Illumination-invariant non-local means based video denoising

In this paper, we present a robust illumination-invariant non-local means (NLM) based video denoising algorithm with special illumination handling. Illumination variances pose a challenge to the NLM-based denoising algorithms. To address this issue, we first propose several possible technical improvements, and verify their efficacy of eliminating the influence of illumination changes. Then, by analyzing and comparing these techniques, a histogram processing based technique is integrated into the non-local means denoising framework. Experimental results on synthesis and real video denoising show that the proposed method is able to fully explore the non-local self-similarity property in natural videos under variable illumination conditions.