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Old 23rd February 2021, 18:09   #1  |  Link
YaBoyShredderson
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What exactly makes something compressible??

Just a general question here, i already know that motion requires more bitrate, noise/grain requires more bitrate, lots of complex motion like confetti or snow can have a similar effect to noise, but what else? I have the bluray for pennyworth season 1 and it seems to be the most easily compressed content i have. Using veryslow crf 18 film tune with x264, i was often getting just a couple of mbits, even tho the average for that preset was more like 10 to 12. X265 veryslow crf 20 was often less than 1 mbit, maybe 600-800 kbits. This is all 1080p24. Nothing in particularl stands out to me why this would be so easily compressed. Its not noisy, but its no cleaner than some other content. Theres a fair amount of action, i have lots of stuff with less. So what makes this so easy?
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Old 24th February 2021, 13:55   #2  |  Link
Forteen88
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Probably also more details, like a blanket with different colors, patterns and shadows is less compressible than a single-color non-pattern blanket.
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Old 24th February 2021, 22:06   #3  |  Link
RanmaCanada
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Most media these days are shot on solid state, so there is no film grain. Film grain makes a HUGE difference in compressibility.
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Old 25th February 2021, 00:38   #4  |  Link
benwaggoner
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The key thing in all modern codecs is that they convert from the spatial domain (pixels) to the frequency domain (how pixel values change over a region). For an IDR frame, slight and regular changes between adjoining pixels take fewer bits to encode well, and large and irregular changes require more bits to encode well, because it takes a lot more frequencies to add up to the final result. It's the same thing temporally; the more a frame is like the frames it references, the fewer bits it takes. With motion estimation, if there's a very good match between an area of a frame and a frame it references, that can be coded in very few bits. If there's not a good match, a lot more bits are needed to code the difference between the best match and where in the new frame it is referenced from.

Psychovisual factors come in play as well. Noisy areas, like foliage, can withstand more aggressive compression because the artifacts aren't that different than the original texture. But a little blocking in a smooth gradient can be painfully obvious.

Sharp grain/noise is the hardest, because it is high frequencies randomly distributed, so hard to encode for an IDR frame, and overlays everything with that, so prediction is a lot less accurate.

The Film Grain Synthesis approach is compelling, as it just does a grain removal pass during encoding, parameterizes the grain that was removed, and then reconstructs it on playback. All going well, you get the same grain texture, but at a lower bitrate as the encoding itself is grain-free. AV1 is the first reasonably mainstream codec to have mandatory support of FGS in all decoders.

Of course, grain removal, grain parameterization, and grain synthesis have been hard problems for a few decades, and aren't solved by any means. FGS implementations are getting incrementally better, but aren't at the "just check that box and it'll come out fine" stage.
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Old 25th February 2021, 00:43   #5  |  Link
benwaggoner
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Quote:
Originally Posted by RanmaCanada View Post
Most media these days are shot on solid state, so there is no film grain. Film grain makes a HUGE difference in compressibility.
Solid state sensors still can have gain noise, which has pretty similar compression challenges as grain. Bigger sensors, longer exposures, and brighter lighting all help reduce that, just like they did with analog film.

In a given situation most digital cameras are going to be a lot better than typical 35mm film, but digital cameras also get used in situations where no one would have even tried to use film before.

Supersampling is valuable here, where the sensor has more individual picture elements than the editing format it'll be converted to. Note that a sensor's pixels are either Red, Green, or Blue, while encoded pixels each have Red, Green and Blue values. So 4K camera to 4K post actually requires some spatial upsampling as part of the conversion from the Bayer pattern sensor to a video format.
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