On the tomographic reconstruction resolution from compressive holography Conference Paper uri icon


  • Compressive sensing (CS) [1,2] has made a large impact in various research fields during the recent years. Compressive sensing theory provides an alternative to conventional signal sampling paradigm, according to which a relatively large amount of information is acquired and then most of it is discarded during the digital post processing stage. Instead, CS attempts to take the smallest number of measurements, while still guaranteeing exact signal reconstruction. Compressive sensing theory relies on the assumption that the signal we wish to acquire can be represented sparsely in some domain. Since natural images and scenes tend to have extremely sparse representations, 2D and 3D imaging are among the most beneficiary fields from the introduction of CS, specifically one of the fields that was greatly benefited from CS is digital holography (DH) [3]. In previous works, we have dealt with the reconstruction and performance …

publication date

  • January 1, 2013