Adaptive filter for unwrapping noisy phase image in phase-stepping interferometry (original) (raw)
Related papers
Interferogram phase noise reduction using morphological and modified median filters
1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications, 1995
Phase unwrapping for S A R Interferometry is one of the barriers for obtaining an operational interferometric S A R system (MAR). For filtering the phase one uses mainly a low pass linear filter applied on the complex interferometric image before evaluating the phase. This paper compares three different non linear methods which filter the wrapped phase map. The first method is based on a morphological filter, the second one is a modified median filter and the third is a modified mode filter. All filters are built considering the periodic character of the wrapped phase function. The characteristics of these filtering approaches are compared, and the number of residues are calculated after each filtering step.
Applied Optics, 2011
A method to construct an unweighted quality map for phase extraction and phase unwrapping is proposed, based on an object image pattern. The object image pattern must be recorded under the same conditions as that of the corresponding interference patterns, except that the lights coming from the reference arm of the interferometer are hidden. An unweighted quality map that can represent the valid and invalid regions in the interference patterns is completed successfully, based on two factors: the fact that the object region in the object image pattern is homologous with the valid region (i.e., the interference region) in the interference patterns, and on distinguishing between the object and background regions in the object image pattern using neighbor window threshold filtering and fitting the boundary of the object image. The application of the proposed method to the real measurement shows its feasibility and correctness. This paper might provide an alternative method for constructing an unweighted quality map for phase extraction and phase unwrapping.
A new technique for noise filtering of SAR interferometric phase images
IEEE Transactions on Geoscience and Remote Sensing, 1998
This paper addresses the noise filtering problem for synthetic aperture radar (SAR) interferometric phase images. The phase noise is characterized by an additive noise model. The model is verified with an L-band shuttle imaging radar (SIR)-C interferogram. An adaptive filtering algorithm based on this noise model is developed. It emphasizes filtering noise adaptively according to the local noise level and filtering along fringes using directionally dependent windows. This algorithm is effective, especially for the tightly packed fringes of X-band interferometry. Using simulated and SIR-C/X-SAR repeat-pass generated interferograms, the effectiveness of this filter is demonstrated by its capabilities in residue reduction, adaptive noise filtering, and its ability to filter areas with high fringe rates. In addition, a scheme of incorporating this filtering algorithm in iterative phase unwrapping using a least-squares method is proposed.
We propose a statistical phase-shifting estimation algorithm for temporal phase-shifting interferometry (PSI) based on the continuous wavelet transform (CWT). The proposed algorithm explores spatial information redundancy in the intraframe interferogram dataset using the phase recovery property on the power ridge of the CWT. Despite the errors introduced by the noise of the interferogram, the statistical part of the algorithm is utilized to give a sound estimation of the phase-shifting step. It also introduces the usage of directional statistics as the statistical model, which was validated, so as to offer a better estimation compared with other statistical models. The algorithm is implemented in computer codes, and the validations of the algorithm were performed on numerical simulated signals and actual phase-shifted moiré interferograms. The major advantage of the proposed algorithm is that it imposes weaker conditions on the presumptions in the temporal PSI, which, under most circumstances, requires uniform and precalibrated phase-shifting steps. Compared with other existing deterministic estimation algorithms, the proposed algorithm estimates the phase-shifting step statistically. The proposed algorithm allows the temporal PSI to operate under dynamic loading conditions and arbitrary phase steps and also without precalibration of the phase shifter. The proposed method can serve as a benchmark method for comparing the accuracy of the different phase-step estimation methods.
Phase-unwrapping algorithm for noisy phase-map processing
Applied Optics, 1994
Automated fringe-pattern processing is important in a great number of industrial applications, such as optical data testing and quality control. One of the main problems that arises with these processes is the automated phase unwrapping of the phase map associated with the fringe pattern. Usually the phase map presents problems such as noise, and low-modulation areas. A new phase-unwrapping algorithm with high noise immunity is presented. The algorithm is easily implemented and can process arbitrary shapes. The main features of this algorithm are the use of a queue for the processing of arbitrary shapes and a selection criterion that determines which pixels are going to be processed.
Applied Optics, 2012
A simple phase estimation employing cubic and average interpolations to solve the oversampling problem in smooth modulated phase images is described. In the context of a general phase-shifting process, without phase-unwrapping, the modulated phase images are employed to recover wavefront shapes with high fringe density. The problem of the phase reconstruction by line integration of its gradient requires a form appropriate to the calculation of partial derivatives, especially when the phase to recover has higher-order aberration values. This is achieved by oversampling the modulated phase images, and many interpolations can be implemented. Here an oversampling procedure based on the analysis of a quadratic cost functional for phase recovery, in a particular case, is proposed.
Highlighting properties of filters for their application in temporal phase shifting interferometry
SPIE Proceedings, 2005
The goal of this work is to develop a simple and systematic method to highlight the properties of filters for their application in temporal phase shifting interferometry. In this study, the effects of elementary filters (mean, gaussian and median masks) are analyzed. In order to compare those filters, correlation fringes were numerically synthesized and a Gaussian noise has been added. The advantages and the failures of each studied filtering mask have been enhanced thanks to the comparison of different profiles and fidelity functions. Finally, this study is applied to the filtering of a shearogram recorded in our laboratory.
2D simultaneous phase unwrapping and filtering: A review and comparison
Optics and Lasers in Engineering, 2012
In optical metrology, most phase demodulation methods recover the phase wrapped in the range ½Àp,p. But actually the phase is a smooth surface that exceeds this dynamic range. Therefore, it is necessary to use a phase unwrapping method to recover the desired smooth phase surface. Here we show a performance between our Recursive Phase Unwrapping (RPU) system, the well known Goldstein branch-cut unwrapping method and the Regularized Phase Tracker (RPT). The RPU is a Infinite Impulse Response system that simultaneously unwraps and low-pass filters the wrapped phase. Unlike branch-cut methods, our RPU system does not need mark phase inconstancies for successfully unwrap the phase. We will see that the RPU is a novel practical, fast, and robust solution for the phase unwrapping problem in two-dimensions (2D).
Filtering algorithm for noise reduction in phase-map images with 2π phase jumps
Applied optics, 1998
A filtering algorithm is proposed for processing images generated by TV holography that contain phase jumps and a high noise level. This algorithm first performs phase unwrapping without removing the noise. After that, it removes the noise by use of a conventional low-pass filter. The new approach allows for using low-pass filters with narrow passbands, leading to a better signal-to-noise ratio in the desired signal. Simulation results are presented and discussed. The new algorithm has been applied successfully under real conditions in a holographic station.