Imperial College London
Portrait Picture

ProfessorPier LuigiDragotti

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Signal Processing
 
 
 
//

Contact

 

+44 (0)20 7594 6192p.dragotti

 
 
//

Location

 

814Electrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Dragotti:2018:10.1109/TIP.2018.2852488,
author = {Dragotti, P and Huang, J},
doi = {10.1109/TIP.2018.2852488},
journal = {IEEE Transactions on Image Processing},
pages = {5234--5247},
title = {Photo realistic image completion via dense correspondence},
url = {http://dx.doi.org/10.1109/TIP.2018.2852488},
volume = {27},
year = {2018}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - In this paper, we propose an image completion algorithm based on dense correspondence between the input image and an exemplar image retrieved from the Internet. Contrary to traditional methods which register two images according to sparse correspondence, in this paper, we propose a hierarchical PatchMatch method that progressively estimates a dense correspondence, which is able to capture small deformations between images. The estimated dense correspondence has usually large occlusion areas that correspond to the regions to be completed. A nearest neighbor field (NNF) interpolation algorithm interpolates a smooth and accurate NNF over the occluded region. Given the calculated NNF, the correct image content from the exemplar image is transferred to the input image. Finally, as there could be a color difference between the completed content and the input image, a color correction algorithm is applied to remove the visual artifacts. Numerical results show that our proposed image completion method can achieve photo realistic image completion results.
AU  - Dragotti,P
AU  - Huang,J
DO  - 10.1109/TIP.2018.2852488
EP  - 5247
PY  - 2018///
SN  - 1057-7149
SP  - 5234
TI  - Photo realistic image completion via dense correspondence
T2  - IEEE Transactions on Image Processing
UR  - http://dx.doi.org/10.1109/TIP.2018.2852488
UR  - http://hdl.handle.net/10044/1/61685
VL  - 27
ER  -
Download