Compressive fresnel holography for object reconstruction through an occluding plane Conference Paper uri icon


  • Compressive sensing is a relatively new framework which allows the reconstruction of a signal from a relatively small number of measurements. This notion relies on the fact that the underlying signal can be sparsely represented and that the measurements are a projection of the signal to some space, which should hold low coherence with the signal's sparsifying operator. The original CS works have shown that when using Fourier or random Gaussian sensing operator, one needs only KlogN measurements, where K is the number of nonzero elements in the signal represented when applying the signal's sparsifying operator and N is the total number of object pixels … Recently, several works have applied the Fresnel based wave propagation as a sensing operator. The Fresnel transform of an object is often captured by means of holography. Under this framework, 3D objects were inferred from their 2D hologram, and 2D and 3D objects …

publication date

  • January 1, 2012