Video denoising using 3-D Hybrid Wavelets and Directional filter banks
We propose a new family of nonredundant 3D directional transforms that are useful for video signals. In our construction, taking into account the correlation amongst frames of video, we first decorrelate the temporal data using a stage of 1D wavelet transform and then we employ the efficient 2D Hybrid Wavelets and Directional filter banks (HWD) transform family to the resulting spatial data where we achieve 3D HWD transform family. We construct translation-invariant version of the proposed family and show its efficiency in video denoising compared to other wavelet-based methods through several experiments.