Bi-Lipschitz Mapping on a Space of Orbits
Kathleen Fleming and Sankalp Yadav
Department of Arts and Sciences, University of North Carolina at Wilmington
Introduction
Phase retrieval is the idea of understanding the nature of an input based on the properties of the output. So, for instance, when we think of x-ray imaging or astronomical photo rendering, we observe two dimensional projections of three-dimensional entities.
Therefore, we must first produce results for a base case and then expand it into a general form to observe ubiquitously true results. In order to accomplish this task of retrieval, we start off by using the idea of bi-Lipschitz bounds.
A bi-Lipschitz bound bounds a functions’ outputs, or intensity measurements, by the distance between the original inputs scaled by a constant lower and upper bound.
With this knowledge, we can now list some objectives to explore within the mapping:
Results
Conclusions
Future Work
Abstract
Acknowledgements
MAT 495 Seminar in Mathematics, Dr. Jameson Cahill, Dr. Daniel Guo
Steps
References Cited
Radu Balan, Pete Casazza, and Dan Edidin. “On signal reconstruction without phase”. In: Applied and Computational Harmonic Analysis 20.3 (2006), pp. 345–356.
Afonso S. Bandeira et al. “Saving phase: Injectivity and stability for phase retrieval”. In: Applied and Computational Harmonic Analysis 37.1 (2014), pp. 106-125
Simon Maretzke and Thorsten Hohage. “Stability Estimates for Linearized Near-Field Phase Retrieval in X-ray Phase Contrast Imaging”. In: SIAM Journal on Applied Mathematics 77.2 (2017), pp. 384–408
Figure 3. Simplistic example of a case of image-based phase retrieval for two inputs plotted onto the same dimensional output