Scientists use digital camera data as the input to their analysis of image processing algorithms. In this paper we measured the “engineered color errors” introduced by digital camera color processing. Camera manufactures build their color management systems using the sRGB design standard. Although that sRGB is a guideline in the beginning, the final firmware shows certain liberties taken to make the best preferred rendering of scenes. The ensemble of algorithms that perform the color balance, color enhancement, tone scale, and post-LUT for display and printing, create large discrepancies between the sRGB measurements of the light from the scene, and actual sRGB values in cameras. We measured these discrepancies. These modifications to scene information introduce large changes in spatial information and make computer vision algorithms less accurate. Camera firmware and software modify color separation data for better looking pictures. These modifications need to be removed for accurate scientific scene analysis. We describe a computer program that converts a RAW digital camera file to calibrated file, in which digit value is proportional to log scene radiances.
John McCann, Vassilios Vonikakis, "Accurate Information vs. Looks Good: Scientific vs. Preferred Rendering" in Proc. IS&T CGIV 2012 6th European Conf. on Colour in Graphics, Imaging, and Vision, 2012, pp 231 - 238, https://doi.org/10.2352/CGIV.2012.6.1.art00041