Error-tolerant Image Compositing

M.W. Tao, M.K. Johnson and S. Paris

European Conference on Computer Vision, 2010


Gradient-domain compositing is an essential tool in computer vision and its applications, e.g. seamless cloning, panorama stitching, shadow removal, scene completion and reshuffling. While easy to implement, these gradient-based techniques often generate bleeding artifacts where the composited image regions do not match. One option is to modify the region boundary to minimize such mismatches. However, this option may not always be sufficient or applicable, e.g., the user or algorithm may not want the selection to be altered. We propose a complementary approach to gradient-based compositing that is robust to inaccuracies and prevents color bleeding without changing the boundary location. Our approach improves standard gradient compositing in two ways. First, we define the boundary gradients such that the produced gradient field is nearly integrable. Second, we control the integration process to concentrate residuals where they are less conspicuous. We show that our approach can be formulated as a standard least-squares problem that can be solved with a sparse linear system akin to the classical Poisson equation. We demonstrate results on a variety of scenes. The visual quality compares favorably to other approaches.


Code and additional results can be found on this page.





This material is based upon work supported by the National Science Foundation under Grant No. 0739255. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.