基于提升框架的实时视频降噪方法

针对基于离散小波变换的视频降噪方法难于实时处理的问题，提出了一种基于提升框架的可实时处理的视频降噪方法。首先，对每帧图像利用提升框架进行多级小波分解，得到尺度系数和小波系数；然后，对不同层次的小波系数采用软阈值收缩方法进行滤波；小波逆变换后，利用时间域滤波方法进一步提高降噪效果。实验结果表明，该方法具有较好的实时性和去噪效果。

A real-time video denoising method based on lifting scheme

Video denoising algorithms based on discrete wavelet transform (DWT) do not allow real-time processing due to their huge computational complexities. To overcome the shortcoming, a new real-time algorithm for video denoising based on lifting scheme was proposed. First, each frame of the video was decomposed into multi-level wavelet to obtain the scaling coefficients and the wavelet coefficients by using lifting scheme. Then, each level of wavelet coefficients was filtered by soft-threshold algorithm. After the inverse wavelet transform, temporal filter was applied on the filtered video to enhance the denoising effect further. Experiments show that this algorithm has better quality in terms of real-time processing and denoising effectiveness.