一种快速中值滤波算法

为了克服基于排序理论的中值滤波算法中因大量的数据比较和移位而造成计算量大、运算速度慢的问题，在考虑了被滤波数据的字长和具体应用处理器的特点的基础上，提出了一种快速中值滤波算法。首先利用数据间的相关性和继承前次排序成果的基础上，快速找到采集数据的初始位置，再通过直接二分比较算法，快速确定采集数据的最终位置，且将采集数据比较次数降到n次（N=2^n-1为滤波窗口长度）；然后利用虚拟移位方法，设计一组映射数组将采集数据移位的次数降为0。通过在Keil C软件平台仿真Aduc847单片机运行实验结果表明，该算法可应用到1kHz的实时数据采集系统中。

A Fast Median Filter Algorithm

Most median filtering algorithm based on the process of sorting theory contains a large number of comparison and data shifting, slows down the speed of algorithm. In considering the filtering data word length and specific application based on the characteristics of the processor, a kind of fast median filtering algorithm is put forward. By taking advantage of the correlationship of previous- ly sorted data, the initial position of the latest acquisited data is quickly determined. By taking advantage of direct dichotomy, the final position of the latest acquisited data is quickly determined, and the number of comparison is declined to n （ N = 2^n - 1, here N is for the length of filtering window）. By designing mapping arrays ,the number of acquisited data shifting is declined to zero. Through simulating Adue847 Micro-converter on the Keil C software platform, experimental results show that this algorithm can be used in the system of 1 kHz real-time data acquisition.