论文标题
使用双重图像先验的实际阶段检索
Practical Phase Retrieval Using Double Deep Image Priors
论文作者
论文摘要
相位检索（PR）涉及从复杂幅度中恢复复杂阶段的问题。我们确定PR问题中难度级别与对称性的数量和多样性之间的联系。我们专注于最困难的远场PR（FFPR），并使用双重图像先验提出了一种新颖的方法。在现实的评估中，我们的方法优于大幅度的所有竞争方法。作为一种单稳定方法，我们的方法不需要培训数据和最少的超参数调整，因此具有良好的实用性。
Phase retrieval (PR) concerns the recovery of complex phases from complex magnitudes. We identify the connection between the difficulty level and the number and variety of symmetries in PR problems. We focus on the most difficult far-field PR (FFPR), and propose a novel method using double deep image priors. In realistic evaluation, our method outperforms all competing methods by large margins. As a single-instance method, our method requires no training data and minimal hyperparameter tuning, and hence enjoys good practicality.
