【摘要】 相位解缠作为InSAR技术中至关重要的一环，直接决定着InSAR地表形变监测与地形高程测量的准确性.受复杂噪声的影响，低相干性区域的相位解缠面临严峻挑战，时常会形成解缠误差并传播到周边区域，造成区域解缠失败.针对这一问题，本文提出了一种通过视觉特征增设虚拟残点的相位解缠方法.首先，该方法将计算机视觉领域中的轮廓特征引入到InSAR相位解缠过程中，自适应地确定虚拟残点的增设位置；其次，增设虚拟残点，平衡低相干性区域中的孤立残点，从而抑制低相干性区域中解缠误差的形成与传播，提高整体区域的相位解缠准确性.本文采用模拟数据与真实数据验证了该方法的有效性，并开展了相关分析讨论.研究结果表明，本文方法相较于经典最小费用流方法，相位标准偏差(PSD)降低了33.00%，实现了更高精度的相位保真，提高了后续地形测量与形变监测的准确性与可信度.更多还原

【Abstract】 Phase unwrapping, as a crucial step in InSAR(Interferometric Synthetic Aperture Radar) technology,directly influences the accuracy of InSAR surface deformation monitoring and topographic elevation measurement. However, phase unwrapping in low-coherence regions remains challenging due to complex noise,often resulting in unwrapping errors which propagate to surrounding areas, leading to the failure of regional unwrapping. To address this, we proposed a phase unwrapping method which incorporates virtual residues through visual features. Firstly, this method introduced contour features from computer vision into the InSAR phase unwrapping process to adaptively determine the placement of virtual residues. Then, virtual residues were added, balancing isolated residues in low-coherence areas, thereby suppressing the formation and propagation of unwrapping errors, and improving the overall accuracy of phase unwrapping. The effectiveness of the proposed method is validated using both simulated and real datasets, followed by relevant analysis and discussion. The results demonstrate that the proposed method achieved a 33.00% reduction in Phase Standard Deviation(PSD)compared to the classical minimum cost flow method, enabling higher phase fidelity along with improved the accuracy and reliability of subsequent topographic mapping and deformation monitoring.更多还原