基于改进人工蜂群的图像矢量量化码书设计算法

Codebook design algorithm for image vector quantization based on improved artificial bee colony

为了进一步提高图像矢量量化的码书质量,提出了一种新的图像压缩矢量量化码书设计算法。该算法采用均方误差(MSE)作为码书设计的适应度函数,利用改进的人工蜂群算法进行适应度函数的优化求解,增强了算法的自组织性和收敛性,大大减少了陷入局部收敛的可能性。将一种基于和值特性的快速码字搜索思想引入到码书设计算法中,使算法计算量明显降低。仿真结果表明,该算法具有计算时间短、收敛速度快的优点,并且生成的码书质量好、稳定性强。

A new vector quantization image compression algorithm based on an improved artificial bee colony was proposed for improving the quality of the code book. In this method, Mean Squared Error （MSE） was used as fitness function and the improved artificial bee colony algorithm was used to optimize it. The self-organization and convergence of the algorithm were improved. At the same time, the possibility of falling into local convergence was reduced. In order to reduce calculation amount of the algorithm, a fast codebook search idea based on sum of vectors was inroduced into the process of fitness function calculation. The simulation results show that the algorithm has the advantages of time-saving calculation and rapid convergence, and the quality and robustness of the codebook generated by this algorithm are good.