  Shadows often create unwanted artifacts in photographs, and removing them can
be very challenging. Previous shadow removal methods often produce de-shadowed
regions that are visually inconsistent with the rest of the image. In this work
we propose a fully automatic shadow region harmonization approach that improves
the appearance compatibility of the de-shadowed region as typically produced by
previous methods. It is based on a shadow-guided patch-based image synthesis
approach that reconstructs the shadow region using patches sampled from
non-shadowed regions. The result is then refined based on the reconstruction
confidence to handle unique image patterns. Many shadow removal results and
comparisons are show the effectiveness of our improvement. Quantitative
evaluation on a benchmark dataset suggests that our automatic shadow
harmonization approach effectively improves upon the state-of-the-art.
