Built-in enhancement methods


The most basic operation is to stretch the image so that the data fits to the output format. There are many different ways to stretch the data, which are configured by giving them in kwargs dictionary, like in the example above. The default, if nothing else is defined, is to apply a linear stretch. For more details, see enhancing the images.


As the name suggests, linear stretch converts the input values to output values in a linear fashion. By default, 5% of the data is cut on both ends of the scale, but these can be overridden with cutoffs=(0.005, 0.005) argument:

- name: stretch
  method: !!python/name:satpy.enhancements.stretch
    stretch: linear
    cutoffs: [0.003, 0.005]


This enhancement is currently not optimized for dask because it requires getting minimum/maximum information for the entire data array.


The crude stretching is used to limit the input values to a certain range by clipping the data. This is followed by a linear stretch with no cutoffs specified (see above). Example:

- name: stretch
  method: !!python/name:satpy.enhancements.stretch
    stretch: crude
    min_stretch: [0, 0, 0]
    max_stretch: [100, 100, 100]

It is worth noting that this stretch can also be used to _invert_ the data by giving larger values to the min_stretch than to max_stretch.





Use numpy.interp() to linearly interpolate data to a new range. See satpy.enhancements.piecewise_linear_stretch() for more information and examples.


Logarithmic stretch based on a cira recipe.


Stretch method based on the Reinhard algorithm, using luminance.

The function includes conversion to sRGB colorspace.

Reinhard, Erik & Stark, Michael & Shirley, Peter & Ferwerda, James. (2002). Photographic Tone Reproduction For Digital Images. ACM Transactions on Graphics. :doi: 21. 10.1145/566654.566575



The colorize enhancement can be used to map scaled/calibrated physical values to colors. One or several standard Trollimage color maps may be used as in the example here:

- name: colorize
  method: !!python/name:satpy.enhancements.colorize
        - {colors: spectral, min_value: 193.15, max_value: 253.149999}
        - {colors: greys, min_value: 253.15, max_value: 303.15}

It is also possible to provide your own custom defined color mapping by specifying a list of RGB values and the corresponding min and max values between which to apply the colors. This is for instance a common use case for Sea Surface Temperature (SST) imagery, as in this example with the EUMETSAT Ocean and Sea Ice SAF (OSISAF) GHRSST product:

- name: osisaf_sst
  method: !!python/name:satpy.enhancements.colorize
        - colors: [
          [255, 0, 255],
          [195, 0, 129],
          [129, 0, 47],
          [195, 0, 0],
          [255, 0, 0],
          [236, 43, 0],
          [217, 86, 0],
          [200, 128, 0],
          [211, 154, 13],
          [222, 180, 26],
          [233, 206, 39],
          [244, 232, 52],
          [255.99609375, 255.99609375, 63.22265625],
          [203.125, 255.99609375, 52.734375],
          [136.71875, 255.99609375, 27.34375],
          [0, 255.99609375, 0],
          [0, 207.47265625, 0],
          [0, 158.94921875, 0],
          [0, 110.42578125, 0],
          [0, 82.8203125, 63.99609375],
          [0, 55.21484375, 127.9921875],
          [0, 27.609375, 191.98828125],
          [0, 0, 255.99609375],
          [100.390625, 100.390625, 255.99609375],
          [150.5859375, 150.5859375, 255.99609375]]
          min_value: 296.55
          max_value: 273.55

The RGB color values will be interpolated to give a smooth result. This is contrary to using the palettize enhancement.

If the source dataset already defines a palette, this can be applied directly. This requires that the palette is listed as an auxiliary variable and loaded as such by the reader. To apply such a palette directly, pass the dataset keyword. For example:

- name: colorize
  method: !!python/name:satpy.enhancements.colorize
      - dataset: ctth_alti_pal
        color_scale: 255


If the source data have a valid range defined, one should not define min_value and max_value in the enhancement configuration! If those are defined and differ from the values in the valid range, the colors will be wrong.

The above examples are just three different ways to apply colors to images with Satpy. There is a wealth of other options for how to declare a colormap, please see create_colormap() for more inspiration.



The three_d_effect enhancement adds an 3D look to an image by convolving with a 3x3 kernel. User can adjust the strength of the effect by determining the weight (default: 1.0). Example:

- name: 3d_effect
  method: !!python/name:satpy.enhancements.three_d_effect
    weight: 1.0