基于混洗蛙跳和粒子群优化算法的块自增纹理合成

摘要

针对基于样图的纹理合成技术,提出了一种基于混洗蛙跳和粒子群优化算法的块自增纹理合成方法.该方法在纹理合成过程中,通过选取尺寸按2的倍数不断增大的纹理块来提高纹理合成的速度,将混洗蛙跳算法和粒子群算法相结合,作为纹理块匹配的寻优策略,以提高纹理块的查找速度和全局搜索性能.实验结果表明,该方法在保证纹理合成质量的前提下,能够显著地提高基于样图的纹理合成速度,并能克服粒子群算法易陷入局部最优解的缺陷.%A texture synthesis algorithm based on Shuffled Frog Leaping Algorithm and Particle Swarm Optimization (SFLA-PSO) and block increasing was proposed for example-based synthesis.It can be used to speed up texture synthesizing through using the texture block of which size was increased two times during the process of texture synthesis.As texture block matching optimum strategy, SFLA and PSO were combined to accelerate and improve the global searching performance.The experimental results prove that the algorithm can significantly accelerate the speed of example-based synthesis on the premise of fine synthesis quality, and also can overcome the defect of easily falling into local optimal solution of PSO algorithm.