Nonnegative and Volume Constrained Image Deblurring Pubblico

Lin, Lu (2016)

Permanent URL: https://etd.library.emory.edu/concern/etds/k3569472r?locale=it
Published

Abstract

In this thesis, we discuss iterative algorithms that can be used for constrained image deblurring. We mainly focus on the gradient projection method, which combines gradient descent with projections that implement constraints, such as nonnegative and volume constraints. Numerical experiments on three test problems using MATLAB illustrate the effctiveness and the efficiency of these methods.

Table of Contents

1 Introduction

1.2 Iterative Methods. 2

1.3 Image Deblurring. 3

2 Gradient Projection Methods

2.1 Gradient Descent Method. 8

2.2 Nonnegative Projection. 12

2.3 Conjugate Gradient Method for Least Squares. 13

3 Projection for Volume and Nonnegative Constraints

3.1 Nonnegative and Volume Projection. 15

3.1.1 Lagrange Multiplier Approach. 16

3.1.2 Newton's Method for finding ρ. 17

3.1.3 Initial Guess of ρ. 17

4 Numerical Experiments

4.1 TestProblem: Satellite. 20

4.1.1 Methods Comparison. 20

4.1.2 Efficiency of the NNV Projection. 23

4.2 TestProblem: StarCluster. 26

4.2.1 Methods Comparison. 26

4.2.2 Efficiency of the NNV Projection. 30

4.3 TestProblem: Grain. 31

4.3.1 Methods Comparison. 31

5 Conclusion and Discussion

About this Honors Thesis

Rights statement
  • Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.
School
Department
Degree
Submission
Language
  • English
Research Field
Parola chiave
Committee Chair / Thesis Advisor
Committee Members
Ultima modifica

Primary PDF

Thumbnail Title Date Uploaded Actions
Nonnegative and Volume Constrained Image Deblurring () 2018-08-28 12:00:26 -0400

Supplemental Files

Thumbnail Title Date Uploaded Actions