Name
Abstract | ||
|---|---|---|
We present an example-based approach for radiometrically linearizing photographs that takes as input a radiometrically linear exemplar image and a target regular uncalibrated image of the same scene, possibly from a different viewpoint and/or under different lighting. The output of our method is a radiometrically linearized version of the target image. Modeling the change in appearance of a small image patch seen from a different viewpoint and/or under different lighting as a linear 1D subspace, allows us to recast radiometric transfer in a form similar to classic radiometric calibration from exposure stacks. The resulting radiometric transfer method is lightweight and easy to implement. We demonstrate the accuracy and validity of our method on a variety of scenes. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1111/cgf.12683 | COMPUTER GRAPHICS FORUM |
Keywords | Field | DocType |
Categories and Subject Descriptors (according to ACM CCS),I,3,8 [Computer Graphics]: Applications,I,4,1 [Image Processing and Computer Vision]: Digitization and Image CaptureRadiometry | Radiometric dating,Computer vision,Radiometric calibration,Computer graphics (images),Subspace topology,Computer science,Image processing,Radiometry,Artificial intelligence,Linearization | Journal |
Volume | Issue | ISSN |
34.0 | 4.0 | 0167-7055 |
Citations | PageRank | References |
2 | 0.38 | 20 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Han Li | 1 | 6 | 0.78 |
| Pieter Peers | 2 | 1109 | 55.34 |