A comparison of phase unwrapping techniques in synthetic aperture radar interferometry

A comparison of different phase unwrapping techniques based on the least mean square error is presented. A testing environment based on simulated interferograms has been created in order to assess the methods described in the literature. Each of them has shown good properties under different constraints. Multigrid with a previous adaptive maximum likelihood gradient estimation is very robust when strong aliasing is not expected. In a general scenario with aliasing, an adaptive multiresolution gradient estimator gives a coarse approximation to the low resolution topography.Peer ReviewedPostprint (published version

Master of Science

thesisConsistency analysis and data collaboration is a relatively new scientific area. It deals with quantifying how well scientific models approximate empirical reality. Consistency analysis is based on methodically comparing model predictions with experimental measurements, but this task is made more difficult by the fact that both models and experiments have their own inherent uncertainties. Computational fluid dynamics (CFD) models are numerical methods able to solve complicated discrete fluid dynamics problems. They are used thoroughly in mechanical, aerospace and energy science. As CFD models are being applied to more and more critical systems, there is a growing need to improve the reliability of CFD model predictions. This work addresses this need by presenting consistency analysis results for a simple CFD model and an experiment in which the concentration field of a buoyant helium plume had been studied by holographic interferometry. A detailed procedure is presented for carrying out data collaboration between simulation and experimental data. This work is novel in a sense that it is the first to present the specific difficulties of collaborating interferometric data. These difficulties arise from the encoded nature of information being present in interferometric fringe images

Phase Unwrapping Citra Insar Menggunakan Pendekatan Minimisasi Energi Lokal

Phase Unwrapping InSAR Image Using Local Energy Minimization Approach. Reconstruction process of phasedata from its cover is called Phase Unwrapping (PU). Ideally, without any noise phrase, singularity, and aliasingproblems, the phase information can be unwrapped easily. However, in fact, the phase data actually always get noisedisturbance and discontinuity. The PU process becomes more complicated and needs a better PU algorithm to addressthe problems properly. In this research, the local PU algorithm is developed using minimization of close related firstorderpixels energy approach. In this method, the energy difference between four close related pixels is counted,followed by getting the probability value to obtain its total multiple ranges. Based on the research using synthesis ringimage and InSAR with coherence 0.8, the Peak Signal to Noise Ratio (PNSR) range will be 30.5373 dB in 20 itteration

Temporal phase unwrapping using deep learning

The multi-frequency temporal phase unwrapping (MF-TPU) method, as a classical phase unwrapping algorithm for fringe projection profilometry (FPP), is capable of eliminating the phase ambiguities even in the presence of surface discontinuities or spatially isolated objects. For the simplest and most efficient case, two sets of 3-step phase-shifting fringe patterns are used: the high-frequency one is for 3D measurement and the unit-frequency one is for unwrapping the phase obtained from the high-frequency pattern set. The final measurement precision or sensitivity is determined by the number of fringes used within the high-frequency pattern, under the precondition that the phase can be successfully unwrapped without triggering the fringe order error. Consequently, in order to guarantee a reasonable unwrapping success rate, the fringe number (or period number) of the high-frequency fringe patterns is generally restricted to about 16, resulting in limited measurement accuracy. On the other hand, using additional intermediate sets of fringe patterns can unwrap the phase with higher frequency, but at the expense of a prolonged pattern sequence. Inspired by recent successes of deep learning techniques for computer vision and computational imaging, in this work, we report that the deep neural networks can learn to perform TPU after appropriate training, as called deep-learning based temporal phase unwrapping (DL-TPU), which can substantially improve the unwrapping reliability compared with MF-TPU even in the presence of different types of error sources, e.g., intensity noise, low fringe modulation, and projector nonlinearity. We further experimentally demonstrate for the first time, to our knowledge, that the high-frequency phase obtained from 64-period 3-step phase-shifting fringe patterns can be directly and reliably unwrapped from one unit-frequency phase using DL-TPU

Applications of SAR Interferometry in Earth and Environmental Science Research

This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions

Un nuovo algoritmo di Phase Unwrapping basato sulla crescita competitiva di regioni

The phase unwrapping problem arises every time one has to analyse experimental data acquired by means of techniques based on periodical phenomena, from the opto-interferometric ones to some geologycal or medical techniques. This paper presents a new phase unwrapping algorithm based on the competitive region growing: starting from an equipotential condition, it makes an area to absorb its neighbours by mean of a quality parameter based on the extension and the coherency of the regions. After a short description of the phase unwrapping problem and of some of the most used techniques, this paper describes the working principle of the algorithm and the implementation details. The paper ends with some examples of applications of the algorithm on synthetic images

Investigation of symmetry attribute analysis on the phase measurements of marine controlled-sourceelectromagnetic surveys

In this paper we study the potential of symmetry attribute analysis applied to the phase component of electric field observations of marine controlled-source electromagnetic data. The effectiveness of symmetry attribute analysis on the phase component of marine controlled-source electromagnetic data in detecting the boundaries of resistive layer(s), such as hydrocarbon accumulation, is investigated. A comparison between symmetry attribute analysis on the phase and magnitude component of 2.5D synthetic data and a real data set is also discussed. The results presented a clear response indicative of the locations of the subsurface resistors. The phase symmetry attribute analysis proved to be effective for qualitative detection of the lateral extent of embedded resistors

Aiding phase unwrapping by increasing the number of residues in two-dimensional wrapped-phase distributions

In phase unwrapping residues are points of locally inconsistent phase that occur within a wrapped-phase map, which are usually regarded as being problematic for phase-unwrapping algorithms. Real phase maps typically contain a number of residues that are approximately proportional to the subsequent difficulty in unwrapping the phase distribution. This paper suggests the radical use of the discrete Fourier transform to actually increase the number of residues in 2D phase-wrapped images that contain discontinuities. Many of the additional residues that are artificially generated by this method are located on these discontinuities. For example, in fringe projection systems, such phase discontinuities may come from physical discontinuity between different parts of the object, or by shadows cast by the object. The suggested technique can improve the performance of path independent phase-unwrapping algorithms because these extra residues simplify the process of setting the branch cuts in the wrapped image based on the distance to the nearest residue. The generated residues can also be used to construct more reliable quality maps and masks. The paper includes an initial analysis upon simulated phase maps and goes on to verify the results on a real experimental wrapped-phase distribution

Ground-based synthetic aperture radar (GBSAR) interferometry for deformation monitoring

Ph. D ThesisGround-based synthetic aperture radar (GBSAR), together with interferometry, represents a powerful tool for deformation monitoring. GBSAR has inherent flexibility, allowing data to be collected with adjustable temporal resolutions through either continuous or discontinuous mode. The goal of this research is to develop a framework to effectively utilise GBSAR for deformation monitoring in both modes, with the emphasis on accuracy, robustness, and real-time capability. To achieve this goal, advanced Interferometric SAR (InSAR) processing algorithms have been proposed to address existing issues in conventional interferometry for GBSAR deformation monitoring. The proposed interferometric algorithms include a new non-local method for the accurate estimation of coherence and interferometric phase, a new approach to selecting coherent pixels with the aim of maximising the density of selected pixels and optimizing the reliability of time series analysis, and a rigorous model for the correction of atmospheric and repositioning errors. On the basis of these algorithms, two complete interferometric processing chains have been developed: one for continuous and the other for discontinuous GBSAR deformation monitoring. The continuous chain is able to process infinite incoming images in real time and extract the evolution of surface movements through temporally coherent pixels. The discontinuous chain integrates additional automatic coregistration of images and correction of repositioning errors between different campaigns. Successful deformation monitoring applications have been completed, including three continuous (a dune, a bridge, and a coastal cliff) and one discontinuous (a hillside), which have demonstrated the feasibility and effectiveness of the presented algorithms and chains for high-accuracy GBSAR interferometric measurement. Significant deformation signals were detected from the three continuous applications and no deformation from the discontinuous. The achieved results are justified quantitatively via a defined precision indicator for the time series estimation and validated qualitatively via a priori knowledge of these observing sites.China Scholarship Council (CSC), Newcastle Universit

Efficient Phase Unwrapping Architecture for Digital Holographic Microscopy

This paper presents a novel phase unwrapping architecture for accelerating the computational speed of digital holographic microscopy (DHM). A fast Fourier transform (FFT) based phase unwrapping algorithm providing a minimum squared error solution is adopted for hardware implementation because of its simplicity and robustness to noise. The proposed architecture is realized in a pipeline fashion to maximize throughput of the computation. Moreover, the number of hardware multipliers and dividers are minimized to reduce the hardware costs. The proposed architecture is used as a custom user logic in a system on programmable chip (SOPC) for physical performance measurement. Experimental results reveal that the proposed architecture is effective for expediting the computational speed while consuming low hardware resources for designing an embedded DHM system