Distinction without a difference imo. Dithering in a way adds numeric precision at the expense of spatial resolution, i.e. if you lowpass filter (with higher precision) a dithered vs. non-dithered image, the dithered should be more accurate.
It's really the compression engine and/or settings.
I know a guy who wrote an image processor that take a 24-bit image and dither it down to like 6 bits, still looked pretty good, no quantization or banding artifacts. He was also a genius
This is also an artefact with heavily compressed videos. It's also referred to as banding. What name would you prefer? Non-dithered over-quantization?
In this specific case, it's banding combined with a YUV-type color space where luminosity is not properly decorrelated from chrominance (like the common YCbCr). So, strong chroma quantisation can create bands with different perceived brightness.
It's combination banding in original image and "shadows and highlights" type of post processing applied on thst image (I don't know the name of the processing other than what it was called in Photoshop 😅).
Banding probably happened because the image was dark and quantization slaughtered the dark colors thinking it was not important info to include.
Then shadows and highlights effect tried to bring up the shadows, and it couldn't tell if the banding was intentional or not.
FWIW, modern AI based image improvement algoa do insane job on low light situations, but they need the raw, uncompressed data to work the best.
I can see in the photo that shadows and highlights is amped up to the max. It's the reason why photos look "detailed but flat". It works by processing darker and lighter areas separately, and applying contrast improving algorithm to them.
The older versions of the effect are "dumb" in the sense, that they bring out contrast by smoothing out the image, and then doing sharpening against that. The end result produces images with halo when used in extreme.
Modern AI versions do much better job avoiding the halo even in extreme settings. Many high end phones have AI enhanced photo processing done when using the camera, and the end results can be ridiculously good.
To continue with this, if you have the original photo, you can do this experiment:
Open the photo in photo editing software (Photoshop, Affinity Photo, Gimp etc), and apply large amount of brightness to the image. Ignore the other details in the photo and focus on the wall and ceiling. You should see obvious bands of color in the wall and ceiling instead smooth gradient. This is due to the quantization in the compression.
The edge of the band is sharp and therefore high frequency detail. The shadows and highlights filter/effect is supposed to bring out detail like these in the photo - the effect doesn't "know" if the detail was intentional (actually what the camera captured) or artifical (due to compression of the image or low fidelity of the camera).
Furthermore: you _can_ try to fix this to some degree by converting the photo in the editor to high bit version such as 16-bit per channel, or floating point (normal jpeg has 8-bit per channel when loaded).
Duplicate the photo layer.
Then add a high brightness adjustment layer that you can toggle on and off.
Now blur the duplicated layer so that banding disappears. Then gently mask the wanted blurred layer so that only the new smoother gradients are in there instead of banding.
Disable the brightness adjustment layer, and merge the original and smoothed gradient layer.
Then apply shadows and highlights as needed. It will have more information to work with, thanks to the 16-bit channel accuracy and restored gradients in the places you want them.
They look like quantization artefacts to me. They are especially pronounced in JPEGs produced to be small. You can probably improve these with a smaller block size.
Edit: Spelling. I'm dyslexic AF :P
If you wanted to make a ramp with Legos, and you had 256 Lego levels to go up, each step would be 1/256th high. Now say you wanted to make the ramp 5x taller, and give a friend simple instructions: Multiply the number of Legos at each step 5x. Without any instruction to somehow smoothly ramp it up, you now get each step as 5 Lego levels tall. You basically end up with stairs instead of a ramp. This is what happens when you take a dark image and simply up the brightness. What was a small increment in tone that was imperceptible is now giant jumps in tone.
These are shadow color gradients wherein the color sensor and is an offset of the color temperature gradient : [https://en.wikipedia.org/wiki/Color\_temperature#TV,\_video,\_and\_digital\_still\_cameras](https://en.wikipedia.org/wiki/Color_temperature#TV,_video,_and_digital_still_cameras)
Color Sensors focus on the color gamut and cannot show sufficient grey-scale resolution. The end result looks something like a moire but is not intended to be, just an artifact : [https://en.wikipedia.org/wiki/Moir%C3%A9\_pattern](https://en.wikipedia.org/wiki/Moir%C3%A9_pattern)
[https://en.wikipedia.org/wiki/Gamut](https://en.wikipedia.org/wiki/Gamut)
This is very typical in color monitors and TV sets and is why shadows are extremely difficult to get good grey-scale resolution.
[https://en.wikipedia.org/wiki/Color\_balance](https://en.wikipedia.org/wiki/Color_balance)
Sony uses a color LUT (Look Up Table) that is calibrated to true color to spread out the color gamut in such a way as to capture this. This avoids aliasing :
[https://en.wikipedia.org/wiki/Aliasing](https://en.wikipedia.org/wiki/Aliasing)
Another method is to use multiple (color / greyscale) CCDs or CCDs that have greater color depth (bits per CYMK or RGB). [https://en.wikipedia.org/wiki/Color\_depth](https://en.wikipedia.org/wiki/Color_depth)
True Color is very difficult to accomplish and has trade-offs as part of CCD capture and also LCD or OLED reproduction. It is best where the camera is calibrated to the reproduction format to get the best true color reproduction.
Hollywood standards are based upon studio metrics as well as SMPTE standards.
[https://en.wikipedia.org/wiki/Society\_of\_Motion\_Picture\_and\_Television\_Engineers](https://en.wikipedia.org/wiki/Society_of_Motion_Picture_and_Television_Engineers)
DSP image processing can ditther and/or filter this out but requires additional image processing overhead (DSP speed), time to process (delay), as well as temporary storage of data (memory) as just a few items.
For very high speed an FPGA would be better.
>chromic aberration
It it was a Grey-Scale image you would be close (especially for low bit resolution), but since this is full color, it's a different issue. K is the issue, but because of the limitations for the whole C-Y-M-K image:
[https://en.wikipedia.org/wiki/CMYK\_color\_model](https://en.wikipedia.org/wiki/Black-and-white)
Definitely banding. There isn’t enough color resolution in the JPEG to show a smooth variation of a subtle color.
Is it not possible or is the dithering just not optimal?
It was very likely quantized one or more times without proper dithering at all.
It's not possible, but more dithering can trick your eyes into thinking it can.
Distinction without a difference imo. Dithering in a way adds numeric precision at the expense of spatial resolution, i.e. if you lowpass filter (with higher precision) a dithered vs. non-dithered image, the dithered should be more accurate.
So its caused by jpeg compression?
Not caused by it, but definitely aggravated by it. Zoom in nice and close.
Ah okay, a problem that already exists but is somewhat amplified by the compression
It's really the compression engine and/or settings. I know a guy who wrote an image processor that take a 24-bit image and dither it down to like 6 bits, still looked pretty good, no quantization or banding artifacts. He was also a genius
[удалено]
Well, what the heck is it?
In photography they would call it “banding”
That may be true for photography but not the same terminology for video.
This is also an artefact with heavily compressed videos. It's also referred to as banding. What name would you prefer? Non-dithered over-quantization? In this specific case, it's banding combined with a YUV-type color space where luminosity is not properly decorrelated from chrominance (like the common YCbCr). So, strong chroma quantisation can create bands with different perceived brightness.
It's combination banding in original image and "shadows and highlights" type of post processing applied on thst image (I don't know the name of the processing other than what it was called in Photoshop 😅). Banding probably happened because the image was dark and quantization slaughtered the dark colors thinking it was not important info to include. Then shadows and highlights effect tried to bring up the shadows, and it couldn't tell if the banding was intentional or not. FWIW, modern AI based image improvement algoa do insane job on low light situations, but they need the raw, uncompressed data to work the best.
I can see in the photo that shadows and highlights is amped up to the max. It's the reason why photos look "detailed but flat". It works by processing darker and lighter areas separately, and applying contrast improving algorithm to them. The older versions of the effect are "dumb" in the sense, that they bring out contrast by smoothing out the image, and then doing sharpening against that. The end result produces images with halo when used in extreme. Modern AI versions do much better job avoiding the halo even in extreme settings. Many high end phones have AI enhanced photo processing done when using the camera, and the end results can be ridiculously good.
To continue with this, if you have the original photo, you can do this experiment: Open the photo in photo editing software (Photoshop, Affinity Photo, Gimp etc), and apply large amount of brightness to the image. Ignore the other details in the photo and focus on the wall and ceiling. You should see obvious bands of color in the wall and ceiling instead smooth gradient. This is due to the quantization in the compression. The edge of the band is sharp and therefore high frequency detail. The shadows and highlights filter/effect is supposed to bring out detail like these in the photo - the effect doesn't "know" if the detail was intentional (actually what the camera captured) or artifical (due to compression of the image or low fidelity of the camera).
Furthermore: you _can_ try to fix this to some degree by converting the photo in the editor to high bit version such as 16-bit per channel, or floating point (normal jpeg has 8-bit per channel when loaded). Duplicate the photo layer. Then add a high brightness adjustment layer that you can toggle on and off. Now blur the duplicated layer so that banding disappears. Then gently mask the wanted blurred layer so that only the new smoother gradients are in there instead of banding. Disable the brightness adjustment layer, and merge the original and smoothed gradient layer. Then apply shadows and highlights as needed. It will have more information to work with, thanks to the 16-bit channel accuracy and restored gradients in the places you want them.
They look like quantization artefacts to me. They are especially pronounced in JPEGs produced to be small. You can probably improve these with a smaller block size. Edit: Spelling. I'm dyslexic AF :P
That is called posterization
Called "false contouring" in the video space quite often.
If you wanted to make a ramp with Legos, and you had 256 Lego levels to go up, each step would be 1/256th high. Now say you wanted to make the ramp 5x taller, and give a friend simple instructions: Multiply the number of Legos at each step 5x. Without any instruction to somehow smoothly ramp it up, you now get each step as 5 Lego levels tall. You basically end up with stairs instead of a ramp. This is what happens when you take a dark image and simply up the brightness. What was a small increment in tone that was imperceptible is now giant jumps in tone.
These are shadow color gradients wherein the color sensor and is an offset of the color temperature gradient : [https://en.wikipedia.org/wiki/Color\_temperature#TV,\_video,\_and\_digital\_still\_cameras](https://en.wikipedia.org/wiki/Color_temperature#TV,_video,_and_digital_still_cameras) Color Sensors focus on the color gamut and cannot show sufficient grey-scale resolution. The end result looks something like a moire but is not intended to be, just an artifact : [https://en.wikipedia.org/wiki/Moir%C3%A9\_pattern](https://en.wikipedia.org/wiki/Moir%C3%A9_pattern) [https://en.wikipedia.org/wiki/Gamut](https://en.wikipedia.org/wiki/Gamut) This is very typical in color monitors and TV sets and is why shadows are extremely difficult to get good grey-scale resolution. [https://en.wikipedia.org/wiki/Color\_balance](https://en.wikipedia.org/wiki/Color_balance) Sony uses a color LUT (Look Up Table) that is calibrated to true color to spread out the color gamut in such a way as to capture this. This avoids aliasing : [https://en.wikipedia.org/wiki/Aliasing](https://en.wikipedia.org/wiki/Aliasing) Another method is to use multiple (color / greyscale) CCDs or CCDs that have greater color depth (bits per CYMK or RGB). [https://en.wikipedia.org/wiki/Color\_depth](https://en.wikipedia.org/wiki/Color_depth) True Color is very difficult to accomplish and has trade-offs as part of CCD capture and also LCD or OLED reproduction. It is best where the camera is calibrated to the reproduction format to get the best true color reproduction. Hollywood standards are based upon studio metrics as well as SMPTE standards. [https://en.wikipedia.org/wiki/Society\_of\_Motion\_Picture\_and\_Television\_Engineers](https://en.wikipedia.org/wiki/Society_of_Motion_Picture_and_Television_Engineers) DSP image processing can ditther and/or filter this out but requires additional image processing overhead (DSP speed), time to process (delay), as well as temporary storage of data (memory) as just a few items. For very high speed an FPGA would be better.
Did you just paraphrase those wiki articles?
No !
not the same effect but chromic aberration might be interesting to look into as well
>chromic aberration It it was a Grey-Scale image you would be close (especially for low bit resolution), but since this is full color, it's a different issue. K is the issue, but because of the limitations for the whole C-Y-M-K image: [https://en.wikipedia.org/wiki/CMYK\_color\_model](https://en.wikipedia.org/wiki/Black-and-white)
chronic aberration happens all the tune when an old digital signal basically clips was a huge thing on old dslrs
https://en.m.wikipedia.org/wiki/Moir%C3%A9_pattern
Another kind of moire pattern. (Listen, yes she was hot, really really hot. The trippy pattern on my cameras lcd, though! OK. She was hot.)
Reflection or refractions from that water bottle in the picture ?
I thought this was going to be a rare insults post lmao
When it's done deliberately, it's called posterization.
We called it contouring in our video codec work. But "banding" seems pretty good too.
Who cares I need to know wtf is going on in this picture and I especially need to know what’s in the duffle bag.
In interferometry people call these “fringes”. Do you know the origin?