Friday, May 10, 2019

Compressive optical interferometry

** Nuit Blanche is now on Twitter: @NuitBlog **

When interferometry is done with radiowaves, then compressive sensing reconstruction makes immediately sense as we get phase measurements. In the case of light, phase retrieval is required or something has to be done at the hardware level.  Something along the lines of some of throughts put in this entry on These Technologies Do Not Exist.



Compressive sensing (CS) combines data acquisition with compression coding to reduce the number of measurements required to reconstruct a sparse signal. In optics, this usually takes the form of projecting the field onto sequences of random spatial patterns that are selected from an appropriate random ensemble. We show here that CS can be exploited in `native' optics hardware without introducing added components. Specifically, we show that random sub-Nyquist sampling of an interferogram helps reconstruct the field modal structure. The distribution of reduced sensing matrices corresponding to random measurements is provably incoherent and isotropic, which helps us carry out CS successfully.

Follow @NuitBlog or join the CompressiveSensing Reddit, the Facebook page, the Compressive Sensing group on LinkedIn  or the Advanced Matrix Factorization group on LinkedIn


Other links:
Paris Machine LearningMeetup.com||@Archives||LinkedIn||Facebook|| @ParisMLGroup About LightOnNewsletter ||@LightOnIO|| on LinkedIn || on CrunchBase || our Blog

No comments:

Printfriendly