Double-Opponent Vectorial Total Variation

We present a new vectorial total variation (VTV) method that addresses the problem of color consistent image filtering. Our approach combines insights based on the double-opponent cell representation in the visual cortex with state-of-the-art variational modelling using VTV regularization. Existing methods of vectorial total variation regularizers have insufficient (even no) coupling between the color channels and thus may introduce color artifacts. We address this problem by introducing a novel color channel coupling inspired from a pullback-metric from an opponent space to the observation space. We show existence and uniqueness of a solution in the space of vectorial functions of bounded variation. In experiments, we demonstrate that our novel approach compares favorably to state-of-the-art methods w.r.t. to structure coherence and color consistency.