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Experimental study on image reconstruction from spatial correlation-based optical flow motion vector over non Gaussian noise contamination using reversed confidential with bilateral filter

机译:基于空间相关的光流动运动矢量的图像重建的实验研究,使用双边滤波器反转机密的非高斯噪声污染

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In motion estimation, noise is a verity to degrade the performance in optical flow for determining motion vector. This paper examines the performance of noise tolerance model in spatial correlation-based optical flow for image reconstruction from motion vector where the source sequences are contaminated by non Gaussian noise. There are Poisson Noise, Salt & Pepper Noise, and Speckle Noise. In the experiment, several standard sequences in different styles are used and the applied combination model of reversed confidential with bilateral filter on spatial correlation-based optical flow is mainly focused to determined the best condition to apply this model with. The result in image reconstruction from motion vector is used in performance comparison with traditional noise tolerance models by using Peak Signal to Noise Ratio (PSNR) as a primary index for studying.
机译:在运动估计中,噪声是降低光流中的性能的真实,以确定运动矢量。本文研究了从非高斯噪声污染的运动矢量图像重建的基于空间相关的光流量的噪声容差模型的性能。有泊松噪音,盐和辣椒噪音和斑点噪音。在实验中,使用不同风格的若干标准序列,并使用基于空间相关的光流量的双侧滤波器反向机密的应用组合模型主要集中于确定应用该模型的最佳条件。通过使用峰值信号与噪声比(PSNR)作为学习的主要索引来实现与传统噪声公差模型的性能比较中的图像重建的结果。

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