MATLAB implementation of compressive sensing example as described in R. Baraniuk, Compressive Sensing, IEEE Signal Processing Magazine, [118], July 2007. The code acquires 250 averaged random measurements of a 2500 pixel image. We assume that the image has a sparse representation in the DCT domain (not very sparse in practice). Hence the image can be recovered from its compressed form using basis pursuit.

Filename	Size	Update
Compressive_Sensing.m	920	2011-11-18
license.txt	1314	2014-02-12

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