Edit Propagation via Edge-Aware Filtering  

作　　者：胡伟 董朝 袁国栋 

机构地区：[1]Department of Computer Science and Technology,Beijing University of Chemical Technology [2]Program of Computer Graphics,Cornell University [3]Department of Computer Science and Technology,Tsinghua University

出　　处：《Journal of Computer Science & Technology》2012年第4期830-840,共11页计算机科学技术学报（英文版）

基　　金：supported by the National Natural Science Foundation of China under Grant No.61003132;the National High Technology Research and Development 863 Program of China under Grant No. 2010AA012400

摘　　要：This paper presents a novel framework for efficiently propagating the stroke-based user edits to the regions with similar colors and locations in high resolution images and videos. Our framework is based on the key observation that the edit propagation intrinsically can also be achieved by utilizing recently proposed edge-preserving filters. Therefore, instead of adopting the traditional global optimization which may involve a time-consuming solution, our algorithm propagates edits with the aid of the edge-preserve filters. Such a propagation scheme has low computational complexity and supports multiple kinds of strokes for more flexible user interactions. Further, our method can be easily and efficiently implemented in GPU. The experimental results demonstrate the efficiency and user-friendliness of our approach.This paper presents a novel framework for efficiently propagating the stroke-based user edits to the regions with similar colors and locations in high resolution images and videos. Our framework is based on the key observation that the edit propagation intrinsically can also be achieved by utilizing recently proposed edge-preserving filters. Therefore, instead of adopting the traditional global optimization which may involve a time-consuming solution, our algorithm propagates edits with the aid of the edge-preserve filters. Such a propagation scheme has low computational complexity and supports multiple kinds of strokes for more flexible user interactions. Further, our method can be easily and efficiently implemented in GPU. The experimental results demonstrate the efficiency and user-friendliness of our approach.

关 键 词：edit propagation edge-aware domain transform guided filter 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]