Adaptive fuzzy filter algorithm for real-time video denoising

Jing Wu, Xin Du, Yunfang Zhu, Gu Wei-kang
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引用次数: 4

Abstract

In order to improve the perceptual quality and the compression efficiency in video transition, a new adaptive fuzzy filter algorithm for real-time Gaussian noise removal is proposed. Based on the analysis of noise and video properties, it exploits the spatiotemporal neighbor information through noise estimation, motion detection, and spatiotemporal neighborspsila similarity measurement. Then, an adaptive fuzzy filter is applied to remove noise. Experimental results showed that the proposed method achieved better performances of noise removal and detail preservation. Compared with other methods, PSNR of the denoised video was improved 1~ 6 dB. And, benefited from its low complexity and fast computation, it could meet the real-time requirements of the video transition.
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实时视频去噪的自适应模糊滤波算法
为了提高视频转换的感知质量和压缩效率,提出了一种实时去高斯噪声的自适应模糊滤波算法。该算法在分析噪声和视频特性的基础上,通过噪声估计、运动检测和时空邻居相似度测量等方法,充分利用时空邻居信息。然后,应用自适应模糊滤波器去除噪声。实验结果表明,该方法具有较好的去噪和细节保留性能。与其他方法相比,去噪后视频的PSNR提高了1~ 6 dB。该算法具有复杂度低、计算速度快的特点,能够满足视频转换的实时性要求。
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