A camera pipeline that allows accurate post-capture white balance editing (CIC best paper award, 2019)
http://cvil.eecs.yorku.ca/projects/public_html/ColorTemperatureTuning/
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Reference code for the paper:
Mahmoud Afifi, Abhijith Punnappurath, Abdelrahman Abdelhamed, Hakki Can Karaimer, Abdullah Abuolaim, and Michael S. Brown. Color temperature tuning: Allowing accurate post-capture white-balance editing. Color Imaging Conference (CIC), 2019 -- best paper award.
We propose an imaging framework that renders a small number of “tiny versions” of the original image (e.g., 0.1% of the full-size image), each with different white-balance (WB) color temperatures. Rendering these tiny images requires minimal overhead from the camera pipeline. These tiny images are sufficient to allow color mapping functions to be computed that can map the full-sized sRGB image to appear as if it was rendered with any of the tiny images’ color temperature. Moreover, by blending the color mapping functions, we can map the output sRGB image to appear as if it was rendered through the camera pipeline with any color temperature. These mapping functions can be stored as a JPEG comment with less than 6 KB overhead. We demonstrate that this capture framework can significantly outperform existing solutions targeting post-capture WB editing.
인용 양식
Afifi, Mahmoud, et al. “Color Temperature Tuning: Allowing Accurate Post-Capture White-Balance Editing.” Color and Imaging Conference, vol. 2019, no. 1, Society for Imaging Science & Technology, Oct. 2019, pp. 1–6, doi:10.2352/issn.2169-2629.2019.27.2.
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