Convex optimization-based blind deconvolution for images taken with coherent illumination

Journal article (2019)

Authors

R. Doelman Team Raf Van de Plas - Mechanical, Maritime and Materials Engineering
M.H.G. Verhaegen Team Raf Van de Plas - Mechanical, Maritime and Materials Engineering
Research Group
Team Raf Van de Plas (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2019 R. Doelman, M.H.G. Verhaegen
DOI: https://doi.org/10.1364/JOSAA.36.000678
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Published Date

2019

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Raf Van de Plas

Abstract

A rank-constrained reformulation of the blind deconvolution problem on images taken with coherent illumination is proposed. Since in the reformulation the rank constraint is imposed on a matrix that is affine in the decision variables, we propose a novel convex heuristic for the blind deconvolution problem. The proposed heuristic allows for easy incorporation of prior information on the decision variables and the use of the phase diversity concept. The convex optimization problem can be iteratively re-parameterized to obtain better estimates. The proposed methods are demonstrated on numerically illustrative examples.

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