White balance is a
crucial step in the photographic pipeline. It ensures the proper
rendition of images by eliminating color casts due to differing
illuminants. Digital cameras and editing programs provide white
balance tools that assume a single type of light per image, such as
daylight. However, many photos are taken under mixed lighting. We
propose a white balance technique for scenes with two light types that
are specified by the user. This covers many typical situations
involving indoor/outdoor or flash/ambient light mixtures. Since we
work from a single image, the problem is highly underconstrained. Our
method recovers a set of dominant material colors which allows us to
estimate the local intensity mixture of the two light types. Using
this mixture, we can neutralize the light colors and render visually
pleasing images. Our method can also be used to achieve post-exposure
relighting effects.
The following thumbnails link to full-resolution,
lossless-compression, 16-bit, PNG-format images for
all results in our paper. They are about 10
megabytes each.
Below, we compare the results
of standard white balance (left), the Local Color
Shifts model [Ebner
2004] (middle), and our technique (right).
| Average White Balance |
Local Color Shifts |
Our Result |
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Below, we use synthetic input images (left) to produce
ground truth results (center) and compare them to
our results (right). Difference images are shown in
our paper.
| Input Image |
Ground Truth |
Our Result |
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Light mixtures can be used to achieve interesting
lighting effects. In this set of images, we modify
the lighting to achieve a sunset effect.
| Input Image |
Our Result |
New Lighting |
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In the following set of images, we dim the interior and exterior lights.
| Our Result |
Dim Interior |
Dim Exterior |
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Stay tuned for additional results!
We would like to thank the Adobe Creative Technology
Labs, the MIT Computer Graphics Group, and Bill
Freeman for their helpful advice. Frédo Durand
acknowledges a Microsoft Research New Faculty
Fellowship and a Sloan Fellowship. Tom Mertens
acknowledges a research fellowship from the Belgian
American Educational Foundation. Part of the research
at Expertise Centre for Digital Media is funded by the
European Regional Development Fund and the Flemish
government.
