Fast sparse edge-based intrinsic image decomposition guided by chromaticity gradients

In this paper, we proposed a novel edge-based method for intrinsic image decomposition. To be specific, to address this ill-posed problem via single image, we employed the information of chromaticity gradient to guide recovering the reflectance gradient map, and regularized the Retinex assumption by the ℓ₀-norm to render the reflectance layer piece-wise smooth. Our method is simple but effective. Qualitative together with quantitative experiments were carried out on some public datasets. The comparison results show that our method runs much faster than the state-of-art methods with comparable performance.