User Manual

The Goals of Color Correction
If reality is a fire hose of visual information, then digital cinema and broadcast would be
represented by a garden hose. Color correction, therefore, could be considered the process of
choosing which parts of the fire hose of raw image data to fit into the garden hose of our
displays in order to create a pleasing image for the viewer.
Maximizing the Look of Your Media
Clearly, the most fundamental aspect of the color correction process is that of making every clip
look its best. While the job of the cinematographer is to light and expose the image with an
artistic intent, your job is to realize this intent by making adjustments to the color and contrast of
the image, so that the final result is as close to what the director and cinematographer had in
mind as is humanly possible. In the process, you have the opportunity to overcome
inconsistencies with exposure and white balance that were, for various reasons, unavoidable.
Furthermore, you can make subtle adjustments to add warmth or contrast that was not available
during the shoot, but that the cinematographer would have liked.
Increasingly, color correction is seen as a critical stage in the post-production process. For
example, the newer generation of digital cinema cameras are capable of shooting raw
colorspace image data, or RGB image data with a log exposure, in order to preserve the
maximum amount of image data for manipulation during the color correction process. However,
when you acquire image data this way, it must be transformed into a viewable image via color
correction in the same way that film negative must first be developed and printed to
positive film.
Log encoded source
Normalized and corrected
Source footage courtesy of Gianluca Bertone DP, www.bertonevisuals.com
Of course, there are also situations in which you may find it necessary to attempt to fix source
media with far more substantial problems in color and exposure. In these cases, the tools exist
to make far more involved adjustments to the image; however, the quality of your results will
depend heavily on the data quality and “latitude” of your source media.
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