To filling my appetite on camera things hunger I've came across to Sigma website and found this 3 layer sensor stuff.

Can anyone really explain this based on their experience or research about this?

Does anybody has a hands on this sigma SD15 or sigma SD1 DSLR since I was only directed and influenced to the big brand in this industry?

  • \$\begingroup\$ thanks guys, it's flooded with such good opinion, views and info, all answer is good and satisfying... \$\endgroup\$ Commented Jan 21, 2011 at 0:48

3 Answers 3


The Bayer sensor used by the vast majority of cameras is basically a two-by-two grid of sensors with 1 blue, 1 red, and 2 green sensors known as a Bayer filter named after the Kodak Labs scientist that came up with it. The data from such a sensor then must go through a demosaicing process that converts the 4 data points into a pixel giving the result of the 3 color merge. The reason for 2 green sites is that the human eye is reported to be more sensitive to green and so the color is emphasized in the system.

The Foveon model, which totally fascinates me, is an approach to follow a more traditional film style. In this context, the idea is that the three primary bands of light operate at different wavelengths and so penetrate the sensor material to different depths, the premise of color film. In this case, blue is the least penetrating and red the most, so by stacking the layers, they can detect at each photo site the level of each of the primary colors. The technology, as a result, eliminates the moire pattern than can result from the demosaicing algorithms associated with a Bayer filter and give a more accurate result.

I'm really excited about the Foveon technology and I'm looking forward to seeing where Sigma takes it. They've finally produced and APS-C camera with this sensor, so when the reviews and samples finally hit, I'm going to be looking at them closely. Having said that, I think the camera makers have done a very good job with the Bayer model, it's a proven and well-understood means of image capture and that can be seen from the often stunning results. If the Foveon exceeds that, we're in photography nirvana. :)

Anyways, I linked some relevant Wiki articles on the two which I think will really help you see the differences.

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    \$\begingroup\$ In the real world, foveon photos don't really look that much different than bayer photos. Color saturation is similar, perhaps a tad better blues. One of the primary differences is the lack of color moire in Foveon, and another is the relatively low image pixel count (14mp is the largest Foveon, while we are pushing 24mp and beyond with bayer FF, 80mp with MF.) It should be noted that monochrome moire is NOT eliminated on foveon (only color moire)! Any device that has a limited resolution will encounter moire when imaging frequencies beyond its nyquist limit, including a Foveon. \$\endgroup\$
    – jrista
    Commented Jan 20, 2011 at 3:15
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    \$\begingroup\$ @jrista-- I couldn't disagree with you more about the look and feel of Foveon images. I have a dp2 and a nikon d300, and have produced 13x19 prints with both cameras (using full-chip images from both). First, no one can tell that they are taken at different resolutions, and second, people can definitely tell that they are different cameras. The saturations are different, the detail resolution is different-- the feel is just different. Some people prefer the d300, others the dp2-- my walls have become a bit of a Rorschach test for sensor style. \$\endgroup\$
    – mmr
    Commented Jan 20, 2011 at 3:23
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    \$\begingroup\$ @jrista - I don't agree. First, I don't think 14mp is "low" on an APS-C sensor, heck Nikon is pushing a 12mp full frame camera and it's getting stunning reviews. Evidence, yet again, that the megapixel count isn't the whole story. Second, the Foveon technology is in infancy compared to the Bayer model and is producing at least as good a result and, in some cases, better. That's darn exciting. Let's not get wedded to a technology here, Sigma may yet produce something better than Kodak has and that's a good thing. \$\endgroup\$
    – Joanne C
    Commented Jan 20, 2011 at 4:10
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    \$\begingroup\$ I was a BIG Foveon fanatic for a long time before I actually bought a camera. I really like the merits of the technology, and I think it has potential...especially if Canon and Nikon can license it. My worry is that it is in Sigma's hands. It has taken them years to announce the 15.3mp APS-C, and the DP2 has barely been able to take off. Sigma doesn't execute well, even if the technology is superb, and that could very well spell the doom of the technology. I would love to see them license the technology, and get a Juggernaut like Canon to release a 21mp Foveon. I'd buy one in a heartbeat. \$\endgroup\$
    – jrista
    Commented Jan 20, 2011 at 6:46
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    \$\begingroup\$ @jrista Are you talking about 14 million photosites, or 14 million total colour-sensing elements? A Foveon sensor with 14 million photosites would do a hell of a lot better than a Bayer with 14 million photosites, probably better than a 24MP Bayer, and hence is not low res by today's standards. However such a camera (the SD1) has not been released yet. A Foveon sensor with 14 million colour sensels but only 4.5 million photosites (like the SD15) will do worse than a 14mp Bayer. \$\endgroup\$
    – Matt Grum
    Commented Jan 20, 2011 at 11:47

I have been shooting Sigma DSLR's for a number of years, since the SD-9. I got into the system when I was moving out of film SLRs into digital and did a lot of research before I made the leap. I too came across the the Foveon chip and the design of it struck me as much more sound than the Bayer design on a conceptual level; plus I really liked the images I saw coming from the camera.

The way to think about the difference here is that a traditional Bayer sensor it really taking three separate photos - one green, one red, one blue. For a 14MP Bayer sensor the green photo is has 7 million pixels, while the red and blue images have 3.5 million pixels of data. None of that data spatially overlaps; that is to say if an object were just one pixel high as captured by the sensor it could vanish in any one of the images depending on color. At any given spatial location 2/3 of the color data is discarded. So while the output you get from a 14MP camera might have 14 million pixels in it, it's essentially a re-sampled and upsized version of the image with greatest detail - the 7 MP green image.

On the foveon side, there is no-where a color in the image can "hide" because at any given sensing location, the full spectrum of light is captured by the three layers of sensors and so there is not as great a need from input from neighbors to resolve what the sensor saw.

The end effect is that Foveon sensors will not be fooled into thinking fine detail is really some kind of color (color moire), and the level of detail captured is constant because no fine detail is accidentally discarded. The bayer sensor discarding 2/3 of the light at any point can sometimes drop fine detail that the Foveon chip will resolve - again it depends on scene color.

Because the level of detail in a Bayer sensor is variable, it can be very hard to compare with the Foveon chip as far as detail captured - but a rough rule of thumb is that a Foveon image will capture around the same level of detail as a Bayer camera with 2/3 of the Foveon MP rating (or sensor count). So for example the upcoming SD1 has 46 million photosites (sensors) which means you can expect similar levels of detail to a 30MP bayer image. But this is again an image without color moire, without an AA filter in front of the filter (when you don't worry about color moire you don't need an AA filter).

You can see some interesting examples comparing the original Canon 5D to the Sigma SD-14 here:


Especially note what happens shooting color targets to get a sense of how detail can vary.

So all the technical stuff aside, what does the sensor do well with? Because it's capturing the full spectrum at every pixel and the same level of resolution regardless of color, I think it captures subtle tonal changes really well. That means really nice skies, or anything else with gradual changes in color or tone. As such they produce really nice images for B&W conversion also, because of the very smooth transitions between tones.

http://www.pbase.com/kgelner/image/90304998 alt text

http://www.flickr.com/photos/kigiphoto/5308324073/in/set-72157625711613108/ alt text

http://www.pbase.com/kgelner/image/108588990 alt text

(full size versions of each of those images can be found at the links).

Where the sensor has had issues, is with higher ISO - the current cameras can do ISO 3200 when asked:

http://www.flickr.com/photos/kigiphoto/4684772878/in/set-72157624236424558/ alt text

but really 800 is more of a realistic limit to most shooting (unless you are shooting for B&W and then those images can hold up really well because of the nature of the noise).

The Sigma cameras are not really oriented to people starting out with photography, because they don't offer a lot of assist modes or things of that nature... so be aware of that if you are thinking of getting into the system. The easiest way to get into trying out the sensor for yourself is the Sigma DP-1 or DP-2, earlier versions of the cameras can be slower to use but all of them will give you a good taste for the detail and color the images capture.

Note that I am obviously not an unbiased source, since I have enjoyed using the cameras for a long time. So the other thing to do even before getting a camera is to go exploring images from the sensor in more detail. I provides some above and you can explore my sites as I generally only shoot Sigma cameras, but you can find a ton of example images from all of the various cameras Sigma has produced here (also with full size images to be found):


Also you can find a ton of great info at Carl Rytterfalk's blog:


Somewhere in there he has sample RAW packs you can download, and various things talking about Sigma cameras, lenses, and the Foveon sensor. He's a great photographer and very enthusiastic as you'll see if you watch any of his videos.

EDIT: Carl has just written a lengthy post of "Why I use Sigma", which directly applies to this question:


The summary of his reasons are:

  1. Nuances (in color)
  2. Density
  3. Micro contrast
  4. True sharpness
  5. Dynamic Range

Which he goes into in more detail at the link, along with some more images.

One side note I forgot to mention, that is not really directly about the sensor, but is about the Sigma specific DSLR's that house the Foveon chip - you can easily use them for IR work as well just by removing the dust protector on the camera (built to be user removable and reinstalls without any tools).

  • \$\begingroup\$ erhh, really nice and comprehensive! congrats... \$\endgroup\$ Commented Jan 21, 2011 at 0:45
  • \$\begingroup\$ One thing I will say about Foveon...the blues really do stand out! \$\endgroup\$
    – jrista
    Commented Jan 21, 2011 at 1:23
  • \$\begingroup\$ I should note that none of those images had any post-processing applied, they are pretty much straight out of the RAW converter with minimal or no adjustment. \$\endgroup\$ Commented Jan 21, 2011 at 4:55

I have lots of praise for Sigma for trying something different and innovative, and on paper the Foveon sensor is a very good idea. However I disagree with the way Sigma refer to their current model with 4.6 million photosites (each of which is sensitive to colour as well as intensity) as have a 14 megapixel sensor!

Multiplying the number of photosites by three to get the Bayer equivalent would be ok if the colour channels were uncorrelated with each other. However in real scenes the colour channels vary from mildly correlated to strongly correlated. Take this following example:

You have a 5MP Foveon sensor and a 15MP Bayer sensor. Each sensor has 5 million red pixels 5 million green pixels and 5 million blue pixels. You are photographing a grey cat sat on a big block of grey concrete. As the light coming from the scene is all grey, the red green and blue pixels in each sensor all receive the same amount of light. However in the Foveon sensor you end up with three identical readings on top of each other which is not very useful, giving only 5 million unique data values. In the Bayer sensor they are displaced laterally giving a potential 15 million unique values. The Bayer image would not even need demosiacing, so would contain a lot more detail.

This is a very contrived example, however correlated colour channels do occur quite often, and this is why Bayer interpolations works. When photographing a yellow object the red reading gives you information about what the green reading would be even though unlike the Foveon there is no green pixel there.

In real world testing due to correlation the resolution is equivalent to just over 2x the Bayer, not the 3x Sigma claim. This means the current flagship Foveon model with 4.6 million photosites is roughly equivalent to a 10 megapixel Bayer (though they will still have slightly different qualities, lack of colour Moire in the Foveon for example). This leaves Foveon lagging a bit behind the 24MP 35mm DSLRs. The current Foveon also struggles in low light as light has to penetrate two layers above in order reach the final layer.

The Future:

So based on that my current advice would be to go with a Bayer camera, however it will be interesting to see what the future holds. After a long hiatus Sigma have announced the SD1 with a 15.4 million photosites. There's no release date yet but if they can pull this off in a decent body it would give the 24MP Nikon D3x a serious run for it's money!

On the other side of the coin Bayer resolutions go up at a steady pace and are backed by simply economics (more people are making Bayers in larger numbers). As sensor resolution increases, whithout corresponding improvements to lens sharpness, Moire and other Bayer artifacts become much less of a problem. Eventually a Bayer sensor with high enough megapixel count will give you the same effect as the Foveon, but with the pixels side by side not on top of each other.

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    \$\begingroup\$ In the Bayer sensor you have 7.5 million green photosites, and 3.75 million red and green photosites. Your example is correct in that a totally neutral subject will give the maximum amount of data, although even in that example because there is no overlap between red/green/blue sensors you would potentially see some color show up in the demosiacing when there was difference in luminance between the cat and the background. But in reality how many things are grey, and how many things show some degree of color? You are also wrong about the SD1, it has 45 million photosites (distinct sensors). \$\endgroup\$ Commented Jan 20, 2011 at 19:11
  • \$\begingroup\$ Kendall would be correct here. With a 15mp Bayer, you have 7.5 million green, and 3.75 each red and blue, rather than an even number of red, green, and blue. That makes sense though, as our eyesight is more sensitive to green as well. I wouldn't necessarily say that Bayer gathering twice as much green info as red/blue info is a detriment in any way. @Kendall: As for the SD1, Matt is correct in that it has 15.4 million PHOTOSITES, or individual photosensitive locations on the sensor. Each PHOTOSITE is capable of sensing three different colors, and therefor has 46.2 million SENSELS. \$\endgroup\$
    – jrista
    Commented Jan 20, 2011 at 22:37
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    \$\begingroup\$ I think we've covered megapixels vs. sensels adequately in the other question. With regards to my cat example, I accept that it is a very rare occurrence to have an entirely monotone scene (a point I accept in the answer) but I also go on to say that in most scenes you may not have three colour channels in complete agreement but you are likely to have colour channels that highly correlate with each other. You could have a very garish scene with bright cyan, shocking pink and luminous yellow, and still have two identical readings per Foveon photosite! \$\endgroup\$
    – Matt Grum
    Commented Jan 20, 2011 at 23:58
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    \$\begingroup\$ It's not fair to say the Bater sensor demosaicing is effectively upsampling the colour channels, what's going on with algorithms like the adaptive homogeneity-directed interpolation is far more sophisticated and exploits strong statistical correlations between colour channels that occur in real images to do much better than just filling in the gaps. \$\endgroup\$
    – Matt Grum
    Commented Jan 21, 2011 at 23:45
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    \$\begingroup\$ If you have large areas of different intensities of pure magenta then you will indeed find the red and blue sensels at each pixel are recording the same values as magenta is the mixture of equal parts red and blue. Yes if you have a thread one pixel wide the Bayer wont be able to see it, but if you have three times the number of pixels in a Bayer sensor it should be able to cover the thread with more than one pixel. Anyway one pixel threads sharply resolved by the lens are just as rare as grey cats... \$\endgroup\$
    – Matt Grum
    Commented Jan 21, 2011 at 23:49

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