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首页> 外文期刊>天津大学学报（英文版） >Modified Adaptive Weighted Averaging Filtering Algorithm for Noisy Image Sequences
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Modified Adaptive Weighted Averaging Filtering Algorithm for Noisy Image Sequences

机译：改进的噪声图像序列自适应加权平均滤波算法

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摘要

In order to avoid the influence of noise variance on the filtering performances, a modified adaptive weighted averaging (MAWA) filtering algorithm is proposed for noisy image sequences. Based upon adaptive weighted averaging pixel values in consecutive frames, this algorithm achieves the filtering goal by assigning smaller weights to the pixels with inappropriate estimated motion trajectory for noise. It only utilizes the intensity of pixels to suppress noise and accordingly is independent of noise variance. To evaluate the performance of the proposed filtering algorithm, its mean square error and percentage of preserved edge points were compared with those of traditional adaptive weighted averaging and non-adaptive mean filtering algorithms under different noise variances. Relevant results show that the MAWA filtering algorithm can preserve image structures and edges under motion after attenuating noise, and thus may be used in image sequence filtering.
机译：为了避免噪声方差对滤波性能的影响，针对噪声图像序列提出了一种改进的自适应加权平均（MAWA）滤波算法。基于连续帧中的自适应加权平均像素值，该算法通过为噪声具有不适当的估计运动轨迹的像素分配较小的权重，从而实现了滤波目标。它仅利用像素的强度来抑制噪声，因此与噪声方差无关。为了评估所提出的滤波算法的性能，将其均方误差和保留边缘点的百分比与不同噪声方差下传统的自适应加权平均和非自适应均值滤波算法进行了比较。相关结果表明，MAWA滤波算法能够在衰减噪声后保留运动状态下的图像结构和边缘，可用于图像序列滤波。

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