Point two cameras at the same leaf, in the same light, and they record different numbers. Not slightly different after processing — different at the moment the shutter closes. The reason is not the gamut setting in the menu. It is the colour filters sitting over the silicon, and they were fixed before the camera left the factory.
Two ideas get collapsed here, and separating them is the whole point. A colour gamut is a triangle in a colour space, fixed by three primaries and a white point: it describes what a set of numbers can represent. Spectral sensitivity is something else — the curves describing how strongly each filter responds at each wavelength. Those curves slope, peak and taper, and they overlap with each other. What a camera can distinguish comes from the curves. What its numbers mean comes from the gamut. Different filter stacks produce different numbers from identical light, and no gamut tag changes that.
The Filter Stack Is the Gamut
Light hits the sensor. It passes through a Bayer filter mosaic. Each pixel sees only a narrow band of wavelengths. The red filter passes long wavelengths, the blue filter passes short ones, and the green filter sits in the middle. But these filters are not perfect cut-offs. They have transition zones. Where the red and green filters overlap, the sensor receives a mix. The shape of that overlap defines the gamut’s vertices.
A camera optimized for skin tones has a specific relationship between its red and green channels. Human skin falls into a narrow, predictable range of hues. To maximize detail in that range, manufacturers shape the filter curves so that the red and green responses are tightly controlled. This often means compressing the dynamic range of other hues. Greens, which sit near the green channel’s peak, get squeezed. The sensor physically cannot distinguish between a bright, saturated green and a duller one as easily as it can distinguish between two shades of beige. The gamut is narrower in that region. It is not a bug. It is the cost of optimizing for one subject.
A camera optimized for landscapes does the opposite. It widens the green channel’s sensitivity to capture the full spread of foliage, from shadowed pine needles to sunlit grass. The red channel might be less precise. The gamut stretches in the green-yellow region. The scene looks "richer" to the eye because the sensor is resolving more distinct hues in that part of the spectrum. The physics is the same. The curves are just shaped differently.
Why This Happens Before Processing
You cannot fix a gamut limitation in post-processing. You can map colors. You can stretch a histogram. You can apply a lookup table. But you cannot recover information that the silicon never recorded. If the red and green filters overlap heavily, the sensor merges those wavelengths into a single signal. That information is gone. No algorithm can separate it back out. It is like trying to unmix paint after it has dried.
This is why two cameras shooting the same scene produce different raw files. The raw file is not a neutral record. It is a specific interpretation of the light. The spectral sensitivity curves are baked into the data. A "white balance" correction just shifts the entire spectrum. It does not change the shape of the gamut. It does not change how the sensor distinguished red from green in the first place.
Film works the same way, but with chemistry. The dyes in the emulsion have specific absorption curves. A slide film like Fuji Velvia 50 is engineered to push green saturation. The green dye layer is more sensitive and more saturated than in a portra-style negative. The film stock itself has a gamut. It is not a neutral canvas. It is a colored filter with a preference. When you shoot Velvia, you are accepting that green will be loud and skin tones might shift. The chemistry decides the gamut. Your camera settings do not.
The Detector Defines the Reality
We talk about "color accuracy" as if there is a true color to be found. There is not. There is only light hitting a detector. The detector’s response curve is the reality. If your sensor’s green channel peaks at 550nm, that is where it sees green. If another sensor peaks at 540nm, it sees a slightly different green. Both are correct. Both are limited. The gamut is the boundary of what that specific silicon can resolve.
Understanding this changes how you shoot. You stop blaming the "bad color science" of a camera and start looking at the filter design. You realize that a camera great for portraits might struggle with vibrant floral arrangements not because of a bad algorithm, but because the physical filters compress that part of the spectrum. The gamut is the shape of the detector. It is not a setting. It is the hardware’s opinion of the world.
The practical consequence is that matching two cameras is not a matter of tagging them with the same colour space. It is a matter of measuring how each one responds and building a transform from that measurement. Try it in the Cineon studio.
For a deeper dive into how color spaces define these boundaries, read our piece on ACES. It explains how a working color space can hold the gamut of multiple sensors without crushing them. But the core truth remains: the gamut is born in the silicon. It is not made in the software.