Saliency-directed image interpolation using particle swarm optimization

In this study, a saliency-directed image interpolation approach using visual attention model and particle swarm optimization (PSO) is proposed. First, a block-based saliency map of an image to be interpolated is generated by the proposed visual attention model in an effective manner. Then, based on the block-based saliency map, bilinear interpolation and PSO interpolation are employed for the pixels in non-saliency blocks and saliency blocks, respectively, to obtain the final interpolation results. Various interpolation filtering mask weights are determined by off-line PSO, which are applicable for horizontal, vertical, and diagonal image interpolation types of saliency pixels in saliency blocks with arbitrary magnification factors (MFs). Based on the experimental results obtained in this study, the interpolation results of the proposed approach are better than those of four comparison methods.