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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:反向机密与双边滤波器在非高斯噪声污染下基于空间相关性的光流运动向量重构图像的实验研究

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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,噪声确实会降低用于确定运动矢量的光流性能。本文研究了基于空间相关性的光流中的噪声容忍模型的性能,该运动用于从运动矢量重建图像,其中源序列受到非高斯噪声的污染。有泊松噪声,盐和胡椒噪声和斑点噪声。在实验中,使用了几种不同样式的标准序列,并且将反向机密与双边滤波器在基于空间相关性的光流上的组合模型主要用于确定应用该模型的最佳条件。通过使用峰值信噪比(PSNR)作为主要研究指标,将运动矢量图像重建的结果用于与传统噪声容忍模型的性能比较。

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