I have a signal organized as an image, i.e. a matrix. Each "pixel" has an error $\sigma_{i,j}$. Simplifying, let's assume that the error is the same for all the involved "pixels". How can I compute the corresponding noise associated to each pixel at 1 sigma error? Clearly, I'm assuming a gaussian distribution for the noise for each pixel.

  • $\begingroup$ Do you mean standard error or standard deviation. The two are not the same? $\endgroup$ – Dave Mar 21 '20 at 14:38
  • $\begingroup$ @Dave: sorry, i simply meant that the error on pixels is the same across the signal. It's only a simplification. $\endgroup$ – Giuseppe Angora Mar 21 '20 at 17:33

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