Efficient antialiased edit propagation for images and videos

Edit propagation on images/videos has become more and more popular in recent years due to simple and intuitive interaction. It propagates sparse user edits to the whole data following the policy that nearby regions with similar appearances receive similar edits. While it gives a friendly editing mode, it often produces aliasing artifacts on edge pixels. In this paper, we present a simple algorithm to resolve this artifact for edit propagation. The key in our method is a new representation called Antialias Map, in which we represent each antialiased edge pixel by a linear interpolation of neighboring pixels around the edge, and instead of considering the original edge pixels in solving edit propagation, we consider those neighboring pixels. We demonstrate that our work is effective in preserving antialiased edges for edit propagation and could be easily integrated with existing edit propagation methods such as [1] and [2].

An example of edit propagation. (a) shows the original image and user strokes. (b) and (c) show the propagation results using the k-d-tree method and our method, respectively. Alias artifacts are visible in (b) along the boundary of the building. Our method successfully eliminate these artifacts, as shown in (c).Figure optionsDownload high-quality image (126 K)Download as PowerPoint slideHighlights
► We introduce a new representation called Antialias Map for antialiased pixels.
► We introduce a novel, efficient framework to eliminate aliasing artifacts in edit propagation.
► We demonstrate that our work is effective in preserving antialiased edges for common edit propagation methods.