Video denoising algorithm via multi-scale joint luma-chroma bilateral filter

Abstract

Video denoising is important for display and subsequent analysis, but remains to be a challenging problem. Key insights that limit the performance of algorithms include two main aspects. First, low-frequency scene information and the coarse-grained noise in the chroma are mixed with each other, which is different from that in the luma. Thus, denoising the chroma by using only its own information is difficult. Second, it is impossible to directly use the denoised luma edge information to guide the chroma denoising for high quality results. Therefore, in this paper, we propose a multi-scale joint luma-chroma bilateral filter to improve chroma denoising performance. Experimental results demonstrate that the proposed algorithm surpasses state-of-the-art algorithms in most cases.

CFA Bayer image sequence denoising and demosaicking chain

“…A similar approach is used by Kim et al [35] but a purely temporal denoising algorithm is applied first, and a second purely spatial after the enhancement stage. Gao et al [23] perform a bilateral filter in both luminance and chrominance (YCbCr) for each frame, for which the bilateral weight distribution is computed only on the luminance. A multiscale wavelet transform permits to deal with non white noise.…”