...and indeed, the link in the other comment here https://news.ycombinator.com/item?id=17597939 explains it best: "This requires processing to convert the 'Quad Bayer' data into an approximation of what a 48MP Bayer sensor would have captured."
Each of the R-G-B sensitive photoreceptors in single-chip sensors are arranged using a Bayer filter pattern which looks like a mosaic. The filter pattern is 50% green, 25% red and 25% blue.
The "pixels" of the final image needs to be calculated from this pattern (called de-mosaicing or de-bayering). There is not a 1-to-1 correlation between RGB pixels in the sensor and RBG pixels in the final image, and the final image size may depend on different algorithms to remove artefacts caused by the filter.
I used an earlier Foveon the "quattro dp2" (APS-C, 45mm focal length equivalent), they have different characteristics from Bayer cameras. They get high marks from landscape photographers where the shooting uses the lowest ISO setting and fast operation is not required.
They have less dynamic range, however given the amount of investment into Bayer tech vs. Sigma's spending on Foveon, that might just be due to more advanced engineering of Bayer and not something inherent in the Foveon design.
The DP Review forum for Sigma cameras: https://www.dpreview.com/forums/1027
The "Merrill" sensors (named in honor of Dick Merrill, an engineer and photographer that did a lot of work on that generation of sensor) are 1:1:1 as you mention - each of the photosites pick up all 3 colors.
The "quattro" sensors have the top, blue-sensitive, layer at the full resolution, with this layer also capturing the luminance of the image (which makes for stunning black and white, even at ISO 3200). The lower 2 layers are at a lower resolution than the blue layer.
I did get very high quality 13x19 inch prints from the quattro ; but have never owned a camera that used the previous Merrill sensor, so I can't give a direct comparison from my own experience.
[1]: https://en.wikipedia.org/wiki/Foveon_X3_sensor
[2]: e.g. Fuji's X-trans, https://en.wikipedia.org/wiki/Fujifilm_X-Trans_sensor
[3]: https://www.bhphotovideo.com/explora/photography/tips-and-so...
Instead of just the same RGB pixel filters all over, mix in pixel filters which are darker (passes less light). Then use this info during de-Bayering to construct a HDR image directly.
Maybe a very silly idea, but would have been fun to play around with (maybe I'll write a simulator).
HDR is as simple as taking multiple exposures and different EV values. It was often down with sheet film cameras, the two negatives being used to create the final print.
And I doubt most people really need effective 48 MP mobile cameras. They could very well do with more dynamic range though.
They used micro lenses, which had some overall sensitivity and angled aliasing challenges, but the results were impressive for the time.
Since they listed the image element size as .8 micrometers, we can do simple math to see that they're quoting the biggest possible number. There are 48M small color cells, 12M big color cells, and 3M RGGB cells. So your luma data is amazing, and your chroma data is garbage.
This obviously assumes the sensor is fabricated without a Bayer filter.
- The Nikon D1x had about 6 million rectangular photon wells on the sensor. But by doubling them up in processing (to make square final pixels), Nikon claimed about 10 million effective pixels. Needless to say, when actual 10 MP sensors debuted (sensors with 10 million photon wells), everyone stopped using their D1x's.
- Fuji used a diagonal array of photon wells on the sensor in the Finepix S2 camera, and claimed that through interpolation, this provided 12 megapixels of effective resolution. Again, once actual 12 MP sensors debuted, the difference was obvious.
- Sigma used a Foveon sensor with about 3.5 million photon wells in their S9, but because each photon well independently sensed red, green, and blue wavelengths (at different depths in the well), Sigma claimed a "3x factor" that allowed their software to produce about 10 million effective pixels in the final image. How'd that go... you guessed it, the vast majority of people preferred sensors with 10 million photon wells.
In short, there are plenty of examples of using computer processing to produce a high number of "effective" pixels, but that doesn't mean the final image will meet user expectations. I predict a pretty obvious difference between an "effective" 48 MP image from this stacked sensor array, vs. an image from, say, a Nikon D850.
That said, even though it's a compromise... compromises sometimes make sense. A D850 is very heavy and very expensive.
EDIT to add: The D1x was good enough to convince National Geographic to use that camera for their first all-digital photo story. I went to the live event at Nat Geo headquarters where they had some 20x30 prints on display, and they did look amazing. I believe they took the D1x 10MP image and sized it up using Genuine Fractals.
http://www.robgalbraith.com/multi_pageff3f.html?cid=7-6450-6...