Adaptive noise reduction of InSAR images based on a complex-valuedMRF model and its application t o phase unwrapping problem

We propose a new adaptive noise reduction method for interferometric synthetic aperture radar (InSAR) complex-amplitude images. In the proposed method, we detect residues (singular points) in the phase image as well as their neighbors at first. Normal areas that contain no residue are used for the estimation of correct pixel values at the marked residues according to 5th order non-causal complex-valued Markov random field (CMRF) model. The process is performed block-wise with the assumption of a locally stationary condition of statistics. Using a CMRF lattice complex-valued neural-network, the error energy defined as the squared norm of distance between signal and estimated values is minimized by LMS steepest descent algorithm. Eventually, the number of residues is decreased. An application is also presented. An InSAR image around Mt. Fuji is processed by the proposed technique and then phase-unwrapped by the branch-cut method. It is found that after the application of the proposed method, a better phase unwrapped image can be obtained successfully     

基于DEM辅助后向投影模型的InSAR高程反演方法

利用干涉合成孔径雷达(InSAR)技术获取数字高程模型(DEM)时,在地形起伏剧烈区域,干涉条纹十分密集,增加了相位解缠的难度,影响相位展开和高程反演的精度.为了解决该问题,该文提出了一种基于DEM辅助后向投影模型的InSAR高程反演方法.该方法可以在统一的后向投影成像空间中实现成像和InSAR高程反演,并且引入外源D...     

A Joint Image Coregistration, Phase Noise Suppression, and Phase Unwrapping Method Based on Subspace Projection for Multibaseline InSAR Systems

As is well known, image coregistration, interferometric phase noise suppression, and phase unwrapping are three key processing procedures of synthetic aperture radar interferometry (InSAR). The three procedures are cascaded in the conventional processing flow of InSAR. Unlike the conventional processing flow, in this paper we propose a joint processing idea to carry out image coregistration, interferometric phase noise filtering, and phase unwrapping simultaneously based on subspace projection for multibaseline InSAR systems. The joint processing method can perform the fine coregistration of all SAR images implicitly by extracting the correlation information in the neighboring pixel sets, suppress the phase noise by utilizing the orthogonality of the signal subspace and the corresponding noise subspace, and optimally estimate the unwrapped interferometric phases (or the terrain heights) by combining the pixel coherence and the baseline diversity of a multibaseline InSAR system. Simulated results are presented to verify the effectiveness of the joint processing method     

利用多基线数据融合提高分布式卫星InSAR系统的干涉相位精度

分布式卫星干涉合成孔径雷达(InSAR)系统可以通过提供长基线来提高测高灵敏度,但长基线会给干涉相位展开带来困难。结合分布式卫星InSAR系统可以同时提供多个稳定基线的特点,该文提出利用多基线数据融合的方法来解决长基线给干涉相位展开带来的困难。文中采用了有效的数据融合方法最大似然估计(ML)法,对多基线分布式卫星InSAR系统的干涉相位进行了估计。模拟结果表明,经过多基线数据融合的干涉相位展开精度要远远大于长基线干涉相位的直接展开精度。     

Phase Unwrapping for SAR Interferometry—A Data Fusion Approach by Kalman Filtering

This paper considers the problem of unwrapping the phase image obtained from a noisy interferometric synthetic aperture radar (InSAR) image. The implicit nonlinearity of the problem is reflected, as well as the drawbacks of this nonlinearity on the performance of phase unwrapping approaches. Some general concepts concerning basic estimation techniques are shortly reviewed. On this background, a Kalman filter-based data fusion approach to unwrap and simultaneously filter the phases of InSAR images is developed. The data fusion concept exploits phase information extracted from the complex interferogram rather than from the phase image and fuses that information with phase slope information extracted from the power spectral density of the interferogram.     

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。      

对配准误差稳健的多基线相位展开方法

提出了一种对配准误差稳健的多基线相位展开方法.该方法首先根据配准误差的方向来确定最优联合观测矢量,进而确定存在配准误差时的真实导向矢量,并且用此导向矢量进行波束形成来进行相位展开,能够同时完成图像配准、干涉相位噪声滤波和相位展开,因此可以在SAR图像配准精度很差(可以允许达到一个分辨单元)的条件下得到稳健的相位展开性能,仿真结果证明了此方法的有效性.     

基于旋滤波的InSAR干涉条纹图滤波方法

InSAR干涉条纹图处理中，对噪声进行滤波是非常关键的一步。该文在分析现有滤波算法的基础上，考虑了干涉条纹图方向性特点，提出了基于旋滤波的InSAR干涉条纹图滤波方法。可以有效地去除残点对相位解缠的影响，同时保持相位信息不受损害。对仿真数据及真实InSAR数据的处理结果证明了该方法的有效性。     

基于StereoSAR辅助的InSAR DEM重建方法研究

StereoSAR与InSAR是两种利用合成孔径雷达图像重建DEM的关键技术。InSAR利用SAR干涉像对的相位信息重建高程,具有DEM重建精度高的特点,但DEM重建精度受环境、时间等失相干因素影响较大;StereoSAR是利用SAR立体像对的幅度信息重建高程,尽管DEM重建理论精度比InSAR差,但受失相干因素影响小,并且可以在缺乏外部辅助高程信息时获取绝对DEM。在传统的InSAR处理中,干涉条纹密集区域相位解缠难度较大,存在相位解缠错误和错误传播现象,且在没有地面控制点或外部DEM的时难以获得绝对DEM。文中提出了一种迭代式的基于StereoSAR辅助的InSAR高精度DEM重建方法,该方法可以在缺乏外部高程信息时获得绝对DEM,降低干涉条纹密集区域相位解缠的难度,提高DEM重建精度。采用文中所提方法、传统InSAR方法及公开DEM辅助InSAR DEM重建方法,分别在地形复杂与平坦区域进行DEM重建,并用ICESat/GLAS及TanDEM-X DEM进行精度评估。DEM重建结果验证了文中所提方法的有效性,所提方法的DEM重建精度优于传统InSAR方法且与公开DEM辅助InSAR DEM重建方法精度相当。     

一种多基线相位解缠频域快速算法

一切将相位由主值或相位差值恢复为真实值的过程统称为相位解缠,除了雷达干涉应用外,相位解缠在合成孔径声纳、自适应光学、核磁共振、地震处理等方面都有重要应用,多基线可提高相位解缠的性能。以多基线干涉合成孔径雷达(InSAR)系统为应用背景,提出一种多基线InSAR干涉相位解缠频域快速算法。该算法的基本思想是使相位梯度估计值的频域函数与各基线相位梯度频域函数加权和之差的平方和最小。仿真及实测数据处理结果表明:频域算法效果与时域算法类似,由于避免了镜像操作,其效率大大提高。     

噪声消除算法在干涉SAR相位解缠中的应用研究

本文把噪声消除算法应用在干涉SAR相位解缠中,分析了该算法的特点.为了更好地解缠干涉SAR数据,提出了一种改进的方法.在原有两点规则的基础上,提出了三点规则,并提出把两点规则和三点规则结合使用来提高相位解缠稳健性的混合算法.该方法有效地解决了噪声消除算法在解缠质量差干涉相位图时不收敛的问题,在保持了算法的计算精度的同时提高了算法的稳健性.对仿真和真实干涉SAR数据的实验结果验证了本文方法的有效性.     

InSAR加权迭代贪婪算法相位解缠及性能分析

针对干涉SAR二维相位解缠问题,提出了一种利用加权迭代贪婪算法提高解缠精度的新方法.首先推导了加权迭代贪婪算法相位解缠的基本原理,然后给出了算法的实现过程,最后进行了仿真分析.在分析比较了W=2和W=3加权迭代贪婪算法性能的基础上,将W=3加权迭代贪婪算法与经典的解缠算法在解缠精度和解缠时间上进行了比较.仿真和实际数据解缠证明,该算法实时、高效、准确.     

由新质量图引导的InSAR快速解缠方法

相位解缠是SAR干涉测量数据处理中的一个关键步骤之一,解缠结果的好坏直接影响最终数字高程模型的精度。该文介绍了一种新的质量图求取方法。该方法考虑到条纹宽度对传统的灰度方差质量图的影响,提出利用平面拟合来消除坡度效应后再求取灰度方差作为质量,取得良好的效果。该文还对质量图的解缠算法进行了改进,利用查找表来降低路径搜索的计算量,大大减少了解缠所需要的时间。由于InSAR图像的数据量往往很大,解缠时间的大大缩短对于这样大量数据的处理是非常有利的。对真实InSAR干涉纹图的处理结果表明,该解缠方法高效而实用。     

合成孔径雷达干涉测量中的相位展开

合成孔径雷达干涉测量技术 (InSAR)是以合成孔径雷达复数据提取的相位信息作为信息源来获取地表的三维信息和变化信息的一项技术。相位展开是InSAR数据处理中的关键步骤之一。本文介绍了合成孔径雷达干涉测量的原理 ,重点讨论了InSAR中的相位展开算法 ,特别对与路径有关的算法和与路径无关的算法进行了分析 ,比较了各类方法的优缺点。指出一些在结构照明型计量中有效的相位展开算法也可以用于合成孔径雷达干涉测量之中的相位展开     

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.     

正交长基线毫米波InISAR运动目标三维成像

提出了一种基于差频测角定位、等效去平地相位和模糊数估计相结合的相位解缠方法.根据波束指向信息在差频下干涉测角,对目标进行粗定位;然后借鉴干涉合成孔径雷达(InSAR)中的去平地相位技术,实现等效去平地相位,缓解相位解缠压力;最后对模糊数进行统计估计,完成相位解缠.实际数据处理结果表明,该方法不仅解决了目标尺寸较大引起的相对相位缠绕问题,而且可以获得目标的绝对相位,实现了对运动目标的三维定位与三维成像.     

旋滤波降噪在干涉SAR相位解缠中的应用研究

干涉相位图的降噪滤波，是干涉合成孔径雷达成像中必须的步骤之一。文中根据干涉条纹在切线方向变化最小的特点，利用沿切线方向的曲线窗口对干涉相位图进行旋滤波降噪，并通过对比不同的滤波结果及相应相位解缠结果，证明了旋滤波在保持条纹结构信息，消除噪声和提高相位解缠精度应用中的可行性和有效性。     

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.     

基于改进粒子群算法的二维相位解缠方法

相位解缠是干涉合成孔径雷达(InSAR)干涉数据处理的关键步骤之一,枝切法作为一种经典的相位解缠算法在相位解缠过程中,建立的枝切线长度越短相位的解缠效果越好,枝切线该如何建立至关重要。在旅行商问题(TSP)理论求解最短路径的思想下,一种利用粒子群优化算法建立最短枝切线的方法被提出,该方法在基本粒子群优化算法中引入变异算子对粒子群算法容易陷入局部收敛的缺陷进行了改进。相对于Goldstein枝切法而言,该方法能够更有效的缩短枝切线的长度,避免解缠过程中\     

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.