$L_{0}$ -Regularized Image Downscaling.

In this paper, we propose a novel L0-regularized optimization framework for image downscaling. The optimization is driven by two L0-regularized priors. The first prior, gradient-ratio prior, is based on the observation that the number of edges in the downscaled image is approximately inverse square proportional to the downscaling factor. By introducing L0 norm sparsity to the gradient ratio, the d...