Image Interpolation Based on Weighted and Blended Rational Function

Conventional linear interpolation methods produce interpolated images with blurred edges, while edge directed interpolation methods make enlarged images with good quality edges but with details distortion for some cases. An adaptive rational-based algorithm for the interpolation of digital images with arbitrary scaling factors is proposed. In order to remove artifacts, we construct a new interpolation model with weight and blend, which are used for preserving the clear edge and detail. The proposed model is blended by basic rational interpolation model and three rotated rational models. The weight coefficients are determined by the edge information from different scale based on point sampling. Experimental results show that the proposed method produces images with high objective quality assessment value and good visual quality.