and image processing
, color balance is the global adjustment of the intensities of the colors (typically red, green, and blue primary colors
). An important goal of this adjustment is to render specific colors – particularly neutral colors – correctly. Hence, the general method is sometimes called gray balance, neutral balance, or white balance. Color balance changes the overall mixture of colors in an image and is used for color correction
. Generalized versions of color balance are used to correct colors other than neutrals or to deliberately change them for effect.
Image data acquired by sensors – either film
or electronic image sensor
s – must be transformed from the acquired values to new values that are appropriate for color reproduction or display. Several aspects of the acquisition and display process make such color correction essential – including that the acquisition sensors do not match the sensors in the human eye, that the properties of the display medium must be accounted for, and that the ambient viewing conditions of the acquisition differ from the display viewing conditions.
The color balance operations in popular image editing
applications usually operate directly on the red, green, and blue channel pixel
values, without respect to any color sensing or reproduction model. In film photography, color balance is typically achieved by using color correction filter
s over the lights or on the camera lens.
Generalized color balance
Sometimes the adjustment to keep neutrals neutral is called ''white balance'', and the phrase ''color balance'' refers to the adjustment that in addition makes other colors in a displayed image appear to have the same general appearance as the colors in an original scene. It is particularly important that neutral (gray, neutral, white) colors in a scene appear neutral in the reproduction.
Psychological color balance
Humans relate to flesh tones
more critically than other colors. Trees, grass and sky can all be off without concern, but if human flesh tones are 'off' then the human subject can look sick or dead. To address this critical color balance issue, the tri-color primaries themselves are formulated to ''not'' balance as a true neutral color. The purpose of this color primary imbalance is to more faithfully reproduce the flesh tones through the entire brightness range.
Illuminant estimation and adaptation
as a reference shot for color balance adjustments.]]
File:PIA16800-MarsCuriosityRover-MtSharp-ColorVersions-20120823.jpg|thumb|right|300px|Comparison of color versions (raw, natural, white balance) of [[Mount Sharp|Mount Sharp (Aeolis Mons)
on [[Mars]] ]]
Most digital cameras have means to select color correction based on the type of scene lighting, using either manual lighting selection, automatic white balance, or custom white balance. The algorithms for these processes perform generalized chromatic adaptation
Many methods exist for color balancing. Setting a button on a camera is a way for the user to indicate to the processor the nature of the scene lighting. Another option on some cameras is a button which one may press when the camera is pointed at a gray card
or other neutral colored object. This captures an image of the ambient light, which enables a digital camera to set the correct color balance for that light.
There is a large literature on how one might estimate the ambient lighting from the camera data and then use this information to transform the image data. A variety of algorithms have been proposed, and the quality of these has been debated. A few examples and examination of the references therein will lead the reader to many others. Examples are Retinex
, an artificial neural network
[Brian Funt, Vlad Cardei, and Kobus Barnard,]
Learning color constancy
" in ''Proceedings of the Fourth IS&T/SID Color Imaging Conference,'' pp. 58–60 (1996).
or a Bayesian method
Color balancing an image affects not only the neutrals, but other colors as well. An image that is not color balanced is said to have a color cast, as everything in the image appears to have been shifted towards one color.
[John A C Yule, ''Principles of Color Reproduction.'' New York: Wiley, 1967.]
Color balancing may be thought in terms of removing this color cast.
Color balance is also related to color constancy
. Algorithms and techniques used to attain color constancy are frequently used for color balancing, as well. Color constancy is, in turn, related to chromatic adaptation
. Conceptually, color balancing consists of two steps: first, determining the illuminant
under which an image was captured; and second, scaling the components (e.g., R, G, and B) of the image or otherwise transforming the components so they conform to the viewing illuminant.
Viggiano found that white balancing in the camera's native RGB color model
tended to produce less color inconstancy (i.e., less distortion of the colors) than in monitor RGB for over 4000 hypothetical sets of camera sensitivities.
This difference typically amounted to a factor of more than two in favor of camera RGB. This means that it is advantageous to get color balance right at the time an image is captured, rather than edit later on a monitor. If one must color balance later, balancing the raw image data
will tend to produce less distortion of chromatic colors than balancing in monitor RGB.
Mathematics of color balance
Color balancing is sometimes performed on a three-component image (e.g., RGB
) using a 3x3 matrix
. This type of transformation is appropriate if the image was captured using the wrong white balance setting on a digital camera, or through a color filter.
Scaling monitor R, G, and B
In principle, one wants to scale all relative luminances in an image so that objects which are believed to be neutral
appear so. If, say, a surface with
was believed to be a white object, and if 255 is the count which corresponds to white, one could multiply all red
values by 255/240. Doing analogously for green
would result, at least in theory, in a color balanced image. In this type of transformation the 3x3 matrix is a diagonal matrix