  Multi-view image-based rendering consists in generating a novel view of a
scene from a set of source views. In general, this works by first doing a
coarse 3D reconstruction of the scene, and then using this reconstruction to
establish correspondences between source and target views, followed by blending
the warped views to get the final image. Unfortunately, discontinuities in the
blending weights, due to scene geometry or camera placement, result in
artifacts in the target view. In this paper, we show how to avoid these
artifacts by imposing additional constraints on the image gradients of the
novel view. We propose a variational framework in which an energy functional is
derived and optimized by iteratively solving a linear system. We demonstrate
this method on several structured and unstructured multi-view datasets, and
show that it numerically outperforms state-of-the-art methods, and eliminates
artifacts that result from visibility discontinuities
