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The past year has seen the term “pixel binning” regularly pop up when talking about smartphone photography. The term doesn’t exactly brings up excitement, but it’s a feature powering loads of phones today.
So what is pixel binning then?
To understand pixel binning, we have to understand what a pixel actually is in this context.In theory, pixels on a camera sensor are photosensitive diodes that are selectively sensitive to red, green or blue frequencies, hence breaking down incident light to capture more color data. Typically, pixels are arranged in grids, where image processors take data from and combine to create photographs that you see. The quality of photographs often depend on how large a pixel is, and how much data is captured by them, hence creating the best balance between brightness and colors.
Pixel size is usually measured in microns (a millionth of a meter), with anything at or below one micron considered small. The iPhone XS Max, Google Pixel 3, and Galaxy S10 cameras all offer large 1.4 micron pixels.
Needless to say, you always want your pixels to be large, as a larger pixel can simply capture more light than a smaller pixel. The ability to capture more light means better performance in the night. But smartphone camera sensors have to be small in order to fit into today’s svelte frames — unless you don’t mind a camera bump.
The small smartphone sensor size means the pixels also have to be small, unless you simply use fewer pixels (i.e. a lower resolution sensor). The other approach is to use more pixels (i.e. a higher resolution sensor) but you’ll either have to increase the size of the sensor and deal with a bump or shrink the pixels even more. Shrinking the pixels down even more will have an adverse effect on low-light capabilities. But that’s where pixel binning can make a difference.
To sum it up in one sentence, pixel-binning is a process that sees data from four pixels combined into one. So a camera sensor with tiny 0.9 micron pixels will produce results equivalent to 1.8 micron pixels when taking a pixel-binned shot.
Think of the camera sensor as a yard and the pixels/photo sites as buckets collecting rain in the yard. You can either place loads of small buckets in the yard, or several big buckets instead. But pixel-binning is essentially the equivalent of combining all the small buckets into one gigantic bucket when needed.
The biggest downside of this technique is that your resolution is effectively divided by four when taking a pixel-binned shot. So that means a binned shot on a 48MP camera is actually 12MP, while a binned shot on a 16MP camera is only four megapixels.
Pixel binning is generally made possible thanks to the use of a quad bayer filter on camera sensors. A bayer filter is a color filter used in all digital camera sensors, sitting atop the pixels/photo sites and capturing an image with red, green and blue colors.
Your standard bayer filter is made up of 50 percent green filters, 25 percent red filters, and 25 percent blue filters. According to photography resource Cambridge in Color, this arrangement is meant to imitate the human eye, which is sensitive to green light. Once this image is captured, it’s interpolated and processed to produce a final, full color image.
Pixel binning is definitely a very smart way of getting the most out of a sensor, but there are limitations even to this implementation.
PIXEL BINNING LIMITATION 1:
Because the resolution is reduced by 1/4th, the image sensor used needs to be of a high enough megapixel count. Huawei got this very right with the P20 Pro, where they used a 40-megapixel sensor to generate a 10-megapixel image which set a benchmark for the entire industry. But for sensors with a lower resolution like the LG G7+ ThinQ which has a 16-megapixel sensor, the resulting image when binned is just 4 megapixels, resulting in a lower level of details captured. However, the images are brighter, making “more visible to the eye”. While you do get to see more "illumination" in the photo, the detail from objects that have been shot is significantly lower due to the reduced resolution.
PIXEL BINNING LIMITATION 2:
The other downside to the use of pixel binning is the lack of RAW output. Since RAW output is the encapsulation of the raw sensor data, a pixel-binned version cannot exist. If the JPG algorithms being used by the smartphone manufacturer are aggressive in favour of reduced file size, the compression would result in even more detail degradation, to the point where photos might look like oil paintings. If the manufacturer allows it, you can either record a RAW image file (without pixel binning) or a pixel-binned JPG.
