Comparing compression in different formats: Difference between revisions

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== Method ==  
== Method ==  
[[File:Format comparison baseline image.PNG|thumb|right|Baseline image contains naked rock, scattered forests and built-up areas ]]
[[File:Format comparison baseline image.PNG|thumb|right|Baseline image contains naked rock, scattered forests and built-up areas ]]
We compare a lossless baseline image to a compressed image and measure the SSIM using Python package ''skimage''. This is repeated with a range of quality values for the compressed images.  
We compare a lossless baseline image to a compressed image and measure the SSIM using Python package [https://scikit-image.org/ scikit-image]. This is repeated with a range of quality values for the compressed images.  
This should give an indication of which method is most efficient. In addition, it will indicate the quality value which will achieve the same SSIM across the compression methods.
This should give an indication of which method is most efficient. In addition, it will indicate the quality value which will achieve the same SSIM across the compression methods.


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| Pixel size || 0.25 meters
| Pixel size || 0.25 meters
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== Result ==
== Result ==

Revision as of 13:46, 22 June 2022

This is a comparison of a small selection of compression methods used in georeferenced raster imagery. The intention is to find which method gives the best "bang for buck" - the best quality for the smallest file size. The measure for quality is SSIM - structural similarity index , which is a perception-based model to calculate the difference between two images.

Method

Baseline image contains naked rock, scattered forests and built-up areas

We compare a lossless baseline image to a compressed image and measure the SSIM using Python package scikit-image. This is repeated with a range of quality values for the compressed images. This should give an indication of which method is most efficient. In addition, it will indicate the quality value which will achieve the same SSIM across the compression methods.

Note that each of the file formats use a different scale for the input "quality" parameter. We include a wide range of the legal values from each of the formats, so this difference should not matter.

The baseline image has the following attributes:

Attribute Value
File size 273 MB
Format GeoTIFF
Compression LZW
Dimensions 10000 x 10000 px
Pixel size 0.25 meters

Result