Targeted video denoising for decompressed videos

The paradigm of using clean patches from a targeted external database to design optimal denoising filters, called Targeted Image Denoising (TID), has been shown to outperform state-of-the-art denoising algorithms such as BM3D. In this paper, we introduce Targeted Video Denoising algorithm that extends the TID algorithm to denoise decompressed video without adding complexity. Our algorithm leverages the motion vectors generated during compression to establish temporal coherency between patches in consecutive frames. We test our algorithm on three decompressed video sequences with different foregrounds, backgrounds and movement patterns, and different noise level settings. Experimental results show that our approach is effective and performs better than original TID and the state-of-the-art video denoising algorithm.