Some Notes.

According to Chrome Stats from Google 2019 [1], ~80% to 85% of images served are above bpp 1.0 ( Bit per Pixel ). Around ~95% are above bpp 0.5. I doubt this have changed if not gotten worse as images gets larger over the years.

There are images such as logo or specific patterns that works a lot better and compressed at low bpp ( below 0.5 ). But those are rare on web, and in the case here, most of the images are photography.

Which means at sub 0.3 bpp it is a ridiculously low bitrate even for Web photo.

HEIC on iPhone 17 is based on HEVC, H.265 hardware encoder on iPhone 17.

VVC / VTM is H.266 Codec, the successor of HEVC / H.265 most people may have heard of one of its encoder called x265.

ETM is H.267 Codec, currently the best in class video compression codec that is still in development.

I assume everyone knows about AV1 and AV2 already since we are on HN.

CPU Encoder, generally speaking produce better image quality while hardware encoder tends to be fast but lower quality. Both HEIC and AV1 are based on hardware encoder on the iPhone 17. ( At least that is my read of it )

In case anyone wondering. JPEG XL is not designed or yet to be optimised for low bpp. It excels at 0.8 bpp onwards depending of type of image. So the result of XL would likely be very bad. Similarly to normal JPEG and H.264 encoder.

I am wondering if this image codec is deterministic.

I would imagine if we use this on the web the actual image size would be a lot smaller. Meaning a lot of the artifacts we see shouldn't matter. And clicking on it would bring up a different image file.

There is finally a possibility in the future some half decent image could be included within 14K frame of the webpage.

Encoding and Decoding speed is actually useable on today's hardware. Decoding in sub 100ms on iPhone 17.

And on another notes, VVC is doing extremely well in terms of compression rate and encoding / decoding complexity.

AV2 launching by the end of this month.

[1] Figure 1

https://www.spiedigitallibrary.org/conference-proceedings-of...

Perceptual Image Codec: What Matters in Practical Learned Image Compression