Interpolation algorithms when downscaling

Question

Im trying to understand downscaling. I can see how interpolation algorithms such as bicubic and nearest neighbour can be used when when upscaling, to \"fill in the blanks\"

Answer 1

If you use a windowed sinc filter, such as lanczos, it actually filters out high frequency details that cannot be represented at the lower resolution. An averaging filter doesn't do this, causing artifacts. A sinc filter also produces a sharper image, and works for both upscaling and downscaling.

If you were to upscale an image with sinc, then downscale it back to the original size, you would get almost the exact same image back, whereas if you just averaged the pixels when downsizing, you would end up with something slightly blurrier than the original. If you used a fourier transform to resize, which the windowed sinc tries to approximate, you would get the exact original image back, apart from rounding errors.

Some people don't like the slight ringing around sharp edges that come from using a sinc filter though. I'd suggest averaging for downscaling vector graphics, and sinc for downscaling photos.