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A Novel Video Denoising Method Based on Surfacelet Transform

机译:一种基于Surfacelet变换的新型视频去噪方法

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In this paper, we propose a novel video denoising method applying 3D Context Model in Surfacelet Transform domain (3DCMST). Because of its directional decomposition, perfect reconstruction and low redundancy, ST has being become a powerful tool in image processing and analysis. In order to take fully advantage of the characteristic of the coefficients in ST domain, the Context model is extended from 2D to 3D, which can accomplish true 3D denoising processing. The coefficients of ST are divided into several classes according to their energy distribution by 3D Context model, and each class has independent energy estimate and threshold respectively. Experimental results show that 3DCMST has a good denoising performance in quality and fidelity. It is especially suitable for the video frame proceeding with furious movement and plenty of texture.
机译:在本文中,我们提出了一种新的视频去噪方法,在Surfacelod转换域中应用3D上下文模型(3DCMST)。由于其定向分解,完善的重建和低冗余,St已成为图像处理和分析中的强大工具。为了充分利用ST域中系数的特性,上下文模型从2D到3D扩展,这可以实现真正的3D去噪处理。 ST的系数根据其3D上下文模型的能量分布分为几个类别,每个类分别具有独立的能量估计和阈值。实验结果表明,3DCMST质量和保真度具有良好的去噪。它特别适用于视频帧进行愤怒的运动和充足的纹理。

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