Compressed sensing for digital holographic microscopy

Marcio M. Marim, Michael Atlan, Elsa D. Angelini, J.-C. Olivo-Marin
2010 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
This paper describes an original microscopy imaging framework successfully employing Compressed Sensing for digital holography. Our approach combines a sparsity minimization algorithm to reconstruct the image and digital holography to perform quadratureresolved random measurements of an optical field in a diffraction plane. Compressed Sensing is a recent theory establishing that near-exact recovery of an unknown sparse signal is possible from a small number of non-structured measurements. We
more » ... onstrate with practical experiments on holographic microscopy images of cerebral blood flow that our CS approach enables optimal reconstruction from a very limited number of measurements while being robust to high noise levels.
doi:10.1109/isbi.2010.5490084 dblp:conf/isbi/MarimAAO10 fatcat:dtzo6zgc5jhjnmcbvrxbxyphta