基于镜像阈值分解的层叠滤波器优化

层叠滤波器的优化设计是层叠滤波理论研究中最为关键的问题.阈值分解是层叠滤波器的特性之一,它有传统阈值分解和镜像阈值分解2种形式,镜像阈值分解定义的层叠滤波器不仅具有低通滤波的特性,还具有带通和高通的特性.文中在MAE准则下,提出一种基于镜像阈值分解的快速自适应层叠滤波器优化算法,该算法在迭代过程中约束代价向量的层叠性并判断其收敛性,最终获得最优层叠滤波器的正布尔函数.通过仿真实验验证最优层叠滤波器的性能.结果表明该算法设计的层叠滤波器具有良好的细节保持能力和去噪声能力,有效地改善了滤波性能.

Optimization of stack filters based on mirrored threshold decomposition

Optimizing stack filters is the most pivotal issue of the study of stack filters theory.The threshold decomposition is one of stack filters property and has two modes: traditional threshold decomposition and mirrored threshold decomposition.The stack filters defined in the binary domain of mirrored threshold decomposition have been empowered not only with lowpass filtering characteristics but with bandpass and highpass characteristics as well.In this paper,under MAE criterion,a fast adaptive optimization algorithm based on mirrored threshold decomposition is presented.This algorithm restricts stacking properties of cost vector and estimates its astringency in order to attain positive Boolean function of optimal stack filters.The performance of optimal stack filters is illustrated by simulations.The results of experiments show that the optimal stack filters can suppress noise and protect the details of image effectively,which improve filtering capability.