The “pixel binning” must have probably appeared in some launch text for the phone you’re looking for. The reason for this is that this technology is currently widely used by cell phone camera systems. Usually, not to go into details, many explain the technology as a way of optimizing image capture or mention only one of its purposes, nothing that really explains what “pixel binning” actually is, but this time you will understand its operation.
In order to understand what “pixel binning” is, it is necessary to define what a pixel is in the context of photography. A pixel can also be called a photosite, which is basically the physical element present in a camera sensor. In turn, the sensors of digital cameras are made to capture light and produce images.
Pixel is usually measured in micron (1 millionth of a meter) and in cell phones. In the case of Samsung’s new sensor, the ISOCELL HP3, we have pixels with only 0.56 μm. However, a smaller pixel may not always be better depending on what you want to do.
The influence of sensor pixel size in photo cameras
The larger the pixel, the easier it is for the camera’s lens and sensor to work in capturing scenes in low-light environments. However, in the case of cell phones, the sensors need to be small to fit among several other components of the device.
To decrease the size of the sensor to make it fit on cell phones, you need to decrease the size of each pixel, unless you lower the resolution of the photos. One way to get around this problem is to use a greater number of pixels, that is, to use a sensor with a higher resolution. However, this will make it necessary to increase the size of the sensor or decrease the volume of each pixel.
When using a sensor with very small pixels, there may be problems with light reception. That’s where the “pixel binning” technique comes in.
What is “pixel binning”?
Pixel binning is the process of grouping data from four pixels into one. With this, it is possible to use sensors with 0.9 micron pixels and produce results equivalent to a camera with 1.8 micron pixels, which has a better performance in night photographs.
Imagine a camera sensor as a house garden and pixels/photosites as buckets collecting water (light) from rain (sun or artificial light source). You can place several small buckets in the yard or several large buckets. Pixel binning is a technique that is equivalent to combining all the small buckets into a gigantic one when necessary (when taking pictures in dark places).
The resolution drop when using pixel binning
While it appears to be flawless, the pixel binning technique has a weak point. When using pixel clustering, the resolution is divided by four (or more). That is, when using this procedure, the result will be that a 48MP camera will produce 12MP photos, while a 64MP sensor will produce 16MP photos.
Pixel binning is possible thanks to the use of a quad-bayer filter on the camera’s sensor. It is present in all digital cameras and causes the image to be captured in red, green and blue colors. The most commonly found pattern in sensors is 50% green filters, 25% red filters and 25% blue filters.
According to cambridgeincolour, this array of sensors tries to mimic the way the human eye sees in real life. After capturing the images by the sensor’s pixels and filters, the camera interpolates what was recorded and produces a colored image, close to what we see in real life.
The quad-bayer filter groups the red, green and blue colors into clusters (squares) with four units and then uses matrix conversion processing based on the software developed to store the pixels. The way the clusters are organized gives information about the light during the conversion process. See the image below to better understand the process.
By using pixel-binning and the quad-bayer filter, it is possible to obtain good photo quality during the day and at night. Usually night shots are brighter than normal (real) and there is not as much noise in the image.
Color accuracy may suffer from pixel binning
In addition to the drop in resolution, the practice of pixel binning ends up decreasing the color accuracy. To avoid this, companies have been looking to improve mosaic algorithms to fill in places where the captured image’s color has been degraded.
A good photo through a cell phone goes beyond pixel binning
The pixel binning technique is excellent for most cases, where the objective is to have convenience and still obtain a good quality in the photographs. But she is not the only one responsible for the beautiful photos we see today. There is still the use of different lenses, HDR technology, computational processing and adjustments made through artificial intelligence, which is developed in different ways by cell phone manufacturers.