Isolated NaN pixels in coherence image


After searching the forum I have not seen this issue being asked. Any help will be appreciated.

Whenever I compute the coherence of two images I am getting many isolated NaN pixels in the coherence image. Is there a mathematical explanation for this?

As an example:
Input images (Atacama desert)


graph_backgeo_coh.xml (4.7 KB)

Subset of the output coherence for swath IW2, VV pol:

There are 5 NaN pixels, surrounded by pixels with coherence > 0.9

S1TBX 5.0.3 on Fedora 25.

if you right-click on your coherence band and select properties: Is ‘use NoData value’ checked? Is a NoData value assigned?

1 Like

Thanks for your reply.
In the coherence band properties, I can see:

  • No-Data value used: checked
  • No-Data value: 0.0

Tracing back the NaN pixels in the graph, they seem to originate from pixels in the input images with 0 in either the I or Q component. Those pixels are converted to NaN, and these NaNs are propagated forward in the graph. Could this be? If this is what is happening, is there a way to make sure that gpt treats zeros as zeros and not as NaNs?

Problems with NaN values have recently reported here:

This won’t probably help you right now but maybe you can also suggest improvements there.

OK I post there as well.