When thinking of pixel (physical) resolution, I imagine the pixel count as sampling the spatial variations in luminance across the scene. More pixels, the greater ability to sample the undulating pattern of changing luminance values more faithfully (such as when there are high frequency patterns).
I then started thinking about Bit-depth, as the systems ability to sample the changes in the luminance’s values at a single pixel.
Thinking of it in these terms made it more clear to me the relation of bit depth to dynamic range and then I’ve read this article talking about how increasing bit depth just increases the amount of noise one captures. To be fair I don’t think I quite understand the whole of the article, but I understand that increasing bit depth allows for higher dynamic range and that it makes sense that increase bit depth also increases the accuracy at which we quantize the noise deviations. However, surely there must also be a gain of increasing bit depth.
For example, ARRI made sure that it’s 12 bit logC4 encoding has an increased Bit depth code value per exposure stop compared to its previous logC3 10bit curve, while also increasing its dynamic range.
So when does Bit depth become redundant, i.e. not visible to the human eye (just noticeable difference) or just end up recording noise (which might not be even noticed) and where does it still improve image due to improved quantization?
The link to the article I was referring to https://m.dpreview.com/articles/4653441881/bit-depth-is-about-dynamic-range-not-the-number-of-colors-you-get-to-capture
Source about ARRI log curves: Harald Brendel in Colorist meetup podcast https://open.spotify.com/episode/6CvgfAPTC0V4FIkXDXq4iV?si=djxl7cBFR3WDxjtC0MVaew
Thank you for your time and please feel free to let me know if I’ve misunderstood something.