Mobile cameras are one of the most important issues for manufacturers. First there was the battle of the megapixels, then there was the battle of the infinite sensors, then we saw different kinds of camera modules and now the one-inch sensors prevailed. In short, the main brands want to offer a device that can take high-quality photos. For this, they use a technique called ‘Pixel Binning’. photo quality improved without us noticing.

you are definitely wondering what is this about pixel groupinghow it works and the main benefits of this technique, which our mobile phone uses to improve the overall quality of our footage.

What is pixel grouping, the secret weapon of mobile cameras?

First of all, we should start with some theory. Megapixels of a photo represents the number of pixels that make up it, and the higher this value, the greater the final result will be. Of course, without implying that a photo with more megapixels is always better, because quality depends on many other factors. However, the increase in resolution of mobile cameras meant that those millions of pixels could serve another purpose.

Here comes the binning, The process of merging adjacent pixels Now this technique of an image to create a larger pixel or superpixel is quite useful due to the high resolution of current sensors and accordingly these units (pixels) are grouped in different ways.

For example, the latest Samsung Galaxy S23 Ultra uses its 200 MP sensor to combine up to 16 adjacent pixels, thus creating a 12.5 MP photo. Another example is given on the Google Pixel, Pixel 7 and Pixel 7 Pro, which groups 50 megapixels into quads and again returns a 12.5 image.

The moment you wonder… Why waste so many megapixels if the camera can take high resolution photos? Here is where the crux of the matter begins. utility and function of pixel grouping.

The size of the pixels, which is crucial for capturing the light

The short and simple answer is: with binning we lose resolution but gain light, primarily responsible for photography. If you’re looking for something more advanced, keep reading.

We’ll get a better understanding of the science of all this by looking at an interview with Judd Heape, vice president of camera (among other things) and video products at Qualcomm. Emphasizes the answer light sensitivity and space limitations.

The sensors of our mobile cameras have many pixels, and as they get larger they improve the details of the photo as we already know. However, also hinders sensor performance in low light conditionsthus the dynamic range is compromised.

By adding more pixels, they are smaller It’s because they fit in the same space (which is limited by the technology available today) and these smaller units “can’t capture a lot of light,” explains the Qualcomm executive.

The size of the pixels is measured in micrometers (μm), so we can say that a sensor with 1μm pixels receives less light than a sensor with 1.2μm pixels. So what is going to happen? Well, camera manufacturers Various measures to combat this problem.

When space matters

One of the solutions is computational photography, which combines several images into one image, the latter contains data from the previous ones. It is not the only ‘life saver’ and it is possible to increase the size of the sensor.

We turn to Google to give an example of this practice. The Pixel 7 uses a 1/1.31-inch sensor for its main camera, so the pixels on it are larger and collect more light. Like everything in this life, this has consequences: now the problem is in space.

Google engineers had to work hard to design their latest phone because with this larger sensor find a place to accommodate the rest equipment photographic. This means less room for other important parts like the battery, which takes up most of the body. This is where the characteristic protrusion of the Google Pixel camera comes from.

How does pixel grouping work?

As we mentioned earlier, pixel grouping combines all of these together to create “superpixels”. By combining them, this superpixel gains greater sensitivity to light, which is the product of the sum of each of its components. Another factor comes into play: wavelength of light received by each pixel in different ways.

As a general rule, 25% of pixels capture red light, 25% blue light, and the remaining 50% green light. When our mobile phone uses this technique, the ISP or image signal processor (for its English abbreviation) allows four (nine or 16) contiguous sets of pixels to be input to obtain the image data. Heap, that compensate the result by lowering the resolutionbut increased sensitivity to light.

Similarly, the performance of expanding a sensor to enlarge pixels cannot be fully reproduced by pixel binning, because with this combination artifacts are created in the image. Fortunately, AI has helped in this area by minimizing these AIs.

Hundreds of megapixels are used in this way, but it is not the only function.

Although it somewhat compensates for the lack of small sensors of smartphones, they carry sensors that accumulate hundreds of megapixels. they don’t just benefit photos with more light.

And here we stop talking about photography. go to video. The latest sensors allow tasks that are not exclusive to larger tasks, such as high-definition video recording. The 8K era has arrived and Samsung has confirmed it, because the Galaxy S23 Ultra can record video in this resolution; not possible).

On the other hand, higher resolution brings us closer to telephoto lensesbecause we can take advantage of high resolutions to achieve quality digital zoom in “adequate lighting conditions”.

No doubt pixel grouping was able to accompany the growth of resolution, to get the most out of it and make up for the problem of having smaller drives. This “cheat” has been with us for several years and will likely continue for a long time.