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.
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Showing 1 to 20 of 78 for “"image restoration"”.
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Estimation theoretical image restoration
… we have developed an extensive study to evaluate image restoration from a single image, colored or monochromatic. Using a mixture of Gaussian and Poisson noise process, we derived an objective function to estimate the unknown object and point spread function (psf) parameters. We have found that, …
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The Image Restoration of BP
… this study was guided by relevant literature in image restoration theory, framing theory, and the situational crisis communication theory. Then, a qualitative content analysis of BP press releases, commericals, and newspaper articles highlighted the relationship between the image restoration …
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Optimization Techniques for Image Restoration
Many fields of study use images to make discoveries about the past, decisions for the present and predictions for the future. Images often acquire degradations such as a blur due to a patient moving during an x-ray or noise picked up through remote sensing imaging equipment. Images may also lose …
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Deep Learning For Microscopic Image Restoration
… to conventional widefield microscopy. SR-SIM images are reconstructed by combining several raw SIM images, which were exposed to patterned illumination with high modulation contrast, in the frequency domain. Noisy raw image data, e.g. due to low laser excitation power or short exposure times, …
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Deconvolution and sparsity based image restoration
… sparse representation are the two key areas in image and signal processing. In this thesis the classical image restoration problem is addressed using these two modalities. Image restoration, such as deblurring, dnoising, and in-painting belongs to the class of ill-posed linear inverse problems, …
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Deconvolution and sparsity based image restoration
… sparse representation are the two key areas in image and signal processing. In this thesis the classical image restoration problem is addressed using these two modalities. Image restoration, such as deblurring, dnoising, and in-painting belongs to the class of ill-posed linear inverse problems, …
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Techniques in image restoration and enhancement
Image processing in its broad sense pervades many areas but it is convenient to group it into three main sections, viz: image coding, usually for image transmission over telecommunication links; pattern recognition for detecting the presence of a particular distribution in an image which is …
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Facial image restoration and retrieval through orthogonality
… how to incorporate orthogonality to facial image restoration and retrieval tasks. A facial image restoration method and three retrieval methods were proposed. Blur in facial images significantly impedes the efficiency of recognition approaches. However, most existing blind deconvolution …
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Deep learning for image restoration and enhancement
Image restoration is the process of recovering an original clean image from its degraded version, and image enhancement takes the goal of improving the image quality either objectively or subjectively. Both of them play a key part in computer vision and image processing and have broad applications …
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One-dimensional processing for adaptive image restoration
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1984.
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Structure guided image restoration : a deep learning approach
Image restoration aims at recovery of degraded images and estimating the original. Over the past few years, computer vision research has been dominated by deep learning techniques in part due to advances in computing infrastructure, algorithms and image capturing devices. As a result, deep neural …
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Image restoration using sub-images and confidence intervals
<p>In applications, images are recorded, blurred, and noisy. This work aims to compute confidence intervals for quantifying the uncertainty of a reconstructed image. By partitioning the image into sub-images, the algorithm remains effective while becoming more efficient. Sub-images also provide …
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Robust Methods for Image Restoration and Edge Detection
… with the problem of noise in various aspects of image processing and computer vision.
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Towards practical deep learning based image restoration model
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-04-06 without embargo terms
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Integration of Model- and Learning-based Methods in Image Restoration
… success of deep learning algorithms in image restoration tasks, there is growing interest in exploring how to combine the practical advantages of learning-based methods with the theoretical understanding that comes from model-based approaches. In fact, while deep learning methods often …
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