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中文摘要：
提出了一种新的基于局部空间像素特征的椒盐噪声自适应加权滤波算法。该算法首先对含噪图像逐点进行噪声检测，把所有像素分为含噪像素点和信号像素点；然后采用自适应加权滤波方法，对检测到的噪声点进行滤波，滤波权重由确定的数学公式来确定，自适应于滤波窗内临近像素的局部特征。实验结果表明，该算法不仅可以有效地除去椒盐噪声，又可以较好地保持图像边缘细节，尤其在噪声密度较大时，效果明显优于传统的中值滤波算法。
英文摘要：
The paper proposes a new adaptive weighted average filtering algorithm based on the feature of local spatial pixels that removes the ‘salt ＆ pepper＇ noise.Firstly,all the pixels are separated into signal pixels an noise pixels according to a decision criterion,then,remove the noise pixels step by step using a new adaptive weighted average filtering algorithm that given in the following.The filtering weights are determined by a well-defined mathematical criterion,which is adaptive to the feature of neighboring pixels in the filtering window.The experiment results show that the algorithm can effectively remove the impulse noises and remains the image edge detail at the same time.Especially,the image is highly corrupted,it can provide more significant improvement than the conventional median filter.
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