Abstract
The growing interest in the applications of digital holography interferometry has led to an increasing demand for reliable phase unwrapping techniques. In digital holography, the phase carries three-dimensional surface information about the object. However, phase mapping is ambiguous as the extracted phase is returned in a form that suffers from 2π phase jumps. Furthermore, the presence of noise in the measured data, in which many singular points (SP) are found, often makes general phase unwrapping algorithms fail to produce accurate unwrapped results. Therefore, it is necessary to use a powerful phase unwrapping method to recover the desired smooth phase surface. For this reason, we developed a phase unwrapping algorithm that is applicable to digital hologram maps. The developed algorithm solves the singularity problem caused by SPs as a result of compensating its effect by using rotational and direct compensators. We show a difference in performance between our developed phase unwrapping algorithm and other well known phase unwrapping methods for digital holographic data. In addition, the methods to extract phase information of the object from hologram maps are also investigated. Results show that the developed algorithm gives satisfactory unwrapped results with low computational time cost.
Highlights
Many techniques allow the measurement of physical properties based on the retrieval of phase information encoded in an interference pattern
We focus on digital holography interferometry techniques.[5]
The other is the experimental data obtained with interferometer to demonstrate the performance of the rotational compensators (RC) þ direct compensator (DC) method for holographic data
Summary
Many techniques allow the measurement of physical properties based on the retrieval of phase information encoded in an interference pattern. The second category includes methods which use the least-squares approach.[15,16,17,18,19,20,21] These algorithms use the same idea of minimization of discrete gradients difference squares as used in the leased-squares approach These differences are taken between the wrapped phase gradients and supposed unwrapped phase gradients. The last category is denoising-unwrapping methods.[26,27,28,29] This type of methods performs phase map denoising to remove noise from wrapped phase by using a filtering process.
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