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Compressed sensing for digital holographic microscopy
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
doi:10.1109/isbi.2010.5490084
dblp:conf/isbi/MarimAAO10
fatcat:dtzo6zgc5jhjnmcbvrxbxyphta