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Image resizing filters
Bicubic and Bilinear downscaling
Lanczos upscaling quality
Bicubic upscaling quality
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homm 2014-11-30 03:09:39 +03:00
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@ -4,14 +4,36 @@ Pillow 2.7
Image resizing filters
----------------------
Bicubic and Bilinear downscalling
Image resizing methods :py:meth:`~PIL.Image.Image.resize` and
:py:meth:`~PIL.Image.Image.thumbnail` takes `resample` argument, which tells
what filter should be used for resampling. Possible values are:
:py:attr:`PIL.Image.NEAREST`, :py:attr:`PIL.Image.BILINEAR`,
:py:attr:`PIL.Image.BICUBIC` and :py:attr:`PIL.Image.ANTIALIAS`.
Almost all of them was changed in this version.
Bicubic and Bilinear downscaling
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
From very begining :py:attr:`~PIL.Image.BILINEAR` and
:py:attr:`~PIL.Image.BICUBIC` filters was based on afine transformations
and uses fixed number of pixels from source image for every destination pixel
(that was 2x2 pixels for :py:attr:`~PIL.Image.BILINEAR` and 4x4 for
:py:attr:`~PIL.Image.BICUBIC`). This gave an unsatisfied result for downscaling.
At the same time high quality convolutions-based algorithm with flexeible kernel
was used for :py:attr:`~PIL.Image.ANTIALIAS` filter).
Starting from 2.7 high quality convolutions-based algorithm is used for all of
these three filters.
If you have previously used any tricks to maintain quality when downscaling with
:py:attr:`~PIL.Image.BILINEAR` and :py:attr:`~PIL.Image.BICUBIC` filters
(for example, reducing within several steps), they a unnecessary now.
Antialias renamed to Lanczos
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
New :py:attr:`PIL.Image.LANCZOS` constant was added instead of
:py:attr:`PIL.Image.ANTIALIAS`.
:py:attr:`~PIL.Image.ANTIALIAS`.
When :py:attr:`~PIL.Image.ANTIALIAS` was initially added, it was the only
high-qality filter based on convolutions. It's name was supposed to reflect
@ -25,9 +47,16 @@ and is an alias for :py:attr:`~PIL.Image.LANCZOS`.
Lanczos upscaling quality
^^^^^^^^^^^^^^^^^^^^^^^^^
Image upscaling quality with :py:attr:`PIL.Image.LANCZOS` filter was almost
the same as :py:attr:`PIL.Image.BILINEAR` due to bug. This was fixed.
Bicubic upscaling quality
^^^^^^^^^^^^^^^^^^^^^^^^^
:py:attr:`~PIL.Image.BICUBIC` filter for affine trnsformations was producing
sharp, slightly pixelated image for upscaling. Bicubic for convolutions is
more soft.
Resize performance
^^^^^^^^^^^^^^^^^^