Comparison of the Optical Flow Quality for Video Denoising

Nelson Monzón, Javier Sánchez

Abstract

Video denoising techniques need to understand the motion present in the scenes. In the literature, many strategies guide their temporal filters according to trajectories controlled by optical flow. However, the quality of these flows is rarely investigated. In fact, there are very few studies that compare the behavior of denoising proposals with different optical flow algorithms. In that direction, we analyze several methods and their performance using a general pipeline that reduces the noise through an average of the pixel’s trajectories. This ensures that the denoising strongly depends on the optical flow. We also analyze the behavior of the methods at occlusions and illumination changes. The pipeline incorporates a process to get rid of these effects, so that they do not affect the comparison metrics. We are led to propose a ranking of optical flows methods depending on their efficiency for video denoising, that mainly depends on their complexity.

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