一种随机竞争学习矢量量化图像编码算法

A Stochastic Competitive Learning Vector Quantization Algorithm for Image Coding

本文分析了确定性模拟退火技术、竞争学习算法在图像编码中的压缩机理 ,提出了一种新的随机竞争学习矢量量化算法 .该算法将竞争过程与代价函数最小化结合起来 ,在学习过程中引入模拟退火 ,并针对矢量量化图像编码的特点 ,提出了新的参数选取策略 ,具有对初始码书依赖性小 ,不会局部最小 ,收敛速度快 ,码书性能好等优点 .文中还通过计算机实践对该方法进行了性能分析 ,验证了算法的有效性和鲁棒性 .

In this paper,we analyze the principles of deterministic annealing technique and competitive learning algorithm for image coding,and present a new stochastic competitive learning vector quantization algorithm for image coding.It combines the procedure of competition with the minimization of cost function.Simulated annealing is used in learning procedure,and several new strategies are presented in the vector quantization for image coding.The algorithm can eliminate the effect of initial codebook selection on the quality of clustering,is not trapped in local minimum,has a good convergence rate,and can get the codebook with good performance.Computer simulation results confirm the effectiveness and robustness of the approach.