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Investigation on the influence of the gradient guided regularization to the SRR performance in terms of PSNR and SSIM. The results show that our SRR approach performed the best with the regularization weight parameter λ ranging from 0.05 to 0.3. The results also suggest that the regularization considerably improved the SRR performance on the simulation data set by referring to the results at λ = 0 (in the case of no regularization).
