Video de-noising method based on 3D wavelet transform and block context model

A video de-noising method based on the 3D Wavelet Transform and Block Context Model (3DWTBCM) is proposed according to the strong correlation between the two frames of video sequence. On the basis of the characteristics of the coefficients in 3D wavelet domain and noise distribution, wavelet coefficients are partitioned into subblocks firstly in the light of local relativity of these coefficients and then the Context model is used in the corresponding subblocks. The wavelet coefficients in each block are divided into several parts by means of their energy distribution in the 3D Context model and each part is estimated by its independent energy distribution. Finally, suitable thresholds are obtained. Experimental results show that 3DWTBCM achieves better de-noising performance than hierarchical 2D de-noising methods and its PSNR is improved more than 0.5-1.2 dB on average in comparison with those of common 3D de-noising methods. In terms of visual quality, 3DWTBCM can effectively preserve the video detail while de-noising the wavelet coefficients and especially can provide video frames with rapid movements and more textures.