Phase Retrieval from Sparse Data

Phase retrieval from sparse data involves reconstructing an unknown signal or image using limited measurements, where some information (the phase) is missing. When data is sparse, it contains mostly zeros or is highly concentrated in certain areas, making the problem challenging. Techniques leverage the sparsity to efficiently recover the original signal by solving mathematical optimization problems, even with incomplete data. This approach is useful in fields like imaging and optics, allowing accurate reconstruction without requiring extensive measurements, saving time and resources while maintaining high-quality results.