Abstract | ||
---|---|---|
Seamless image composition is a widely-used technique for digital image re-creation. Poisson image editing is an effective approach for seamless editing using guided interpolation. However, when applied to image composition with quite different tone in source and target images, like distinct illumination or color distribution, its performance often degrades rapidly owing to deficient user-drawn boundary and immoderate color transition. In this paper, we propose a new solution based on Poisson image editing to keep the coherent tone in the composition result. We firstly employ matting technique to help user effortlessly locate the object of interest. Meanwhile, we build transition zones to coordinate the influence from source and target images with the matte from matting techniques. Then we construct a mixed guided vector based on transition zones to implement the tone adjustment. An effective method is also proposed to find the optimal mixed guided vector. At last, we utilize this optimal vector into Poisson solution. Our method can avoid the drawbacks of Poisson image editing between scenes with distinct tone and produce enjoyable composition results. Experiment results demonstrate the effectiveness of our seamless image composition method. |
Year | DOI | Venue |
---|---|---|
2011 | 10.1145/2087756.2087776 | VRCAI |
Keywords | Field | DocType |
composition result,target image,coherent tone adjustment,image composition,digital image re-creation,seamless image composition,enjoyable composition result,seamless image composition method,matting technique,transition zone,poisson image editing,digital image | Poisson image editing,Computer vision,Image gradient,Computer graphics (images),Effective method,Computer science,Interpolation,Layers,Digital image,Artificial intelligence,Poisson distribution | Conference |
Citations | PageRank | References |
2 | 0.37 | 12 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Li Yong | 1 | 262 | 29.92 |
Zhifeng Xie | 2 | 53 | 10.70 |
Bin Sheng | 3 | 368 | 61.19 |
Yan Gui | 4 | 2 | 0.37 |
Lizhuang Ma | 5 | 498 | 100.70 |