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> dithered images compress poorly If you think about error diffusion dithering in particular on a 1-bit palette - Information theory dictates that you are kind

> dithered images compress poorly If you think about error diffusion dithering in particular on a 1-bit palette - Information theory dictates that you are kind of pushing entropy limits as-is. Compression is still possible, but to get any kind of realistic gain it's going to have to be slow compression. Piping stuff like 1-bit dithered graphics through fast, lossy JPEG/MPEG-style compressors (i.e. quantized DCT) will yield absolute garbage results.

jarenmf 4y ago
Could you please elaborate on the link of error diffusion to information theory? as far as I understand error diffusion minimizes the quantization error for lower frequencies on the expense of adding more noise to higher frequencies. i.e it seems to be only optimizing for human perception
- bob1029 4y ago
  You're right - in pure information theoretic terms there is nothing special happening here. It's a tradeoff like always. But, in human perceptual terms (i.e. how JPEG/MPEG are designed), you may find substantial gain in useful information per bit by applying dithering. The useful amount of information represented by any given bit of data is much larger in this arrangement. 1 bit = 1 entire pixel. In other schemes, you have upwards of 24 bits representing the contents of 1 pixel. To human eyes, only 8 of these bits really matter. You can usually throw away 50% of the other 16 without anyone noticing.
Someone 4y ago
>> dithered images compres poorly > Piping stuff like 1-bit dithered graphics through fast, lossy JPEG/MPEG-style compressors (i.e. quantized DCT) will yield absolute garbage results. Of course dithered images compress poorly when using compression algorithms that aren’t designed for them, but I don’t see why, a priori, they should when the choice of compressor is free. That current compressors for photos are better than those for dithered graphics may only be because there has been way more research in compression of photos than in that of dithered pictures. You could, for example, try to compress a dithered image not by running a JPEG compressor designed for photographic images, but by searching for (search algorithm TBD) a low quality JPEG file that, when dithered, produces an image that is perceptually similar to the original dithered image. For photos, I would expect that JPEG file to look better than its dithered version, but if the input is a dithered photo, I’m not sure. Even if it is, such an approach might still be useful. And JPEG likely isn’t the optimal compressed format. But dithered images is a niche market, so I don’t expect we’ll ever know how good these images can be compressed. Even the demo scene probably won’t work on this. They wouldn’t build a generic compressor, just one that compresses the images in their current demo well.

jarenmf 4y ago

Could you please elaborate on the link of error diffusion to information theory? as far as I understand error diffusion minimizes the quantization error for lower frequencies on the expense of adding more noise to higher frequencies. i.e it seems to be only optimizing for human perception

bob1029 4y ago
You're right - in pure information theoretic terms there is nothing special happening here. It's a tradeoff like always. But, in human perceptual terms (i.e. how JPEG/MPEG are designed), you may find substantial gain in useful information per bit by applying dithering. The useful amount of information represented by any given bit of data is much larger in this arrangement. 1 bit = 1 entire pixel. In other schemes, you have upwards of 24 bits representing the contents of 1 pixel. To human eyes, only 8 of these bits really matter. You can usually throw away 50% of the other 16 without anyone noticing.

Someone 4y ago

>> dithered images compres poorly > Piping stuff like 1-bit dithered graphics through fast, lossy JPEG/MPEG-style compressors (i.e. quantized DCT) will yield absolute garbage results. Of course dithered images compress poorly when using compression algorithms that aren’t designed for them, but I don’t see why, a priori, they should when the choice of compressor is free. That current compressors for photos are better than those for dithered graphics may only be because there has been way more research in compression of photos than in that of dithered pictures. You could, for example, try to compress a dithered image not by running a JPEG compressor designed for photographic images, but by searching for (search algorithm TBD) a low quality JPEG file that, when dithered, produces an image that is perceptually similar to the original dithered image. For photos, I would expect that JPEG file to look better than its dithered version, but if the input is a dithered photo, I’m not sure. Even if it is, such an approach might still be useful. And JPEG likely isn’t the optimal compressed format. But dithered images is a niche market, so I don’t expect we’ll ever know how good these images can be compressed. Even the demo scene probably won’t work on this. They wouldn’t build a generic compressor, just one that compresses the images in their current demo well.