DOI
10.17077/etd.ca6e-j1fx
Document Type
Dissertation
Date of Degree
Fall 2018
Access Restrictions
Access restricted until 01/31/2021
Degree Name
PhD (Doctor of Philosophy)
Degree In
Applied Mathematical and Computational Sciences
First Advisor
Cai, Jian-Feng
Second Advisor
Xu, Weiyu
First Committee Member
Jay, Laurent
Second Committee Member
Jorgensen, Palle
Third Committee Member
Li, Tong
Abstract
Two efficient models in two-dimensional signal processing are proposed in the thesis.
The first model deals with large scale spectral compressive sensing in continuous domain, which aims to recover a 2D spectrally sparse signal from partially observed time samples. The signal is assumed to be a superposition of s complex sinusoids. We propose a semidefinite program for the 2D signal recovery problem. Our model is able to handle large scale 2D signals of size 500*500, whereas traditional approaches only handle signals of size around 20*20.
The second model deals with the problem of single image reflection suppression. Removing the undesired reflection from images taken through glass is of great importance in computer vision. It serves as a means to enhance the image quality for aesthetic purposes as well as to preprocess images in machine learning and pattern recognition applications. We propose a convex model to suppress the reflection from a single input image. Our model implies a partial differential equation with gradient thresholding, which is solved efficiently using Discrete Cosine Transform. Extensive experiments on synthetic and real-world images demonstrate that our approach achieves desirable reflection suppression results and dramatically reduces the execution time compared to the state of the art.
Keywords
compressive sensing, image processing, reflection removal, signal processing
Pages
x, 79 pages
Bibliography
Includes bibliographical references (pages 76-79).
Copyright
Copyright © 2018 Yang Yang
Recommended Citation
Yang, Yang. "2D signal processing: efficient models for spectral compressive sensing & single image reflection suppression." PhD (Doctor of Philosophy) thesis, University of Iowa, 2018.
https://doi.org/10.17077/etd.ca6e-j1fx
Comments
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