Image completion based on views of large displacement

Authors:
Chunxiao Liu;Yanwen Guo;Liang Pan;Qunsheng Peng;Fuyan Zhang
Affiliations:
af1 Zhejiang University, State Key Lab of CAD&CG, 310027, Hangzhou, China;Zhejiang University, State Key Lab of CAD&CG, 310027, Hangzhou, China and Nanjing University, National Laboratory for Novel Software Technology, 210093, Nanjing, China;Zhejiang University, State Key Lab of CAD&CG, 310027, Hangzhou, China;Zhejiang University, State Key Lab of CAD&CG, 310027, Hangzhou, China;af2 Nanjing University, National Laboratory for Novel Software Technology, 210093, Nanjing, China
Venue:
The Visual Computer: International Journal of Computer Graphics
Year:
2007

Citing 0
Cited 4

Image completion using structural priority belief propagation

MM '09 Proceedings of the 17th ACM international conference on Multimedia
Interactive Image Inpainting Using DCT Based Exemplar Matching

ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Fast query for exemplar-based image completion

IEEE Transactions on Image Processing
Interactive image completion with perspective constraint

Proceedings of the 11th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents an algorithm for image completion based on the views of large displacement. A distinct from most existing image completion methods, which exploit only the target image’s own information to complete the damaged regions, our algorithm makes full use of a large displacement view (LDV) of the same scene, which introduces enough information to resolve the original ill-posed problem. To eliminate any perspective distortion during the warping of the LDV image, we first decompose the target image and the LDV one into several corresponding planar scene regions (PSRs) and transform the candidate PSRs on the LDV image onto their correspondences on the target image. Then using the transformed PSRs, we develop a new image repairing algorithm, coupled with graph cut based image stitching, texture synthesis based image inpainting, and image fusion based hole filling, to complete the missing regions seamlessly. Finally, the ghost effect between the repaired region and its surroundings is eliminated by Poisson image blending. Our algorithm effectively preserves the structure information on the missing area of the target image and produces a repaired result comparable to its original appearance. Experiments show the effectiveness of our method.