Color image super-resolution based on Wiener filters

This work presents a study on color-image super-resolution algorithms based on adaptive Wiener filtering, which have low computational complexity in comparison to other image resolution enhancement methods. First, the monochrome super-resolution using Wiener filtering is applied to Wavelet Transform coefficients to mitigate the effects of random noise in the low resolution images. Then, the standard and Wavelet-domain super-resolution algorithms using Wiener filtering are applied to color channels to perform the color images super-resolution. A chrominance compression method is proposed to reduce the number of operations required for estimating the high resolution image.