A non-negative quadratic programming approach to minimize the generalized vector-valued total variation functional

We propose a simple but flexible method for solving the generalized vector-valued TV (VTV) functional with a non-negativity constraint. One of the main features of this recursive algorithm is that it is based on multiplicative updates only and can be used to solve the denoising and deconvolution problems for vector-valued (color) images. This algorithm is the vectorial extension of the IRN-NQP (Iteratively Reweighted Norm - Non-negative Quadratic Programming) algorithm [1] originally developed for scalar (grayscale) images, and to the best of our knowledge, it is the only algorithm that explicitly includes a non-negativity constraint for color images within the TV framework.