Rank-based radiometric calibration

Han Gong, Graham D. Finlayson, Maryam M. Darrodi, Robert B. Fisher

Research output: Contribution to journalArticlepeer-review

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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 are 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).
Original languageEnglish
Pages (from-to)50404-1-50404-8
Number of pages8
JournalJournal of Imaging Science and Technology
Volume62
Issue number5
Early online date26 Sep 2018
DOIs
Publication statusPublished - 26 Sep 2018

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