This is incredible, though I'm a little confused as to why the psi matrix is IDCT and not something of a Fourier flavor...
IDK seems kinda weird, there's a lot of handwavey stuff that I don't fully understand.
And I'm also wondering what the significance of the frequency domain is--can you generalize compressed sensing with other transforms as well?
One way to think of it is your transforming to some other basis. You could do something similar with any vector base change where you go from a dense representation to a sparse one. Think of things like an eigen decomposition where most of the eigenvalues are small or zero and can be ignored
Or does it have to be sparse? I thought it just has to have a low L1 norm