Convolution resampling and other libraries about vips-bench HOT 4 OPEN

libvips also has adaptive convolution resample as well as fixed window interpolators -- it has two completely different paths for the two systems.

I think that comment went in in 2015 after we swapped some mails. You said that pillow-simd always used adaptive convolution, so I wanted to avoid penalising pillow-simd, and picked nearest.

Do you think Image.BILINEAR would be fairer?

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libvips also has adaptive convolution resample as well as fixed window interpolators -- it has two completely different paths for the two systems.

Could you disclose why they are separated? If you have both, the good solution is to choose one of them internally based on scale factor, but do not let a user spoil the data. In my opinion, fixed window interpolation shouldn't be used for the shrinking at all, because even with scale factor from 0.5 to 1 the window width will be > 2.

Do you think Image.BILINEAR would be fairer?

Yes. To be honest, I also think that VIPS's method should be changed to adaptive convolution and OpenCV's method to INTER_AREA.

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It's just historical: vips used to just have fixed-window interpolators, and the adaptive kernel stuff was added in 8.3 (I think).

I've swapped everything to adaptive, I think.

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I don't think that reduce is actually adaptive:

Pillow:

im = im.resize(0.1, kernel='linear')

im = im.reduce(1.0 / 0.1, 1.0 / 0.1, kernel='linear')

im = im.similarity(scale = 0.1, interpolate = pyvips.Interpolate.new("bilinear"))

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