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Please use this identifier to cite or link to this item: http://hdl.handle.net/10481/43889

Title: Image super resolution using compressed sensing observations
Authors: Alsaafin, Wael Hasan Abdallah
Direction: Vega López, Miguel
Molina Soriano, Rafael
Collaborator: Universidad de Granada. Departamento de Ciencias de la Computación e Inteligencia Artificial
Issue Date: 2016
Submitted Date: 25-May-2016
Abstract: Compressed Sensing (CS) is a new technology that simultaneously acquires and compresses images reducing acquisition time and memory requirements to process or transmit them. It es- tablishes that a sparsely representable image/signal can be recovered from a highly incomplete set of measurements or projections of the image. Image Super Resolution (SR) is an important post-processing technique where multiple input images are super resolved to obtain one or more images of higher resolution and better quality. SR necessitates a good image registration procedure in order to obtain a High Resolution (HR) image of enhanced quality. Such quality should overcome image degradation due to system hardware, optical and spatial limitations. In this dissertation we propose a novel framework to obtain HR images from CS imaging systems capturing multiple Low Resolution (LR) images of the same scene. The assumption that when an image admits a sparse representation in a transformed domain, a blurred version of it will also be sparse in the transformed domain allows us to recover blurred images from CS observations Similarly, a warped, blurred, and down-sampled LR image is expected to be also sparse in a transformed domain and hence can be reconstructed from the corresponding CS observation. The proposed Compressed Sensing Super Resolution (CSSR) approach, combines existing CS reconstruction algorithms with an LR to HR approach based on the use of a new robust sparsity promoting prior based on super Gaussian regularization.
Sponsorship: Tesis Univ. Granada. Programa Oficial de Doctorado en: Tecnologías de la Información y la Comunicación
Publisher: Universidad de Granada
Keywords: Imágenes
Tratamiento digital de imágenes
Resolución (Optica)
Color
Algoritmos
Procesado de imágenes
Compresión
UDC: 77
070
(043.2)
120309
URI: http://hdl.handle.net/10481/43889
ISBN: 9788491259213
Rights : Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License
Citation: Alsaafin, W.H.A. Image super resolution using compressed sensing observations. Granada: Universidad de Granada, 2016. [http://hdl.handle.net/10481/43889]
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