All the clump finding algorithms implemented by the FINDCLUMPS command assumes that the noise level is constant across the supplied data array, and equal to the the value of the RMS parameter. This is true even if the supplied NDF contains a VARIANCE component3.
However, in many cases the real noise level may vary across the data array. This may result in real clumps being missed in low noise areas and spurious noise spikes being interpreted as real clumps in high noise areas. To avoid this some way of taking account of the varying noise level is needed. Since the assumption of constant noise level is more or less intrinsic to most of the clump finding algorithms, this is best done by first converting the data array into an array containing the signal-to-noise (SNR) ratio, and then running FINDCLUMPS on this SNR array rather than the original data array. This will determine the spatial extent of each clump, but the output catalogue will contain clump parameters in terms of SNR values rather than the original data values. Therefore, the EXTRACTCLUMPS command should then be used to transfer the clumps outlines found within the SNR array into the original data array and extract the corresponding clump parameters.
So the procedure is as follows.
If you have separate data and noise arrays, then a suitable SNR array can be produced using the KAPPA MATHS command.
The noise level in the SNR array will, by definition, be constant and equal to 1.0.
3Although any available VARIANCE component will be used to determine the default value for the RMS parameter. The GaussClumps algorithm will also use any available variance values to weight the data when fitting individual Gaussians.