ImageFilter Module

The ImageFilter module contains definitions for a pre-defined set of filters, which can be be used with the Image.filter() method.

Example: Filter an image

from PIL import ImageFilter

im1 = im.filter(ImageFilter.BLUR)

im2 = im.filter(ImageFilter.MinFilter(3))
im3 = im.filter(ImageFilter.MinFilter)  # same as MinFilter(3)


The current version of the library provides the following set of predefined image enhancement filters:

  • BLUR
class PIL.ImageFilter.Color3DLUT(size, table, channels=3, target_mode=None, **kwargs)

Three-dimensional color lookup table.

Transforms 3-channel pixels using the values of the channels as coordinates in the 3D lookup table and interpolating the nearest elements.

This method allows you to apply almost any color transformation in constant time by using pre-calculated decimated tables.

New in version 5.2.0.

  • size – Size of the table. One int or tuple of (int, int, int). Minimal size in any dimension is 2, maximum is 65.
  • table – Flat lookup table. A list of channels * size**3 float elements or a list of size**3 channels-sized tuples with floats. Channels are changed first, then first dimension, then second, then third. Value 0.0 corresponds lowest value of output, 1.0 highest.
  • channels – Number of channels in the table. Could be 3 or 4. Default is 3.
  • target_mode – A mode for the result image. Should have not less than channels channels. Default is None, which means that mode wouldn’t be changed.
class PIL.ImageFilter.BoxBlur(radius)

Blurs the image by setting each pixel to the average value of the pixels in a square box extending radius pixels in each direction. Supports float radius of arbitrary size. Uses an optimized implementation which runs in linear time relative to the size of the image for any radius value.

Parameters:radius – Size of the box in one direction. Radius 0 does not blur, returns an identical image. Radius 1 takes 1 pixel in each direction, i.e. 9 pixels in total.
class PIL.ImageFilter.GaussianBlur(radius=2)

Gaussian blur filter.

Parameters:radius – Blur radius.
class PIL.ImageFilter.UnsharpMask(radius=2, percent=150, threshold=3)

Unsharp mask filter.

See Wikipedia’s entry on digital unsharp masking for an explanation of the parameters.

  • radius – Blur Radius
  • percent – Unsharp strength, in percent
  • threshold – Threshold controls the minimum brightness change that will be sharpened
class PIL.ImageFilter.Kernel(size, kernel, scale=None, offset=0)

Create a convolution kernel. The current version only supports 3x3 and 5x5 integer and floating point kernels.

In the current version, kernels can only be applied to “L” and “RGB” images.

  • size – Kernel size, given as (width, height). In the current version, this must be (3,3) or (5,5).
  • kernel – A sequence containing kernel weights.
  • scale – Scale factor. If given, the result for each pixel is divided by this value. the default is the sum of the kernel weights.
  • offset – Offset. If given, this value is added to the result, after it has been divided by the scale factor.
class PIL.ImageFilter.RankFilter(size, rank)

Create a rank filter. The rank filter sorts all pixels in a window of the given size, and returns the rank’th value.

  • size – The kernel size, in pixels.
  • rank – What pixel value to pick. Use 0 for a min filter, size * size / 2 for a median filter, size * size - 1 for a max filter, etc.
class PIL.ImageFilter.MedianFilter(size=3)

Create a median filter. Picks the median pixel value in a window with the given size.

Parameters:size – The kernel size, in pixels.
class PIL.ImageFilter.MinFilter(size=3)

Create a min filter. Picks the lowest pixel value in a window with the given size.

Parameters:size – The kernel size, in pixels.
class PIL.ImageFilter.MaxFilter(size=3)

Create a max filter. Picks the largest pixel value in a window with the given size.

Parameters:size – The kernel size, in pixels.
class PIL.ImageFilter.ModeFilter(size=3)

Create a mode filter. Picks the most frequent pixel value in a box with the given size. Pixel values that occur only once or twice are ignored; if no pixel value occurs more than twice, the original pixel value is preserved.

Parameters:size – The kernel size, in pixels.