Compressing sensing techniques for holography: Theory and examples Conference Paper uri icon


  • 1. Introduction Compressive sensing (CS) is a new signal acquisition paradigm which has already created a large impact in many research fields [1]. 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 [2]. Therefore, it is not surprising that CS found its application in the field of digital holography (DH) [3-13]. Here we present a brief overview of CS …

publication date

  • April 28, 2012