In many computer vision systems, it is assumedthat the image brightness of a point directly reflects the scene radiance of the point. However, the assumption does not hold inmost cases due to nonlinear camera response function, exposure changes, and vignetting. The effects of these factors are mostvisible in image mosaics and textures of 3D models where colors look in consistent and notable boundaries exist. In thispaper, we propose a full radiometric calibration algorithm that includes robust estimation of the radiometric response function, exposures, and vignetting. By decoupling the effect of vignetting from the response function estimation, we approach each processin a manner that is robust to noise and outliers. We verifyour algorithm with both synthetic and real data which showssignificant improvement compared to existing methods. We applyour estimation results to radiometrically align images for seamlessmosaics and 3D model textures. We also use our methodto create high dynamic range (HDR) mosaics which are more representative of the scene than normal mosaics.
|Number of pages||15|
|Journal||IEEE transactions on pattern analysis and machine intelligence|
|Publication status||Published - 2008 Apr|
Bibliographical noteFunding Information:
The authors gratefully acknowledge the support of the US NSF Career Award IIS 0237533 and a Packard Fellowship for Science and Technology. We would also like to thank Dan Goldman, Anatoly Litvinov, and Yoav Schechner for providing us with the data and the code for experiments.
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics
- Artificial Intelligence
- Applied Mathematics