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IMAGE SEQUENCES FILTERING USING ADAPTIVE WEIGHTED AVERAGING FILTER WITHOUT ESTIMATING NOISE VARIANCE

机译:在不估计噪声方差的情况下使用自适应加权平均滤波器滤波图像序列

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In this paper, we will propose a novel spatiotemporal filter that utilizes consecutive frames in order to remove noise. The consecutive frames include: current, previous and next noisy frames. The filter proposed in this paper is based upon the weighted averaging pixels intensity in image sequences. The weights are determined by a well-defined mathematical criterion, which is adaptive to the feature of spatiotemporal pixels of the consecutive frames. It is experimentally shown that the proposed filter can preserve image structures and edges under motion while suppressing noise, and thus can be effectively used in image sequences filtering. Most importantly, our proposed filter is independent of noise variance and only utilizes the intensity of pixels to suppress noise. This is a significant advantage to the other proposed filters in [1], [2], [3] and [4], which most widely make use of noise variance in order to remove noise.
机译:在本文中,我们将提出一种新颖的时空滤波器,该滤波器利用连续的帧来去除噪声。连续帧包括:当前,上一个和下一个噪声帧。本文提出的滤波器基于图像序列中的加权平均像素强度。权重由定义明确的数学准则确定,该准则适合于连续帧的时空像素的特征。实验表明,所提出的滤波器可以在抑制噪声的同时保留运动中的图像结构和边缘,因此可以有效地用于图像序列滤波。最重要的是,我们提出的滤波器与噪声方差无关,并且仅利用像素的强度来抑制噪声。这是[1],[2],[3]和[4]中其他建议的滤波器的一个显着优势,它们最广泛地利用噪声方差来消除噪声。

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