A Conservative Sharpening Filter for Interpolated Images
Leonardo Ramos Emmendörfer · 2020
Interpolation methods are computationally efficient and rather effective for magnification from low-resolution images in order to generate higher resolution images. However, blur and other undesirable visual artifacts are often produced during the process. This work evaluates a sharpening filter that enhances the quality of interpolated images by preserving information from the original low-resolution images. The novel filter was shown to achieve statistically significant increments in both the PSNR and SSIM of magnified RGB images using two image sets from the literature.