基于间断自适应MRF的相位解缠算法

合成孔径干涉雷达（InSAR）技术已被广泛应用于地面高程信息的获取。相位解缠作为其关键步骤直接关系到地表高程的提取精度。然而，相位解缠受相位连续性假设的限制无法识别间断相位，影响在陡峭地形区域的高程反演精度。针对上述问题，本文提出了一种基于间断自适应马尔可夫随机场模型（DA-MRF）的相位解缠算法处理间断相位。首先构建DA-MRF模型的能量函数能够自适应地在连续相位处保持像素连接，同时在间断相位处阻断像素连接；然后再利用图割算法优化能量函数，完成相位解缠。仿真和实测数据试验证明，本文方法与常用的相位解缠算法相比，具有更强的间断相位保持能力，更适用于地形变化剧烈场景中的地形重建。

Phase unwrapping method based on discontinuity adaptive markov random fields

Interferometric synthetic aperture radar (InSAR) technology has been widely applied to digital elevation model (DEM) generation. Phase unwrapping, as one of key procedures in InSAR technique is related directly to the accuracy of DEM reconstruction. However, phase unwrapping method can not estimate the discontinuous phase due to the limitation of the phase continuity assumption, which reduces the accuracy of DEM generation in the mountainous area. To solve this problem, a phase unwrapping method based on discontinuity adaptive MRF (DA-MRF) is proposed in this paper, which can deal with discontinuous phase. Firstly, the energy function of DA-MRF is established which can keep the pixel pairs connected for the continuous phase while make the pixel pairs disconnected for the discontinuous phase adaptively. Then, the graph cuts method is used to optimize the energy function of DA-MRF to obtain the final result. The simulated and real data experiments both demonstrate that the proposed method has more powerful discontinuity persevering ability and is more applicable in DEM generation in the mountainous area, compared with other phase unwrapping methods.