Tile-Based Two-Dimensional Phase Unwrapping for Digital Holography Using a Modular Framework


Autoria(s): Antonopoulos, Georgios C.; Steltner, Benjamin; Heisterkamp, Alexander; Ripken, Tammo; Meyer, Heiko; Zhang, Heye
Data(s)

2015

Resumo

A variety of physical and biomedical imaging techniques, such as digital holography, interferometric synthetic aperture radar (InSAR), or magnetic resonance imaging (MRI) enable measurement of the phase of a physical quantity additionally to its amplitude. However, the phase can commonly only be measured modulo 2π, as a so called wrapped phase map. Phase unwrapping is the process of obtaining the underlying physical phase map from the wrapped phase. Tile-based phase unwrapping algorithms operate by first tessellating the phase map, then unwrapping individual tiles, and finally merging them to a continuous phase map. They can be implemented computationally efficiently and are robust to noise. However, they are prone to failure in the presence of phase residues or erroneous unwraps of single tiles. We tried to overcome these shortcomings by creating novel tile unwrapping and merging algorithms as well as creating a framework that allows to combine them in modular fashion. To increase the robustness of the tile unwrapping step, we implemented a model-based algorithm that makes efficient use of linear algebra to unwrap individual tiles. Furthermore, we adapted an established pixel-based unwrapping algorithm to create a quality guided tile merger. These original algorithms as well as previously existing ones were implemented in a modular phase unwrapping C++ framework. By examining different combinations of unwrapping and merging algorithms we compared our method to existing approaches. We could show that the appropriate choice of unwrapping and merging algorithms can significantly improve the unwrapped result in the presence of phase residues and noise. Beyond that, our modular framework allows for efficient design and test of new tile-based phase unwrapping algorithms. The software developed in this study is freely available.

Identificador

http://dx.doi.org/10.15488/299

http://www.repo.uni-hannover.de/handle/123456789/321

Idioma(s)

eng

Publicador

San Francisco : Public Library Science

Relação

http://dx.doi.org/10.1371/journal.pone.0143186

ESSN:1932-6204

Direitos

CC BY 4.0

http://creativecommons.org/licenses/by/4.0/

frei zugänglich

Fonte

PloS ONE 10 (2015), Nr. 11

Palavras-Chave #algorithms #holography #polynomial #Gaussian noise #linear algebra #physical mapping #magnetic resonance imaging #machine learning algorithms #ddc:600
Tipo

status-type:publishedVersion

doc-type:article

doc-type:Text