Infuse chroma subsampling downscaling algorithm and ChatGPT

I had this conversation with ChatGPT and I’d like to know your opinion:

Question 1: Imagine we want to display one movie on an HD display means 1080p. We have two versions of the same movie. One is a Blu-ray version with a 30 GB size (you can calculate the bitrate). This means that this movie has been encoded with h.264 codec and 4:2:0 chroma subsampling. The other version is a 4k version with a 30 GB size; this one is encoded with h.265 codec and 4:2:0 chroma subsampling. This version needs to be downscaled to 1080. Tell me, what will be happened to its chroma subsampling?

Answer: When downscaling a 4K video to 1080p, the chroma subsampling of the video remains the same. In this case, both the Blu-ray version (1080p, H.264) and the 4K version (H.265) have 4:2:0 chroma subsampling. This means that for both versions, color information is sampled at half the resolution of the luma (brightness) information…

Question 2: Why do you think when it is down-sampled, its chroma subsampling ratio remains at 4:2:0? For each, we have more information. When downsampling, we have four times the data compared to the 1080 version.

You are correct that when downscaling a 4K video to 1080p, you have more information available compared to a native 1080p version. However, the chroma subsampling ratio remaining at 4:2:0 in the downscaled version is a simplification, as the actual result depends on the downscaling algorithm used.

Some downscaling algorithms may take advantage of the additional color information available in the 4K video and produce a higher effective chroma subsampling in the downscaled 1080p version. This could potentially result in better color reproduction and finer color details compared to a native 1080p video with 4:2:0 chroma subsampling.