In the previous blog, we saw different methods by which color image can be obtained from an image sensor. Out of these methods, the Bayer filter is most widely used today and in this blog, we will discuss it in detail.
To form a color image, we need to collect information at RGB wavelengths for all the pixels or sensors. But this process is expensive both in terms of time and money.
So in 1976, Bayer thought of an alternative. Instead of capturing all RGB information at each pixel, Bayer thought of capturing one out of RGB for each pixel. Now, each pixel will contain either R, G or B. To be able to form a color image, he decided 50% pixels be Green and rest equally to Red and Blue (to mimic human eye) and these are arranged in a pattern as shown below
He would then use interpolation or color demosaicing algorithm to find the missing information for example pixel capturing Red will need Green and Blue and so on. We will study in more detail about interpolation algorithms in next blog.
The overall procedure from Bayer to RGB color image can be summarized as
So, with Bayer filter, we are only storing one color information(either R, G or B) at each pixel which reduces the computation time and cost while maintaining the image quality. That’s why it is used widely.
Hope you understand the Bayer filter, why it is used and how the color image is obtained from the Bayer image.Hope you enjoy reading.
If you have any doubt/suggestion please feel free to ask and I will do my best to help or improve myself. Good-bye until next time.