Basic Color and Imaging Concepts

Color correction involves controlling both an image’s contrast and its color (exercising separate control over its hue and saturation). This section explains these important imaging concepts so that you can better understand how the Color tools let you alter the image. For detailed information, see:

Contrast Explained

Contrast adjustments are among the most fundamental, and generally the first, adjustments made. Contrast is a way of describing an image’s tonality. If you eliminate all color from an image, reducing it to a series of grayscale tones, the contrast of the picture is seen by the distribution of dark, medium, and light tones in the image.

Controlling contrast involves adjustments to three aspects of an image’s tonality:

  • The black point is the darkest pixel in the image.

  • The white point is the brightest pixel in the image.

  • The midtones are the distribution of all tonal values in between the black and white points.

    Figure. Comparing black, mids, and white point in an image and its histogram.

An image’s contrast ratio is the difference between the darkest and brightest tonal values within that image. Typically, a higher contrast ratio, where the difference between the two is greater, is preferable to a lower one. Unless you’re specifically going for a low-contrast look, higher contrast ratios generally provide a clearer, crisper image. The following two images, with their accompanying Histograms which show a graph of the distribution of shadows, midtones, and highlights from left to right, illustrate this.

Figure. Comparing low and high contrast images and histograms.

In addition, maximizing the contrast ratio of an image aids further color correction operations by more evenly distributing that image’s color throughout the three tonal zones that are adjusted with the three color balance controls in the Primary In, Secondaries, and Primary Out rooms. This makes it easier to perform individual corrections to the shadows, midtones, and highlights.

For more information about adjusting image contrast, see Contrast Adjustment Explained.

Luma Explained

Luma (which technically speaking is gamma-corrected luminance) describes the exposure (lightness) of a video shot, from absolute black, through the distribution of gray tones, all the way up to the brightest white. Luma can be separated from the color of an image. In fact, if you desaturate an image completely, the grayscale image that remains is the luma.

Luma is measured by Color as a digital percentage from 0 to 100, where 0 represents absolute black and 100 represents absolute white. Color also supports super-white levels (levels from 101 to 109 percent) if they exist in your shot. While super-white video levels are not considered to be safe for broadcast, many cameras record video at these levels anyway.

Figure. Illustration of luma range.

Note: Unadjusted super-white levels will be clamped by the Broadcast Safe settings (if they’re turned on with their default settings), so that pixels in the image with luma above 100 percent will be set to 100 percent.

What Is Setup?

People often confuse the black level of digital video with setup. Setup refers to the minimum black level assigned to specific analog video signals and is only an issue with analog video output to the Beta SP tape format. If you are outputting to an analog tape format using a third-party analog video interface, you should check the documentation that came with that video interface to determine how to configure the video interface for the North American standard for setup (7.5 IRE) or the Japanese standard (0 IRE). Most vendors of analog video interfaces include a software control panel that allows you to select which black level to use. Most vendors label this as “7.5 Setup” versus “0 Setup,” or in some cases “NTSC” versus “NTSC-J.”

Video sent digitally via SDI has no setup. The Y′CBCR minimum black level for all digital video signals is 0 percent, 0 IRE, or 0 millivolts, depending on how you’re monitoring the signal.

Gamma Explained

Gamma refers to two different concepts. In a video signal, gamma refers to the nonlinear representation of luminance in a picture displayed on a broadcast or computer monitor. Since the eye has a nonlinear response to light (mentioned in The Y′CBCR Color Model Explained), applying a gamma adjustment while recording an image maximizes the perceptible recorded detail in video signals with limited bandwidth. Upon playback, a television or monitor applies an inverted gamma function to return the image to its “original” state.

You want to avoid unplanned gamma adjustments when sending media from Final Cut Pro to Color. It’s important to keep track of any possible gamma adjustments that occur when exporting or importing clips in Final Cut Pro during the editing process, so that these adjustments are accounted for and avoided during the Final Cut Pro–to–Color roundtrip. For more information on gamma handling in Final Cut Pro, see the Final Cut Pro 7 User Manual.

Gamma is also used to describe a nonlinear adjustment made to the distribution of midtones in an image. For example, a gamma adjustment leaves the black point and the white point of an image alone, but either brightens or darkens the midtones according to the type of adjustment being made. For more information on gamma and midtones adjustments, see The Primary In Room.

Chroma Explained

Chroma (also referred to as chrominance) describes the color channels in your shots, ranging from the absence of color to the maximum levels of color that can be represented. Specific chroma values can be described using two properties, hue and saturation.


Hue describes the actual color itself, whether it’s red or green or yellow. Hue is measured as an angle on a color wheel.

Figure. Illustration of hue wheel.


Saturation describes the intensity of that color, whether it’s a bright red or a pale red. An image that is completely desaturated has no color at all and is a grayscale image. Saturation is also measured on a color wheel, but as the distance from the center of the wheel to the edge.

Figure. Illustration of saturation range.

As you look at the color wheel, notice that it is a mix of the red, green, and blue primary colors that make up video. In between these are the yellow, cyan, and magenta secondary colors, which are equal mixes of the primary colors.

Primary and Secondary Color Relationships Explained

Understanding color wheel interactions will help you to see how the Color controls actually affect colors in an image.

Primary Colors

In any additive color model, the primary colors are red, green, and blue. These are the three purest colors that can be represented, by setting a single color channel to 100 percent and the other two color channels to 0 percent.

Secondary Colors

Adding any two primary colors produces a secondary color. In other words, you create a secondary color by setting any two color channels to 100 percent while setting the third to 0 percent.

  • Red + green = yellow

  • Green + blue = cyan

  • Blue + red = magenta

One other aspect of the additive color model:

  • Red + green + blue = white

All these combinations can be seen in the illustration of three colored circles below. Where any two primaries overlap, the secondary appears, and where all three overlap, white appears.

Figure. Illustration of primary and secondary color interactions.

Complementary Colors

Two colors that appear 180 degrees opposite each other on the wheel are referred to as complementary colors.

Figure. Illustration of complementary colors on color wheel.

Adding two complementary colors of equal saturation to each other neutralizes the saturation, resulting in a grayscale tone. This can be seen in the two overlapping color wheels in the illustration below. Where red and cyan precisely overlap, both colors become neutralized.

Figure. Illustration of complementary colors neutralizing one another.

Understanding the relationship of colors to their complementaries is essential in learning how to eliminate or introduce color casts in an image using the Color Primary or Secondary color correction controls. For example, to eliminate a bluish cast in the highlights of unbalanced daylight, you add a bit of orange to bring all the colors to a more neutral state. This is covered in more detail in The Primary In Room.

The HSL Color Space Model Explained

The HSL color space model is another method for representing color and is typically used for user interface controls that let you choose or adjust colors. HSL stands for hue, saturation, and lightness (roughly equivalent to luminance) and provides a way of visualizing the relationships among luminance, hue, and saturation.

The HSL color space model can be graphically illustrated as a three-dimensional cone. Hue is represented by an angle around the base of the cone, as seen below, while saturation is represented by a color’s distance from the center of the cone to the edge, with the center being completely desaturated and the edge being saturated to maximum intensity. A color’s brightness, then, can be represented by its distance from the base to the peak of the cone.

Figure. Illustration of the HSL color space in three dimensions.

Color actually provides a three-dimensional video scope that’s capable of displaying the colors of an image within an extruded HSL space, for purposes of image analysis. For more information, see The 3D Scope.