Using a laser to blast away a Bayer filter array from a CCD

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.

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

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.

There is not single one on the market and the only one worth mentioning is from 1995 with 0.38MP per sensor.

https://en.wikipedia.org/wiki/Minolta_RD-175

Extra fun fact: Bayer filters were developed by Bryce Bayer at Eastman Kodak, who first researched digital sensors.

Despite such a head start, Kodak went on to completely fail the analog-to-digital camera transition. A prime example of the Disruption Dilemma.

YUV/YCbCr 420 means that there is one set of chroma samples (Cb+Cr) for each 2x2 block of luma samples (pixels).

Often, the chroma samples fall on pixels in even rows and on even lines. So pixels in odd rows or on odd lines, have to borrow (interpolate) their chroma values from neighbouring pixels.

> the monochrome version is typically 20% - 30% more expensive than the color version, which is counterintuitive...

The market for monochrome sensors is very tiny compared to the rest of the commercial products. Every phone now has 2 or more cameras on it, and there are billions of those.

Any changes to the manufacturing steps means more setup and effort. Different test procedures, quality control, documentation, etc.. That is all overhead, to be absorbed by a relatively small production volume.

I'm surprised it is only a 30% premium, I'd have expected higher actually.

> because you can prioritize gathering brightness signal over color signal, so you get more detailed photo

I wonder how long until phone cameras are purely monochrome, and apply ML to add the "correct" color in post-processing.

Actually, wasn't there some phone a few years ago with one high-res black-and-white sensor and one low-res color sensor, and it combined them through some tricky to produce a sharp color image?