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首页> 外文会议>Conference on Image Processing: Algorithms and Systems III; 20040119-20040121; San Jose,CA; US >Motion and Detail Adaptive Denoising of Video
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Motion and Detail Adaptive Denoising of Video

机译：视频的运动和细节自适应去噪

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摘要

Non-linear techniques for denoising images and video are known to be superior to linear ones. In addition video denoising using spatio-temporal information is considered to be more efficient compared with the use of just temporal information in the presence of fast motion and low noise. Earlier, we introduced a 3-D extension of the A'-nearest neighbor filter and have investigated its properties. In this paper we propose a new, motion- and detail-adaptive filter, which solves some of the potential drawbacks of the non-adaptive version: motion caused artifacts and the loss of fine details and texture. We also introduce a novel noise level estimation technique for automatic tuning of the noise-level dependent parameters. The results show that the adaptive A'-nearest neighbor filter outperforms the none-adaptive one, as well as some other state-of-the-art spatio-temporal filters such as the 3D α-trimmed mean and the state-of-the-art rational filter by Ramponi from both a PSNR and visual quality point of view.
机译：已知用于对图像和视频进行去噪的非线性技术要优于线性技术。另外，与存在快速运动和低噪声的情况下仅使用时间信息相比，使用时空信息的视频去噪被认为更加有效。之前，我们介绍了A'最近邻滤波器的3-D扩展，并研究了它的特性。在本文中，我们提出了一种新的，具有运动和细节自适应功能的滤波器，该滤波器解决了非自适应版本的一些潜在缺点：运动引起的伪像以及精细细节和纹理的丢失。我们还介绍了一种新颖的噪声级估计技术，用于自动调整噪声级相关参数。结果表明，自适应A'近邻滤波器的性能优于非自适应滤波器，以及其他一些最新的时空滤波器，例如3Dα修剪均值和时态滤波器。从PSNR和视觉质量的角度来看，Ramponi都提供了先进的理性滤波器。

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