Hi,

Roberto Winter wrote:

I guess the whole point is that Lanczos is not really the 'best' algorithm for reducing images (as suggested in the scalings dialogs whe selecting the algorithm). Now, isn't there a problem?...

Yes, there is - and the problem isn't just that Lanczos is not the "best" algorithm for reducing images, *interpolation* of any kind is inapproprite when reducing images.

Interpolation allows us to estimate pixel values that "fall in the cracks" between sample points in the original image - which is a great help when enlarging; however, when reducing, the "correct" approach is to perform a weighted average of all source pixels that are "covered" by the destination pixel.

Cubic interpolation gives a tolerable approximation of the "correct" method; Lanczos Sinc, it would appear, doesn't.

Another point worth considering is that, while for band-limited photographic images Lanczos performs very well, for artifically sharp images it can result in almost JPEG-like ringing artifacts.

So while it produces the "best" results for many images - and is certainly the method that causes the least amount of blurring when rotating an image by a few degrees, it's not *always* the best choice.

All the best, --
Alastair M. Robinson