Revisiting radiometric calibration for color computer vision

Haiting Lin, Seon Joo Kim, Sabine Susstrunk, Michael S. Brown

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Citations (Scopus)

Abstract

We present a study of radiometric calibration and the in-camera imaging process through an extensive analysis of more than 10,000 images from over 30 cameras. The goal is to investigate if image values can be transformed to physically meaningful values and if so, when and how this can be done. From our analysis, we show that the conventional radiometric model fits well for image pixels with low color saturation but begins to degrade as color saturation level increases. This is due to the color mapping process which includes gamut mapping in the in-camera processing that cannot be modeled with conventional methods. To this end, we introduce a new imaging model for radiometric calibration and present an effective calibration scheme that allows us to compensate for the nonlinear color correction to convert non-linear sRGB images to CCD RAW responses.

Original languageEnglish
Title of host publication2011 International Conference on Computer Vision, ICCV 2011
Pages129-136
Number of pages8
DOIs
Publication statusPublished - 2011
Event2011 IEEE International Conference on Computer Vision, ICCV 2011 - Barcelona, Spain
Duration: 2011 Nov 62011 Nov 13

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other2011 IEEE International Conference on Computer Vision, ICCV 2011
Country/TerritorySpain
CityBarcelona
Period11/11/611/11/13

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

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