Adaptive video denoising using block matching 3-D filtering

Reducing noise in a video sequence is of vital importance in many applications. Despite the fact that many good video denoising methods were proposed in recent years, there is still a need to further improve the existing video denoising methods. Video block matching 3-D filtering (VBM3D), which was developed by Dabov et al. in 2007, is one of the recent state-of-the-art video denoising methods of interest. In the VBM3D, it is assumed that the noise standard deviation for the whole video sequence is known in advance. This is an important drawback of this method. In this paper, we propose a new method to reduce the noise in a video frame adaptively. If the noise standard deviation of the video frame is less than a threshold τ₀, then we do not apply any denoising method on it. If, on the other hand, the noise standard deviation is greater than τ₀, and there are k>;0 video frames with noise standard deviation σ_n(j) satisfying |σ_n(j) - σ_n(i)| <; ε for j∈[i +1,...,i +k], then we apply VBM3D on the k video frames in order to reduce the noise in these video frames. If the next video frame does not satisfy |σ_n(i +1) - σ_n(i)|<;ε, then we apply the 2-D block matching 3-D filtering (BM3D) method to denoise it. We conducted some experiments to reduce the noise in several video sequences, and we found out that our proposed method outperforms VBM3D for denoising video sequences with different noise levels.