 "Compressive Sensing and the Visual System" 
Joelle Barral
Final Project - PSY 221 
Stanford University
Winter 2008
Comments welcome: jbarral@stanford.edu

** The project was meant to be a literature project. The simulation part of
it was therefore minimal. I implemented what I needed to better understand the
concepts, but none of the simulations have been optimized. Some mfiles are very simple, they
provide a pictorial support for an explanation that can be found on the webpages. **

Libraries needed: 
* ISET http://www.imageval.com
* l1magic www.l1-magic.org

Files:

----- For pictorial support -----

alphabet.m :	    cf. On the necessity of a sparse code. 
counterexample.m    cf. Counterexample

----- Simulations -----

random_b.m	     Generates a*b independent draws of a Bernoulli random variable with probability of success p.
random_g.m	     Generates an a*b matrix of gaussian values with mean mu and standard deviation sigma
random_sp.m          Generates an a*b matrix where each column has sparsity d
random_w.m	     Generates an a*b Walsh matrix as used for the single-pixel camera

SimuNoOptics.m       Simulates a Compressive Sensing Measurement and Reconstruction
SimuWithOptics.m     Same with the single-pixel camera optics. 
sensorComputeImage.m Replaces the original ISET function.

NB: we also commented out all the wait bars in ISET since they are time consuming when K measurements are performed.



