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Sometimes taking a neutral position on things like color balance isn’t really the safe or smart thing to do – sometimes it’s downright dangerous!
The camera term for color balance is White Balance, although we measure gray cards rather than white surfaces. Why? The difference isn’t about semantics, it’s about math.
Neutral gray colors (yes, gray is a color) are all composed of equal measurable parts of each RGB color, while pure white contains no measurable color at all. Photographic gray cards are absolutely color-neutral. We don’t use white cards simply because you can’t measure data that doesn’t exist.
What we perceive as white in a photograph more often than not contains trace amounts of red, green, or blue. Just enough to throw the color balance of the photo way off center if used as a reference (try it and you’ll see).
The Gray Balance tools in Photoshop and Lightroom will neutralize whatever color you click on, so always pick a gray patch rather than a white one. The ColorChecker includes a row of neutral gray patches, none of them being pure white.
The human eye is very forgiving in this respect. It perceives white in a very assumptive manner. White paper viewed under color light still appears white because of what we call memory colors, a cognitive database of repeated experience. If we associate a color with an object often enough, we establish a link between the two.
Not so with the camera. Its sensors have no such recollection and are not so forgiving. This is why you must balance color in Photoshop and Lightroom by referencing known neutral gray elements in the photo to known values.
Your camera’s Auto White Balance, or AWB, is what is relied on by most shooters because the flawed assumption that cameras recognize light like we humans do. Actually, the cameras are dumb electronic devices that evaluate light more clinically than do our eyes. Our brain’s cerebral cortex parses the hues of light according to our memory color catalog.
Whether under candlelight or sunlight, fluorescent or tungsten, sunset or noonday, a white sheet of paper will always appear white because your brain retains the associative reference. Your brain compensates for almost every color of light, delivering a believable impression of what you’ve come to think of as reality.
No matter when you see these memory color items, your brain registers these colors and in a sense, overrides the actual color of the light. Unfortunately, this is not true for (digital or film) cameras.
Trusting that the camera’s AWB will correctly diagnose light and set the proper color interpretation is a flawed and risky assumption fraught with problems.
First, in the language of RGB color, equal values of red, green, and blue (like red 128, green 128, and blue 128) light produce an absolutely neutral gray color. This is an absolute of color science.
In order for the camera’s AWB algorithm to deliver accurate color, it must assume that there exists a detectable and absolutely neutral gray component in the scene. A pretty wild assumption considering that there are over 16,000,000 colors in the visible spectrum.
The camera then examines the light reflecting from objects in the scene and locks onto the cluster of pixels whose RGB values are closest to equal (regardless of how dissimilar). The AWB mandate then forces those colors to become absolutely neutral value while twisting all other colors in the scene in a similar manner.
This is all well and good IF that cluster of pixels in the captured scene actually is, in reality, neutral (gray) in color. The corrected values will then actually balance the colors in the image and produce an image that looks “real”.
But, if the scene does not have an absolutely neutral component – if there is a bluish somewhat-gray item in the scene but is not truly neutral gray (like the snow scene below) – then the image processor in your camera will dutifully and obediently change that bluish color to neutral gray, and shift all the other colors in the scene in the same direction on the color wheel.
While your eyes and your cerebral cortex use memory colors to forgive any color cast in a scene, they do not afford that same corrective assumption to photographic images. If the collection of pixels or printed dots produce off-color results, your perception will register and report “bad color”.
Your camera is not smart, it is simply efficient and obedient. It will obey anything you tell it to do. It’s a machine, it is not a volitional entity. It has neither reasoning power nor color-compensating algorithms.
Your camera may claim to have “intelligence,” but that intelligence is merely scripted logic, sometimes labeled artificial intelligence (the keyword here is “artificial”). You are the only one with actual intelligence. You must tell the camera what to do, NOT the other way around.
Take control of the situation and set your camera’s white balance setting according to the current lighting conditions. Your options include manual pre-sets for all typical lighting situations: Daylight, Cloudy, Shade, Tungsten, Fluorescent, Flash, and usually a couple of custom setups.
There is a time to use your white balance tools to reference true neutral gray in the scene to set the gray balance in your photos, and there is a time to keep those items in your camera bag. The truth is, neutralizing every image can literally suck the natural color right out of a scene.
A gray balance tool placed in the scene (for an initial test shot) will serve as the gray balance reference for correcting any color casts in images captured in that scene.
This correction takes place after the capture when the test image is opened in Adobe Lightroom, Camera Raw, or Photoshop. When the White Balance tool is applied to a reference gray in the test image, all photos open at the time can be color corrected automatically.
This is truly a great way to accurately set the lighting balance within a series of photos taken during a single session.
Unless the scene contains “emotional” light such as candlelight, sunrise/sunset, late afternoon or early morning light, nightlife/neon, etc. If the scene to be captured contains this kind of emotional (or mood) lighting, the very mood can effectively be neutered by the white balance process. Shooter beware.
The cool shadows that are evident in the image on the left are typical of moonlight reflecting off the snow. Setting the camera’s color mode to Daylight, allowed the tungsten lamplight to capture warm lighting amidst the cold snow, recording the scene exactly as I experienced it.
In the picture on the right, the camera’s White Balance was set to AWB, assuming that this “automatic” setting would capture the colors of the image faithfully. Oops! In truth, AWB actually lost the shivering cold lighting altogether.
In both of the above cases, white/neutral balance routines were employed, and the ambiance of both scenes was dutifully destroyed. By forcing each unique lighting to be neutralized, both the warmth of the sun and the frigid look of the night snow were lost.
There is no single, always-right color balance setting on the camera. In fairness, most times the AWB setting in the camera and gray balance in the editing software work out very nicely.
But occasionally the “intelligent” camera and the powerful editing software need smarter input. That means you. Using a known neutral color element in the picture as a reference allows you to become the color expert.
So what have we learned? There is a time for White Balance just as there is a time for political correctness. BUT to force the strict application of either in every situation can destroy the spirit of free expression.
Use gray balance only when emotional/mood lighting isn’t present and when a good gray component is in the scene. Too many dramatic scenes get neutered (or neutralized) in the name of neutrality.
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