Progressive compressive imaging from Radon projections

Sergei Evladov, Ofer Levi, Adrian Stern

Research output: Contribution to journalArticlepeer-review


In this work we propose a unique sampling scheme of Radon Projections and a non-linear reconstruction algorithm based on compressive sensing (CS) theory to implement a progressive compressive sampling imaging system. The progressive sampling scheme offers online control of the tradeoff between the compression and the quality of reconstruction. It avoids the need of a priori knowledge of the object sparsity that is usually required for CS design. In addition, the progressive data acquisition enables straightforward application of ordered-subsets algorithms which overcome computational constraints associated with the reconstruction of very large images. We present, to the best of our knowledge for the first time, a compressive imaging implementation of megapixel size images with a compression ratio of 20:1.

Original languageEnglish
Pages (from-to)4260-4271
Number of pages12
JournalOptics Express
Issue number4
StatePublished - 13 Feb 2012
Externally publishedYes


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