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Comment by _Microft | Hacker News Reader

Often it is even 50% green, 25% red and 25% blue pixels. There are different patterns, though. What you get as "megapixel" number of cameras counts subpixels individually, that is a "10MP" labelled camera does not have 10 million pixels of each color but 10 million subpixels in total.

https://en.wikipedia.org/wiki/Bayer_filter

If you have a device that can output RAWs, you can look at a RAW image using the FOSS photo development program "Darktable". Choose "photosite color" as the "demosaic" filter to show the individual color channel values (and thereby the Bayer pattern of your camera).

But yes, after removing the filter, you have three times the number of pixels but you lost color information.

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Demosaicing algorithms are very good at restoring the resolution "lost" to the BFA. They can introduce some artifacts (zipper effect, "labyrinth", fringe color, to name a few) but in general, sharpness isn't lost as much as people imagine.

Nowadays they classical algorithms are being replaced by convnets that are trained on different BFA/image pairs and can get very good results -- at the cost of placing a convnet in the middle (so much higher computational cost, which can be offloaded to a GPU/AI accelerator if available).

If you want to see what a "pixel perfect" camera gives you, there are the Sigma cameras with Foveon sensors[0] or you can check the cameras that have a sensor-shift superresolution approach (some pro Olympus and Hasselblad models have this feature). Sensor-shift SR has the problem that it works best on static scenes, because it takes several images which are then later combined on a single picture, and if there's movement between the images it may introduce a few artifacts.

[0] which do full color data for every pixel, as they use silicon depth to filter wavelenth

Foveon sounds great in theory, but it doesn't deliver IMHO. It can achieve parity in terms of pixel level sharpness and color at the lower ISOs, but picture quality breaks down very quickly even at moderate ISOs.

https://tinyurl.com/yyrndzkk

https://tinyurl.com/t9nnadc

OT: why URL shortener? This is not twitter with a length restriction.

I've ran into issues with forum s/w URL sanitizers mangling URLs from DPReview. Maybe I should have just tested it. Here we go!

https://www.dpreview.com/reviews/image-comparison/fullscreen...

Thanks!

> at the cost of placing a convnet in the middle (so much higher computational cost, which can be offloaded to a GPU/AI accelerator if available)

It also makes it harder to undo the effects of the demosaicking algorithm, which may be important if you're doing things like subpixel superresolution.

Now that's something that I haven't done, but you left me wondering... Wouldn't any demosaicing algorithm complicate things at that point? If you have a few links to share I'd like to read a bit more about it.

I always wondered if this was a good ratio. I get that green usually has the strongest signal and thus better low-light performance. For bright shots, I find that preserving higher resolution in blue results in higher perceptual resolution of the final image. You can simulate something like it by using an extreme 'night mode' more-red/no-blue display mode and watching a 4k video.

Green was chosen because it's to what the human eye is most sensitive. Look at Fuji's X-trans[0], and there are also RGBW arrays that prioritize dynamic range.

All in all, the BFA is "good enough" most of the times. For the use cases where it isn't, you're either:

* Budget constrained and can't really afford not using BFA

* Able to (pay for and) use either a color wheel in front of your sensor, or go with prism + triple sensor.

* Bite the bullet and go with a "strange" color array. You'll probably need to work on the software side for demosaicing to get proper support and fix eventual artifacts.

[0] even more green! 20/36 photosites are green, 8 red 8 blue

[1] with W being white, meaning no color filter or "panchromatic cell". In theory this helps on dim light conditions.

The requirements for sensors is different than displays. I guess I was asking why the non-rectangular displays didn't have more blue than green or red as that would improve perceived resolution more.

Good info, but your citations are a bit jumbled up Doctor.

Yeah, the [1] was about RGBW

> I always wondered if this was a good ratio. I get that green usually has the strongest signal and thus better low-light performance.

More importantly, green is close to what your eyes perceive as luminance. This is important because you can perceive a lot more luma detail than chroma detail. This is why things like 4:2:2 sampling work.

If you read Bayer's original patent, he proposed using Y Cr Cb (luminance, colour part red, colour part blue) instead of GBR filters[0]. This would people optimal from a computer science perspective. Sadly it doesn't work physically. Sensing negative-blue and negative-red can't really be done with a simple filter.

[0] https://patents.google.com/patent/US3971065

Since the "pixels" are either formed at every intersection of 4 photosites (overlapping each other) or by interpolating data for each color to include the "missing" photosites (which is effectively the same), the megapixel count should fairly accurately represent both the number of photosites and the number of pixels in the output image.

I'm not exactly sure how the edge pixels are treated, but the difference in number between pixels and photosites should be on the order of a few thousand at most.

> I'm not exactly sure how the edge pixels are treated ...

It is quite common to have more than the "nominal" number of pixels in a sensor array. So there are extra pixels for the edges.

Ah yes. I had forgotten about this. I believe there are also extra pixels at the edge of some sensors that are unexposed, and just used for calibration purposes.

Are you saying that one photosite might be included in more than one pixel and therefore the overall pixel count is roughly equal to the number of photosites?

I'm saying that each photosite definitely is included in more than one output pixel, and I'm also saying that the number of output pixels should be about the same as the number of photosites.

This is obviously capturing less information than if you had a completely separate set of photosites for each pixel, but the megapixel count of cameras is nevertheless accurate.

Modern cameras sometimes come with a "pixel shift" function, which uses the image stabilization system to take 4 images each shifted one photosite from the others to construct an image where each pixel contains the information of 4 independent photosites with no sharing between the pixels.

The resolution of the final image is the same as a normal image, but the result is much clearer, and far less likely to suffer from blue/red moire.

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