This class contains everything needed for the deconvolution
i)the real (unblurred) signal (if known, otherwise only the length is needed)
ii)the real psf that blurs the signal
iii)the parameters (\lambda_f, \lambda_h and the norms to be used to regularize)
iv)the estimation of the real signal f_hat
v)the estimation of the real psf h_hat
This class also provides a cost function to be minimized to deconvolve the signal
and a cost function for the psf.
This class contains everything needed for the deconvolution
i)the real (unblurred) signal (if known, otherwise only the length is needed)
ii)the real psf that blurs the signal
iii)the parameters (\lambda_f, \lambda_h and the norms to be used to regularize)
iv)the estimation of the real signal f_hat
v)the estimation of the real psf h_hat
This class also provides a cost function to be minimized to deconvolve the signal
and a costfunction for the psf.
Compute TV semi-norm (total variation norm of this signal
the TV norm is defines as the integral over the derivative of the signal
in case of a discrete signal like this, the integral becomes a sum and the
derivative is approximated by a forward difference of order 1.