Modeling Radiometric Uncertainty for Vision with Tone-Mapped Color Images

TitleModeling Radiometric Uncertainty for Vision with Tone-Mapped Color Images
Publication TypeJournal Article
Year of Publication2014
AuthorsXiong, Y., Scharstein D., Chakrabarti A., Darrell T., Sun B., Saenko K., & Zickler T.
Published inIEEE Transactions on Pattern Analysis and Machine Intelligence
Other Numbers3697

To produce images that are suitable for display, tone-mapping is widely used in digital cameras to map linear color measurements into narrow gamuts with limited dynamic range. This introduces non-linear distortion that must be undone, through a radiometric calibration process, before computer vision systems can analyze such photographs radiometrically. This paper considers the inherent uncertainty of undoing the effects of tone-mapping. We observe that this uncertainty varies substantially across color space, making some pixels more reliable than others. We introduce a model for this uncertainty and a method for fitting it to a given camera or imaging pipeline. Once fit, the model provides for each pixel in a tone-mapped digital photograph a probability distribution over linear scene colors that could have induced it. We demonstrate how these distributions can be useful for visual inference by incorporating them into estimation algorithms for a representative set of vision tasks.


This work was partially supported by funding provided through National Science Foundation grants no. IIS-0905243, IIS-0905647, IIS-1134072, IIS-1212798, IIS-1212928, IIS-0413169, and IIS-1320715; by DARPA under the Mind’s Eye and MSEE programs; and by Toyota. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors or originators and do not necessarily reflect the views of the NSF, DARPA, the U.S. Government, or Toyota.

Bibliographic Notes

IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 36, No. 11, pp. 2185-2198

Abbreviated Authors

Y. Xiong, D. Scharstein, A. Chakrabarti, T. Darrell, B. Sun, K. Saenko, and T. Zickler

ICSI Research Group


ICSI Publication Type

Article in journal or magazine