I currently have images that contain some NaN values within them. I would like SNAP to replace these NaN pixels with the average value of the 3x3 matrix of pixels around the NaN pixel - is there a way to do this? I do not want to do this operation for the whole image, as this would distort my results.
in case the NaN pixels are only single pixels you can
calculate an average product using the 3x3 mean (or median) filter. No more NaNs should be left then in the output raster (let’s say it is named F3).
open the band maths of your original product (O1): and enter something like
IF NaN THEN F3 ELSE O1
The output shoult have replaced these NaNs by the filtered pixels wherever one is NaN.
@ABraun but in your case the value of whole band will be charged, I got from our colleague post, that he wants to replace the nan by matrix 3×3 around , without affects the other values,
@falahfakhri I don’t think so. The filtered image is computed as an intermediate product, but only those filtered values which lie at NaN positions will be replaced in the final (third) product after the band maths, all others remain the original (ELSE O1)…
original (left) and corrected (middle) band, Only the NaNs were replaced, the rest is the original file (as seen in the cyan maximum in the middle and the patterns on the right.
I would like SNAP to replace these NaN pixels with the average value of the 3x3 matrix of pixels around the NaN pixel - is there a way to do this This method replaces all NaN values with a specified value. We can calculate the average of each column using the mean method, which returns a Series containing the average value for each column. Pandas Data Frame. NaN stands for Not A Number and is one of the common ways to represent the missing value in the data. It is a special floating-point value and cannot be converted to any other type than float.1