A Weighted and Combined Super Resolution Reconstruction Algorithm

Abstract

The weaknesses between L 1 norm minimization estimator and L 2 norm minimization estimator in the traditional super resolution reconstruction problem are analyzed. In this paper, L 1 norm and L 2 norm are weighted and combined to measure the data fidelity term, and based on an approximate total variation regularization method [1][2], a robust weighted and combined super resolution reconstruction algorithm is proposed. Simulation experiments show that this method not only enhances the quality of the restoration images and has better edge-preserving capability, but also efficiently removes the visual artifacts and is robust to noise.