Application of Compressive Sensing to Digital Holography
Abstract
Compressive sensing has been used in many imaging domains to facilitate high quality reconstruction from under-sampled data. This work presents a new reconstruction algorithm for use with under-sampled digital holography measurements and yields reconstruction quality far superior to conventional backpropagation methods. The report describes the new dictionary prior and its use in an iterative soft thresholding algorithm and presents systematic studies of performance versus various physical variables such as exposure time, degree of under-sampling, and object sparsity.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 2015
- Accession Number
- ADA616059
Entities
People
- Mark Neifeld
Organizations
- University of Arizona