Just some questions on the technology and theory behind this stuff.
People talk all about how so-and-so's color beats the other's color, but why does any of that matter when a LUT could convert one camera's image to another?
Barring bit-depth issues (although maybe I shouldn't), I assume that if we shot every camera against a chip chart, it would be trivial to design LUTs to make any footage look precisely like any other camera's footage of the same subject, color-wise.
any camera $4k and up can be matched almost exactly the same to each other. proof below:
The flavor from red's ipp2 or arri's wide gamut comes from converting electronic locus points from light freq spikes that combine to produce hues and saturation into CIE colorspace. This is accomplished across the largest gamut possible without getting banding, noise, or glare from the special matrix combiner.
If you want to match things perfectly, you first either need at least 16bit RAW or first align the total overal gamma curve perfectly before hue and saturation. This is because with any other method, aligning the individual luma values per hue would cause banding.
Each camera has their strengths and weakness for dynamic range, noise color reproduction, etc. larger cameras have professional inputs, metadata, etc. that help post workflow automatically. red has 17 f-stops dynamic range and arri firmware clips color to 50ire.
More expensive cameras support greater precision with hue linearity where the hue maintains a straight light in the vectorscope across all exposures.
If you would like to read more about this, pm me. I have consolidated many, many articles of color science into a channel.
I'd certainly be interested in reading/watching more. Gamut is something I still haven't completely wrapped my head around; the idea of cameras seeing different color-space doesn't quite make sense to me, unless it's something as simple as technical ability to "see" that color. But if the primary limitation is just avoiding banding, it at least makes more sense to me that it's tied to the quality of the data.