Picture Quality Prediction in Image Processing
Résumé
Interpolations are among the most important tools for image processing. However, whether they are used for image compression and reconstruction purposes or for the increase of the image resolution along vertical, horizontal or both dimensions, the induced interpolation errors are often only qualitatively and a posteriori described. In this paper, we propose to extend a method used in an OFDM context to achieve a quantitative a priori estimation of interpolation errors. As shown by simulations, this estimation proves to be consistent with a posteriori error and quality measurements, such as mean square error (MSE) and peak signal-to-noise ratio (PSNR).