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Volume: 26 | Article ID: art00011
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Rank-Based Radiometric Calibration
  DOI :  10.2352/J.lmagingSci.Technol.2018.62.5.050404  Published OnlineNovember 2018
Abstract

Raw images are more useful than JPEG images for machine vision algorithms and professional photographers because raw images preserve a linear relation between pixel values and the light measured from the scene. A camera is radiometrically calibrated if there is a computational model which can predict how the raw image is mapped to the corresponding rendered image (e.g., JPEGs) and vice versa. Our method makes use of the observation that the rank order of pixel values is mostly preserved post-color correction. We show that this observation is the key for getting a compact and robust radiometric calibration model. Since our method requires fewer variables, it can be solved for using less calibration data. An additional advantage is that we can derive the camera pipeline from a single pair of raw-JPEG images. Experiments demonstrate that our method delivers state-of-the-art results (especially for the most interesting conversion from JPEG to raw). © 2018 Society for Imaging Science and Technology. © 2018 Society for Imaging Science and Technology.

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  Cite this article 

Han Gong, Graham D. Finlayson, Maryam M. Darrodi, Robert B. Fisher, "Rank-Based Radiometric Calibrationin Proc. IS&T 26th Color and Imaging Conf.,  2018,  pp 59 - 66,  https://doi.org/10.2352/J.lmagingSci.Technol.2018.62.5.050404

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Copyright © Society for Imaging Science and Technology 2018
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Color and Imaging Conference
color imaging conf
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