You can reproduce some of the image processing described here with software today.<p>For example, in Figure 3, the histogram at the top right is a &quot;periodogram&quot; of the original image data. It shows that the original image is skewed towards the high end of the frequency spectrum. They apply a high-pass filter (discard the lowest frequencies) so the processed image shows higher details than the original.<p>If you had the original photograph as an image file, let&#x27;s say an image of the surface of Mars, [0] you could filter out the lowest ten frequency components with a Python script: [1]<p><pre><code>    pip install avena
    avena filter high 10 pia19676-fig1_ml_mcam04403coloradjusted24bwscale.jpg
</code></pre>
The result: <a href="http:&#x2F;&#x2F;imgur.com&#x2F;a&#x2F;ASusx" rel="nofollow">http:&#x2F;&#x2F;imgur.com&#x2F;a&#x2F;ASusx</a><p>Notice the details are more visible.<p>[0] <a href="http:&#x2F;&#x2F;www.nasa.gov&#x2F;jpl&#x2F;msl&#x2F;pia19676&#x2F;geological-contact-zone-near-marias-pass-on-mars" rel="nofollow">http:&#x2F;&#x2F;www.nasa.gov&#x2F;jpl&#x2F;msl&#x2F;pia19676&#x2F;geological-contact-zone...</a><p>[1] (shameless plug) <a href="https:&#x2F;&#x2F;github.com&#x2F;eliteraspberries&#x2F;avena" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;eliteraspberries&#x2F;avena</a>