The ZπM algorithm:: A method for interferometric image reconstruction in SAR/SAS
The ZπM algorithm:: A method for interferometric image reconstruction in SAR/SAS
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DOI：
10.1109/tip.2002.999675
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发表时间：
2002-04-01
影响因子：
10.6
通讯作者：
Leitao, JMN
中科院分区：
文献类型：
--
作者：
Dias, JMB;Leitao, JMN
本文提出了一种有效的算法，用于从干涉孔径雷达和声纳（干涉合成孔径雷达/InSAS）的不完全、噪声和模2 π观测值中估计绝对相位（而不是简单的模2 π）。所采用的框架也是其他应用，如光学干涉测量，磁共振成像和衍射断层扫描的代表。采用贝叶斯观点，观测密度为2 pi周期，考虑了干涉对去相关和系统噪声，绝对相位的先验概率由复合高斯-马尔可夫随机场（CGMRF）建模，该随机场适用于分段光滑的绝对相位图像。我们提出了一个迭代方案的最大后验概率（MAP）绝对相位估计的计算。每次迭代包含一个离散优化步骤（Z-步骤），通过网络编程技术和迭代条件模式（ICM）步骤（π-步骤）实现。因此，该算法被称为ZpiM，其中字母M代表最大化。本文的一个重要贡献是同时实现相位展开（2 pi倍数的推断）和平滑（观测的去噪）。与在展开之前对数据进行低通滤波的方法相比，这显著提高了绝对相位估计的精度。一组实验结果，比较所提出的算法与其他方法，说明了我们的方法的有效性。
This paper presents an effective algorithm for absolute phase (not simply modulo-2pi) estimation from incomplete, noisy and modulo-2pi observations in interferometric aperture radar and sonar (InSAR/InSAS). The adopted framework is also representative of other applications such as optical interferometry, magnetic resonance imaging and diffraction tomography. The Bayesian viewpoint is adopted; the observation density is 2pi-periodic and accounts for the interferometric pair decorrelation and system noise; the a priori probability of the absolute phase is modeled by a compound Gauss-Markov random field (CGMRF) tailored to piecewise smooth absolute phase images. We propose an iterative scheme for the computation of the maximum a posteriori probability (MAP) absolute phase estimate. Each iteration embodies a discrete optimization step (Z-step), implemented by network programming techniques and an iterative conditional modes (ICM) step (pi-step). Accordingly, the algorithm is termed ZpiM, where the letter M stands for maximization. An important contribution of the paper is the simultaneous implementation of phase unwrapping (inference of the 2pi-multiples) and smoothing (denoising of the observations). This improves considerably the accuracy of the absolute phase estimates compared to methods in which the data is low-pass filtered prior to unwrapping. A set of experimental results, comparing the proposed algorithm with alternative methods, illustrates the effectiveness of our approach.