Single image super-resolution using combined total variation regularization by split Bregman Iteration

Lin Li, Yuan Xie, Wenrui Hu, Wensheng Zhang

Abstract: Highlights•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.