通过假设预测方位和实测方位差值服从零均值的高斯分布，利用贝叶斯理论来修正各滤波器的权重。
And the weight of each filter is updated using Bayes theory based on the assumption that the difference between estimate and measurement bearings obeys Gaussian distributions with zero mean error.
通过介绍一种易于实现的自适应权重中值滤波器(AWMF)。
The paper presents an easily applicable adaptive weighted median filter (AWMF).
通过与均值滤波、中值滤波的对比实验，自适应权重中值滤波器表现出良好的滤波特性，而且它在抑制噪声的同时，较大限度地保持住图象的边沿特征。
By the comparative tests with the mean filter and the median filter, the AWMF performs best features in the reduction of noise and keeping edge information of images.
通过与均值滤波、中值滤波的对比实验，自适应权重中值滤波器表现出良好的滤波特性，而且它在抑制噪声的同时，较大限度地保持住图象的边沿特征。
By the comparative tests with the mean filter and the median filter, the AWMF performs best features in the reduction of noise and keeping edge information of images.
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