DocumentCode :
949597
Title :
Robust Radiometric Calibration and Vignetting Correction
Author :
Kim, Seon Joo ; Pollefeys, Marc
Author_Institution :
North Carolina Univ., Chapel Hill
Volume :
30
Issue :
4
fYear :
2008
fDate :
4/1/2008 12:00:00 AM
Firstpage :
562
Lastpage :
576
Abstract :
In many computer vision systems, it is assumed that the image brightness of a point directly reflects the scene radiance of the point. However, the assumption does not hold in most cases due to nonlinear camera response function, exposure changes, and vignetting. The effects of these factors are most visible in image mosaics and textures of 3D models where colors look inconsistent and notable boundaries exist. In this paper, 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 process in a manner that is robust to noise and outliers. We verify our algorithm with both synthetic and real data, which shows significant improvement compared to existing methods. We apply our estimation results to radiometrically align images for seamless mosaics and 3D model textures. We also use our method to create high dynamic range (HDR) mosaics that are more representative of the scene than normal mosaics.
Keywords :
brightness; calibration; computer vision; image segmentation; image texture; 3D model textures; computer vision systems; high dynamic range mosaics; image brightness; image mosaics; image textures; nonlinear camera response function; robust radiometric calibration; scene radiance; vignetting correction; Radiometric response function; high dynamic range imaging; radiometricimage alignment; vignetting; Algorithms; Artifacts; Calibration; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Photography; Radiometry; Reproducibility of Results; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2007.70732
Filename :
4359347
Link To Document :
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