XNoise_StDev help page



  GENERAL DESCRIPTION

  The XNoise_StDev widget computes an estimate of the
  gaussian noise standard deviation in a given image; the
  estimator is the standard deviation of the best fit gaussian
  to the data histogram. Before computing the histogram, the
  input image is median-subtracted, in order to remove the
  signal, leaving only pure noise.
    
 
 
  PARAMETERS

  'Patch size for median subtraction':
      Integer size of box for median smoothing of the image.
      The median is subtracted from the image, in order to
      remove the signal from each pixel.

  'Fraction of data points to use':
      To speed up the computation, a value < 1 may be
      selected. In this case a sub-set of pixels is extracted
      from the input data.

  'Threshold to reject out-liers':
      Before computing the histogram, the so-called out-liers
      (pixels whose value is very different from the median or
      the mean of the data) are rejected.
      In practice the median of the data and the standard
      deviation from the median are computed: the out-liers are
      identified as those pixels whose absolute distance from
      the median is larger than a multiple of the standard
      deviation.

  'Minimum number of bins in one HWHM':
      The histogram bin is optimized in order to have a minimum
      number of elements in the histogram width. This will
      improve the accuracy of the fitting.

  'Size of histogram':
      Specify the size of the 'useful' part of the histogram
      around the mode, which will be used for fitting.

  'gaussian' or 'gaussian + constant', etc.:
      Select suitable model for histogram fitting.



  CONTROLS/BUTTONS

  'Processing...':
      Compute and fit the histogram using the currently defined
      parameters. At the end of the computation, a message
      appears reporting the estimated standard deviation and
      the histogram mode, which should be as close as possible
      to 0.

  'Plot histogram':
      Call the XPlot widget to plot the histogram and the best
      fit model. If any of the 'gaussian + background term'
      models is used, the background itself is shown in the plot.

  'Help':
      Display this help page.

  'Exit':
      Quit XNoise_StDev.