ill-posed linear inverse problems, which requires a proper regularization for a credible solution. The aim is to develop techniques that are stable, practical and require a minimum amount …
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Deconvolution and sparsity based image restoration
… these two modalities. Image restoration, such as deblurring, dnoising, and in-painting belongs to the class of ill-posed linear inverse problems, which requires a proper regularization for a credible solution. The aim is to develop techniques that are stable, practical and require a minimum amount …
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Numerical Methods for Separable Nonlinear Inverse Problems with Constraint and Low Rank
… and so on. For example, image reconstruction and deblurring require the use of methods to solve inverse problems. Since the problems are subject to many factors and noise, we can't simply apply general inversion methods. Furthermore in the problems of interest, the number of unknown variables is …
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Techniques for high-speed high-resolution in-vivo volumetric fluorescence imaging
… diffractive optical element (DOE), (2) an image deblurring algorithm termed Deblurring by Pixel Reassignment (DPR). Together, these methods aim to expand the capabilities of optical microscopy for high-speed, high-resolution, and quantitative imaging across complex biological samples. In the …
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Medical image enhancement
… is considered a serious problem. Therefore, “deblurring” an image to obtain better quality is an important issue in medical image processing. In our research, the image is initially decomposed. Contrast improvement is achieved by modifying the coefficients obtained from the decomposed image. …
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Inverse filtering by signal reconstruction from phase
… transform. We will investigate a new method of deblurring images based only on phase data. It will be shown that this method is much more robust in the presence of noise than existing methods and that, because no magnitude information is required, it is also more robust to an incorrect guess of …
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On fundamental computational barriers in the mathematics of information
… pursuit, linear programming, lasso and image deblurring as well as finding an optimal neural network given training data. These results are somewhat paradoxical given the success that existing algorithms exhibit when tackling these problems with real world datasets and a substantial portion of …
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A General Framework of Large-Scale Convex Optimization Using Jensen Surrogates and Acceleration Techniques
… including Sparse Linear Regression (Image Deblurring), Positron Emission Tomography, X-Ray Transmission Tomography, Logistic Regression, Sparse Logistic Regression and Automatic Relevance Determination for X-Ray Transmission Tomography.</p>
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Bayesian approaches to bilinear inverse problems involving spatial evidence : color constancy and blind image deconvolution
… the latter, we consider the specific instance of deblurring, in which we seek to separate the effect of blur caused by camera motion from all other image properties in order to produce a sharp image from a blurry one. Both problems share the common characteristic of being bilinear inverse …
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wavelet domain inversion and joint deconvolution/interpolation of geophysical data
… allows for sparsely sampled data to aid in image deblurring problems, or, conversely, noisy and blurred data to aid in sample interpolation. In order to overcome difficulties arising from high dimensionality, the solution must be derived in the correct framework and the structure of the problem …
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Point Spread Function Engineering for Scene Recovery
… blur-free image and a PSF, and deconvolution (or deblurring) techniques have to be used to recover image details from a blurry region. Here, I propose a comprehensive framework of PSF evaluation for the purpose of image deblurring, in which the effects of image noise, deblurring algorithm, and the …
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Inertial iterative thresholding with applications to sparse and low-rank signal recovery
… examples include total variation denoising and deblurring, and L`1-regularized regression. Iterative thresholding methods have low complexity, but they typically take many iterations to converge, especially on ill-conditioned problems. In this thesis we explore how inertia can be used to …
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