We click lot of photos daily.But we always struggle to click a perfect photo when in low light.So we are always looking for a solution to click the best photo like using flash but we end up clicking blurry photos.So that is where pixel binning comes into play.So let's have a look at how we can use this technique to click better low light photos.
To understand Pixel Binning we will have to first understand the camera sensor
Understanding Camera Sensor
Unlike what we understand a pixel to be when we look at an image, the “pixels” on a sensor has a red, green or blue filter on top of it, allowing only the light that passes through these filters to be registered. These filtered pixels are laid out in alternate patterns, with green pixels being two times that of the red and blue pixels in any given horizontal or vertical line. The adjacent red green and blue pixels are combined into a single RGB pixel using a process called ‘demosaicing.’ The binning process takes place during the demosaicing stage, even before the JPG is generated.
What is Pixel Binning?
Pixel Binning is a image signalling processor based technique.It takes place at the time of demosaicing process where it combines information from four pixels into one.For example that a pixel binning take 2x2 grid and combines them into one.The information captured by each individual pixel is now combined into one Super Pixel.The unfortunate result of that is the resolution of the resulting image is 1/4th resolution of the sensor.The combination of data collected by 4 adjacent pixels into one “super pixel” is called pixel binning
Benefits of Pixel Binning
Pixel Binning solves one big problem of Low Light Photography. By combining raw data from four pixels into one, the effective output is a higher amount of light captured, while reducing the noise generated. Without actually artificially boosting the “signal” (amount of light perceived by the sensor, usually done by increasing the ISO), the resulting image is much brighter.Pixel binning is definitely a very smart way of getting the most out of a sensor, but there are limitations even to this implementation.
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