Integrated Denoising and Unwrapping of InSAR Phase Based on Markov Random Fields
Integrated Denoising and Unwrapping of InSAR Phase Based on Markov Random Fields
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DOI：
10.1109/tgrs.2013.2268969
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发表时间：
2013-07
影响因子：
8.2
通讯作者：
Runpu Chen;Weidong Yu;Robert Wang;Gang Liu;Yunfeng Shao
中科院分区：
文献类型：
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作者：
Runpu Chen;Weidong Yu;Robert Wang;Gang Liu;Yunfeng Shao
在传统的干涉合成孔径雷达（SAR）技术处理流程中，相位的处理是通过两个分离的、连续的步骤进行的，相位去噪和相位解缠。也就是说，首先，生成没有噪声的包裹相位，然后，重构没有2π模糊度的真实相位（在这里和本文的其余部分中，真实相位是指没有噪声的信息引起的展开相位）。这种分离的步骤将不可避免地带来额外的估计误差，因为每个步骤都有必要的近似和假设，而这些近似和假设并不总是成立的。相反，在本文中，我们把相位去噪和解缠作为一个单一的问题，从观察到的真实相位恢复。在此基础上，提出了一种基于马尔可夫随机场（MRF）的相位去噪与去包裹算法。考虑到干涉相位的先验知识，MRF被用来模拟包括真实相位和它们的观测值的随机变量集合中的元素之间的关系。模型建立后，根据MRF结构的局部独立性，定义了MRF的能量函数，并将其最小化，得到了真实相位的估计。最后，通过仿真和真实相位数据进行实验，并与几种常用的去包裹方法进行比较，验证了该算法的有效性。
In the traditional processing flow of interferometric synthetic aperture radar (SAR) technique, the processing of phase is conducted via two separated and successive steps, i.e., phase denoising and phase unwrapping. That is to say, first, wrapped phases without noise are generated, and then, the true phases without 2π-ambiguities are reconstructed (here and in the rest of this paper, true phase refers to the information-induced unwrapped phase without noise). Such separated steps will inevitably bring in extra estimation error because each step has necessary approximations and presumptions which do not always hold. On the contrary, in this paper, we treat phase denoising and unwrapping as a single problem of true phase recovery from observed ones. Following this methodology, an integrated phase denoising and unwrapping algorithm based upon Markov random fields (MRFs) is proposed. Taking a priori knowledge of interferometric phases into account, MRF is used to model the relationship between the elements in the random variable set including both true phases and their observations. After the model is built up, the energy function of this MRF is defined according to the local-independence property inferred from the MRF structure and then minimized to obtain the estimate of the true phase value. In the end of this paper, experiments on simulated and true phase data are conducted, and the comparison with several commonly used unwrapping methods is proposed to verify the efficiency of the proposed MRF algorithm.