MATLAB implementation of compressive sensing example as described in R.Baraniuk, Compressive Sensing, IEEE Signal Processing Magazine, , 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.
Stuart Gibson (2022). simple compressed sensing example (https://www.mathworks.com/matlabcentral/fileexchange/41792-simple-compressed-sensing-example), MATLAB Central File Exchange. Retrieved .
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