Abstract

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.

Highlights

  • The ability to measure the phase of a complex physical signal is a key advantage of imaging methods such as digital holography [1], interferometric synthetic aperture radar (InSAR) [2], PLOS ONE | DOI:10.1371/journal.pone

  • We propose to solve the least squares fitting problem by casting it into a linear system that is solved with singular value decomposition (SVD)

  • We have presented a modular tile-based phase unwrapping approach that was cast into a C++11 program with a modular framework

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Summary

Introduction

The ability to measure the phase of a complex physical signal is a key advantage of imaging methods such as digital holography [1], interferometric synthetic aperture radar (InSAR) [2], PLOS ONE | DOI:10.1371/journal.pone.0143186 November 24, 2015Modular Tile-Based Phase Unwrapping Framework or magnetic resonance imaging [3]. Due to the 2π periodicity of a phase map, the resulting measurement typically yields the true phase modulo 2π. Such a phase map is called wrapped and will show distinctive jumps (wraps) of magnitude 2π. Phase unwrapping is the process of removing the 2π ambiguity from the wrapped phase map. This process is trivial for the one dimensional case, but it becomes extremely challenging in two dimensions, even more so when measurement errors deteriorate the quality of the wrapped phase map [4]. Phase unwrapping has been studied for decades, yet due to a growing number of applications, it remains an active area of research until today [5,6,7,8,9]

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