遥测地形数据中粗差的自动滤除

对于地形遥测数据中引入的脉冲噪声（粗差），传统的滤波算法往往需要选择滤波门限、自适应能力不强，或者不能在滤除噪声的同时有效地保护信号数据。针对以上问题，提出了一种新颖的脉冲噪声自适应滤除算法，该算法基于数理统计和模糊数学思想，对局部数据（滤波窗口）进行均值和方差估计，并根据估计结果自动选择检噪门限，进而实现噪声检测和平滑。实验结果显示，在脉冲噪声密度小于5%时，该算法的滤波信噪比增益远高于常用滤波算法和其它同类算法；算法对平稳信号的处理效果较好。

Automatically Remove Impulse Noise from Telemetric Terrain Data

As for impulse noise removal from terrain data, traditional algorithms either us ually require thresholds manaully selected , or can't effectively preserve usefu l signal when filtering noise. To resolve the problem, This paper presents a new adaptive algorithm . The algorithm, which based on static theory and fuzzy mathe matics, evaluates the average and variance of each local data group (or named fi lter window), and then uses the results to automatically select thresholds for e ach window to detect and smooth impulse noise. The experimental results show cle arly that the growth of GSNR using this algorithm is much higher than those of other commom algorithms and similar algorithms whenever density of impulse noise is below 5%, and the algorithm is more suitable for processing steadily changed siginal.