基于最小费用流的InSAR干涉相位展开算法

从影响InSAR干涉相位展开算法的相干系数出发,分析了相干系数对干涉处理的影响,提出了基于新的加权系数矩阵的最小费用流算法,定义了新的加权系数矩阵并分析其性能,使得加权系数矩阵不再随着幅度的变化而变化,减小了相干系数较小时对干涉相位展开的不利影响。通过仿真和实测数据检验本方法的处理性能,可以获得较好的相位展开处理效果。     

Phase unwrapping via graph cuts.

Phase unwrapping is the inference of absolute phase from modulo-2pi phase. This paper introduces a new energy minimization framework for phase unwrapping. The considered objective functions are first-order Markov random fields. We provide an exact energy minimization algorithm, whenever the corresponding clique potentials are convex, namely for the phase unwrapping classical Lp norm, with p > or = 1. Its complexity is KT (n, 3n), where K is the length of the absolute phase domain measured in 2pi units and T (n, m) is the complexity of a max-flow computation in a graph with n nodes and m edges. For nonconvex clique potentials, often used owing to their discontinuity preserving ability, we face an NP-hard problem for which we devise an approximate solution. Both algorithms solve integer optimization problems by computing a sequence of binary optimizations, each one solved by graph cut techniques. Accordingly, we name the two algorithms PUMA, for phase unwrappping max-flow/min-cut. A set of experimental results illustrates the effectiveness of the proposed approach and its competitiveness in comparison with state-of-the-art phase unwrapping algorithms.     

InSAR相位解缠最小二乘算法的研究

相位解缠是干涉合成孔径雷达（InSAR）测量地形高程的重要步骤之一。由噪声和欠采样导致的相位不一致性问题是相位解缠的难点。本文分析了相位解缠最小二乘算法的原理和性质,总结了算法的优缺点。最后采用加拿大RadarSatl数据进行实验,验证了分析的结果。     

2-D phase unwrapping and instantaneous frequency estimation

The phase of complex signals is wrapped since it can only be measured modulo-2π; unwrapping searches for the 2π-combinations that minimize the discontinuity of the unwrapped phase, as only the unwrapped phase can be analyzed and interpreted by further processing. Given an estimate of the phase gradient (i.e., of the instantaneous frequency), the 2-D unwrapped phase can be obtained as a solution of a variational problem. The analysis of unwrapping is done quite separately from instantaneous frequency estimation so that the reliability of both steps can be assessed independently. Various methods for evaluating 2-D instantaneous frequency are presented and compared in the presence of noise and amplitude variations. A study has also been made on aliasing arising in areas where, with respect to instantaneous frequency, spatial sampling is insufficient. The presence of noise in the data further complicates phase aliasing analysis since there is no way to distinguish between the aliasing due to noise or that due to steep phase slopes     

Residues cluster-based segmentation and outlier-detection method for large-scale phase unwrapping

2-D phase unwrapping is an important technique in many applications. However, with the growth of image scale, how to tile and splice the image effectively has become a new challenge. In this paper, the phase unwrapping problem is abstracted as solving a large-scale system of inconsistent linear equations. With the difficulties of large-scale phase unwrapping analyzed, L(0)-norm criterion is found to have potentials in efficient image tiling and splicing. Making use of the clustering characteristic of residue distribution, a tiling strategy is proposed for L(0)-norm criterion. Unfortunately, L(0)-norm is an NP-hard problem, which is very difficult to find an exact solution in a polynomial time. In order to effectively solve this problem, equations corresponding to branch cuts of L(0)-norm in the inconsistent equation system mentioned earlier are considered as outliers, and then an outlier-detection-based phase unwrapping method is proposed. Through this method, a highly accurate approximate solution to this NP-hard problem is achieved. A set of experimental results shows that the proposed approach can avoid the inconsistency between local and global phase unwrapping solutions caused by image tiling.     

地基SAR干涉相位滤波优化方法

地基SAR对边坡进行形变监测过程中,为了获得较高的图像质量和进行相位解缠的需要,往往要对干涉相位进行滤波优化,以提高干涉相位图的信噪比,减少干涉相位图中的残差点,从而有助于更好地进行相位解缠,提高形变监测的精度与可行性。本文针对地基SAR干涉相位图的空变等特性,对地基SAR干涉相位滤波算法进行了研究,着重介绍了四种经典、高效的干涉相位滤波算法,并进行了地基SAR边坡形变监测试验,使用实测干涉数据进行了四种滤波处理,从定量及定性的角度对每种滤波算法进行了比较与评估。最终给出了最优滤波算法,为地基SAR进行干涉相位实时滤波优化及后续数据处理提供了基础。      

A Wide-Band Approach to the Absolute Phase Retrieval in SAR Interferometry

Because of possible multiple solutions allowed, the unwrapping of interferometric fringe patterns in the spatial domain is an ill-posed problem which needs some a priori knowledge of the ground morphology for the solution of ambiguities. This is especially true for interferometric SAR (Synthetic Aperture Radar) data. In this paper we propose a different approach to InSAR processing for retrieving the height of ground points independently from each other, unlike most conventional phase unwrapping procedures, which operate in the spatial domain. The basic idea is to repeat raw data focusing by using range sub-bands centered at different frequencies, in order to find a point history of the interferometric phase variation vs. frequency. We introduce the general framework of the method together with considerations on the theoretical limits of applicability, then we report results of our simulations related to a wide-band SAR system. We show that, under certain conditions, height values can be retrieved over a network of coherent and strong scatterers, even when enclosed into low-coherence areas.     

基于自适应参数的径向基函数相位解缠算法

为了改进基于径向基函数的相位解缠(RBFPU)算法 ,针对不同的缠绕图, 提出了一种自适应参数的RBFPU(ADRBFPU)算法:先对图像进行分块 ,然后按照各块的图像复杂度确定对应的径向基函数的宽度。实验结果表明,在不同噪声水 平下,与经典RBFPU算法及经典的质量图导向(QGPU)法和图割(PUMA)法等相比,本文算法具 有更好的鲁棒性。     

Reduction of the need for phase unwrapping in radar interferometry

Monitoring of a small change by synthetic aperture radar (SAR) has previously been demonstrated for several sites, We derive two methods for detecting small displacements in the general case of differential interferometry: (1) the topographic elimination method and (2) the three-pass method. We explain the reasons which make us favor the former method. Validation and calibration of both methods are described. The topographic elimination method is preferred because of the limited need for phase unwrapping. Although phase unwrapping is usually considered to be a key component of radar interferometry, we show that it can be avoided most of the time by using a rough digital elevation model available throughout the world and a new technique, the integer interferometric combination (IIC). Several examples validating the IIC technique are presented as well as considerations about the probability and cost of having a successful study on a given site, which is not a site of opportunity. We conclude with some examples of topography-free, map-registered interferograms, which were produced automatically from SAR raw data and digital elevation models of various quality using the above methods. This validates these methods from an operational point of view     

干涉SAR最小二乘二维相位展开法的改进

二维相位展开是干涉SAR成像的关键步骤和难点,以SIR－C／X－SAR真实数据得出的相位条纹为对象,用Pritt的最小二乘法做了展开,发现并讲座了最小二乘的平滑作用对展开结果的不良影响,并用一种依据二阶差分的加权对最小二乘法进行改进,更好地实现了相位展开。     

一种InSAR建筑物图像仿真及高程反演方法

城市建筑区域叠掩、阴影严重,图像理解困难且干涉相位变化复杂紊乱,一直是InSAR处理的困难区域。SAR图像仿真能为图像理解和处理方法研究提供数据支撑,然而现有建筑区域SAR图像仿真方法大多无法获得具有相干性的干涉SAR图像对。该文提出了一种面向建筑区域的干涉SAR复图像对仿真方法,能够获得建筑的复数图像对、干涉相位图以及叠掩成分数目等信息,为城区干涉SAR处理及信息提取研究提供仿真数据支撑。同时,基于仿真中对相位变化规律的分析,提出叠掩区相位解缠时的基准确定方法,解决传统解缠方法面临的叠掩区域干涉相位不连续问题,进而反演建筑高程信息。最后,通过建模仿真结果与实际SAR图像和干涉相位的对比,验证了仿真方法的正确性,并对仿真及实际干涉相位进行解缠和高程反演处理,验证了该文高程反演方法的有效性。      

基于最小截面差的相位展开

相位展开 (PhU)问题从理论上讲是一个不适定问题。根据被测物理量的整体连续性 ,提出了一种基于最小截面差的相位展开方法。理论分析和对实验条纹图的处理结果表明 ,该方法特别适合于具有相位间断大于π ,条纹欠采样及随机噪声等条纹图的相位展开。同支切 (Branchcuts)法相比 ,该方法具有算法简单、计算量小且可靠度高的特点 ,具有一定的实用性。     

A sparsity-driven approach for joint SAR imaging and phase error correction

Image formation algorithms in a variety of applications have explicit or implicit dependence on a mathematical model of the observation process. Inaccuracies in the observation model may cause various degradations and artifacts in the reconstructed images. The application of interest in this paper is synthetic aperture radar (SAR) imaging, which particularly suffers from motion-induced model errors. These types of errors result in phase errors in SAR data, which cause defocusing of the reconstructed images. Particularly focusing on imaging of fields that admit a sparse representation, we propose a sparsity-driven method for joint SAR imaging and phase error correction. Phase error correction is performed during the image formation process. The problem is set up as an optimization problem in a nonquadratic regularization-based framework. The method involves an iterative algorithm, where each iteration of which consists of consecutive steps of image formation and model error correction. Experimental results show the effectiveness of the approach for various types of phase errors, as well as the improvements that it provides over existing techniques for model error compensation in SAR.     

一种基于UPF的干涉SAR相位展开方法

提出一种不敏粒子滤波的相位展开方法.该方法是不敏粒子滤波器与路径跟踪策略以及全方位的局部相位梯度估计相结合的结果,不受模型噪声统计特性和线性条件约束,同时完成噪声消除和相位展开;利用不敏卡尔曼滤波器来进行粒子更新,使重要密度函数能够融入最新观测信息和更加符合真实状态的后验概率分布,从而提高了相位展开精度与效率.仿真和实...     

基于二阶差分的加权最小费用流相位展开算法

相位展开是光学干涉相位测量技术中的重要步骤,由于噪声、欠采样等因素的影响,精确的相位展开变得非常困难。将相位的二阶差分和最小费用流算法结合,提出一种以相位的二阶差分作为最小费用流权重的相位展开算法。模拟计算表明,该算法既可有效地避免枝切法由于连接的枝切形成闭合区域导致局部相位不能展开的问题,又可减小最小二乘法近似逼近带来的较大误差,相对于未设置权值的最小费用流算法,提高了其相位展开的精度。对三维形貌测量中的实验数据相位展开结果,证明了该算法的有效性。     

Unwrapping of MR phase images using a Markov random field model

Phase unwrapping is an important problem in many magnetic resonance imaging applications, such as field mapping and flow imaging. The challenge in two-dimensional phase unwrapping lies in distinguishing jumps due to phase wrapping from those due to noise and/or abrupt variations in the actual function. This paper addresses this problem using a Markov random field to model the true phase function, whose parameters are determined by maximizing the a posteriori probability. To reduce the computational complexity of the optimization procedure, an efficient algorithm is also proposed for parameter estimation using a series of dynamic programming connected by the iterated conditional modes. The proposed method has been tested with both simulated and experimental data, yielding better results than some of the state-of-the-art method (e.g., the popular least-squares method) in handling noisy phase images with rapid phase variations.     

Hierarchical network flow phase unwrapping

The well-studied interferometric synthetic aperture radar (InSAR) problem for digital elevation map generation involves the derivation of topography from the radar phase. The topography is a function of the full phase, whereas the measured phase is known modulo 2/spl pi/, necessitating the process of recovering full phase values via phase unwrapping. This mathematical process becomes difficult through the presence of noise and phase discontinuities. This paper is motivated by research which models phase unwrapping as a network-flow minimization problem. A major limitation is that often a substantial computational effort is required to find solutions. Commonly, these phase images are huge (/spl Gt/10 million pixels), and obviously the sheer size of the problem itself makes phase unwrapping challenging. This paper addresses the development of a computationally efficient hierarchical algorithm, based on a "divide-and-conquer" approach. We have shown that the phase-unwrapping problem can first be partitioned into independent phase-unwrapping subproblems, which can further be recombined to produce the unwrapped phase. Interestingly, the recombination step itself can be interpreted as an unwrapping problem, for which a modified network-flow solution applies! In short, this paper develops a parallelization of the network-flow algorithm, allowing images of virtually unlimited size to be unwrapped and leading to dramatic decreases in the algorithm execution time.     

A Bayesian filtering technique for SAR interferometric phase fields

SAR interferograms are affected by a strong noise component which often prevents correct phase unwrapping and always impairs the phase reconstruction accuracy. To obtain satisfactory performance, most filtering techniques exploit prior information by means of ad hoc, empirical strategies. In this paper, we recast phase filtering as a Bayesian estimation problem in which the image prior is modeled as a suitable Markov random field, and the filtered phase field is the configuration with maximum a posteriori probability. Assuming the image to be residue free and generally smooth, a two-component MRF model is adopted, where the first component penalizes residues, while the second one penalizes discontinuities. Constrained aimulated annealing is then used to find the optimal solution. The experimental analysis shows that, by gradually adjusting the MRF parameters, the algorithm filters out most of the high-frequency noise and, in the limit, eliminates all residues, allowing for a trivial phase unwrapping. Given a limited processing time, the algorithm is still able to eliminate most residues, paving the way for the successful use of any subsequent phase unwrapping technique.     

New approaches in interferometric SAR data processing

It is known that interferometric synthetic-aperture radar (SAR) images can be inverted to perform surface elevation mapping. Among the factors critical to the mapping accuracy are registration of the interfering SAR images and phase unwrapping. A registration algorithm is presented that determines the registration parameters through optimization. A figure of merit is proposed that evaluates the registration result during the optimization. The phase unwrapping problem is approached through a new method involving fringe line detection. The algorithms are tested with two SEASAT SAR images of terrain near Yellowstone National Park. These images were collected on SEASAT orbits 1334 and 1420, which were very close together in space, i.e. less than 100 m     

Multifrequency InSAR height reconstruction through maximum likelihood estimation of local planes parameters

A technique that is able to reconstruct highly sloped and discontinuous terrain height profiles, starting from multifrequency wrapped phase acquired by interferometric synthetic aperture radar (SAR) systems, is presented. We propose an innovative unwrapping method, based on a maximum likelihood estimation technique, which uses multifrequency independent phase data, obtained by filtering the interferometric SAR raw data pair through nonoverlapping band-pass filters, and approximating the unknown surface by means of local planes. Since the method does not exploit the phase gradient, it assures the uniqueness of the solution, even in the case of highly sloped or piecewise continuous elevation patterns with strong discontinuities.