A fast algorithm for image analogy using particle swarm optimization

This work employs particle swarm optimization (PSO) based texture synthesis approaches, it differs from the pixel-based texture synthesis method, in this way, and the synthesis speed is increased. We apply particle swarm optimization (PSO) to improve the process of searching and matching in patch-based texture synthesis, change the throughout search method of the original algorithm; speed up the process of synthesis without influencing the quality of the image. This algorithm also accomplishes orientation control of matching patches in structure and details through appropriate parameter setting. In our proposed approach, only a single input sample is required to achieve desirable analogy results.