Umar Asghar

You are already at the latest version Traditional Deep Learning (DL) models for single-image super-resolution (SISR) employ upsampling techniques such as interpolation, transpose convolution, or pixel-shuffle operations. These upsampling techniques are not explicitly aware of the frequency domain structure, leading to a loss of finer details. As a result, edges and structural high-information details are often not preserved.