Single image super-resolution using combined total variation regularization by split Bregman Iteration
We propose a new regularization item called steering kernel regression total variation (SKRTV). A MAP super-resolution framework is presented to assemble the global reconstruction constraint, SKRTV and NLTV terms. We solve our model using split Bregman iterations.
super-resolution total variation split bregman iteration steering kernel regression local structural regularity non-local self-similarity