Different camera brands process colors in slightly different ways, similar to how different chefs cook the same dish differently. For instance, the colors that come out of Sony cameras are more accurate, while colors from Canon cameras are often said to be more pleasing. Why does this happen? To answer this question, Gerald Undone is here with a video about camera color science:
What is Color Science?
In general, users tend to use the term color science to describe how the colors come out with a particular camera brand. However, the topic is much more vast and technical in nature.
“Color science is the study of the psychological and physiological components of color generation and color vision.”
How Cameras Get Their Unique Colors
Information carried by light rays to the camera sensor is subject to a lot of variables. It can be altered by the environment, reflections off of the different objects around the camera and the subject, the lens filter through which the light passes, and also the various lens elements. All these components determine the accuracy of the light striking the sensor.
Before the light strikes the camera sensor, it has to go through a color filter called the Bayer filter. This filter is responsible for providing color information to the sensor. To make the colors appear unique, camera manufacturers tweak this filter. The Bayer filter has an array of red, blue, and green filters in a square grid in which every 2×2 section has two greens, one red, and one blue filter. This filter is also subject to imperfections and can change the nature of light passing through them. Camera manufacturers can manipulate this “imperfection” by design to get their unique look.
Pretty Colors Don’t Relate to Accuracy
Now that you understand how manufacturers tweak the colors, you should also know that they can make colors look more pleasing. And pleasing colors don’t mean accurate colors. Also, accurate colors may not appear pleasing to everyone. For instance, Undone shares that while Sony systems produce the most accurate colors, many people find them unflattering.
“Some people prefer an accurate, even if uglier image, so that they can develop the picture the way they want from a more precise starting point. But other people just need great-looking JPEGs right off the card.”
Does it Even Matter?
Undone feels that debating over which color science is the best doesn’t make sense. Here are his three arguments to support his idea:
- The concept of “pleasing colors” is really subjective. There is no right or wrong way to express color. Also, pleasing colors are not necessarily accurate.
- Beginners are the ones who’d benefit the most from having the most pleasing colors straight out of the camera. But they don’t have a preference over which camera they’d use.
- If a user is really aware of the complexities of color science across different brands, then chances are they’re experienced with processing images. This means that they can adapt colors to their taste. Color science doesn’t matter to them either.
So why bother discussing color science? Is it just to say something positive about a brand that we love? Or to promote how little effort we need to put into creating an image that we feel is pleasing? In both the cases, it doesn’t matter at all.
What practical implications do different color sciences have? The answer to this question comes down to the nature of your projects. Some projects that you work on may have a very narrow window for delivery. For such cases, you’d be better off using a camera system that directly delivers pleasing looking images.
“If you remove time completely from the equation, I would almost never recommend that you buy a camera based solely on its color processing algorithms because other specs and usability are going to be much more important.”
However, if you want maximum creative control, a balanced, feature-rich camera and a lot of data in your images, Undone suggests that you ignore all the stuff about color science and focus on the features that really matter.
Does the way a camera brand renders color affect your buying decision?
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