An adaptive distance-based edge preserving interpolation algorithm for natural images
In this paper, we propose a new image interpolation method using adaptive weights based on inverse gradients and distances from the pixels used in prediction. Since the weights are based on different spatial locations of the pixels, this allows preservation of important edge information and hence to prevent extensive blurring across edges in the upsampling process. Experimental results on a large test image set show that the proposed algorithm gives better performance compared to conventional algorithms.