Chroma Reconstruction from Inaccurate Measurements

Abstract

Non-linear filter responses of natural colour images have been shown to display non-Gaussian heavy tailed distributions which we call sparse. These filters operate in the YUV colour space on the chroma channel U (and V) using weighting functions obtained from the gray image Y. In this paper we utilise this knowledge for denoising the chroma channels of a colour image from inaccurate measurements. In our model the U (and V) elements are affected by noise, with a good version of the gray image Y obtainable through existing methods. We show that accurate reconstruction of the chroma components can be accomplished by solving an L1 constrained optimisation problem, where the sparse filter response on natural images is used as a regularization term. This scheme gives comparable results to leading commercial and state of the art denoising algorithms, and exceeds for chroma noise that does not correlate with the luminance structure.