Mathematically Evaluating mpv's Upscaling Algorithms
This work aims to mathematically quantify image quality and performance of different real-time upscaling algorithms.
Like its name implies, upscaling is simply the act of increasing the scale of something. In the digital signal processing case, taking discrete information in a given scale and calculating points between the existing samples. The easiest and most classic way of doing this is through simple linear interpolation, if you want to find a value between two points you can simply draw a line between them and linearly find any value in this line. If you wanted to find the value that's placed exactly in the middle of those 2 discrete points, you could simply do an arithmetic mean with their values to find your answer.
Linear interpolation can be done in a plane, through both axis, creating what we call "bilinear" interpolation. Bilinear interpolation is the simplest interpolation algorithm, easiest to calculate and unironically the most widespread one due to the fact that it's extremely simple to implement.
