Image editing using level set trees

An efficient method for precise computation of image-aware geodesic distances for image editing algorithms is proposed. It exploits the connection between image representation as a mapping from a Cartesian grid and as a collection of its level sets, organized into a tree structure. The distance computation is reformulated in the domain of the image level sets, where it can be calculated without introducing approximation errors, which are unavoidable when working the image domain. Advantages of the proposed approach are demonstrated for image segmentation application.