beam$^{-1}$ (and from 0.372 to 0.362 mJy beam$^{-1}$ for the inner channel range 34 to 114). Hence while flattening the baselines, the method does not significantly change the global noise properties of the cube, In Figure \[fig:projection\], we compare two data cubes, using the same position-velocity cut, one as obtained before the additional continuum subtraction, and one as obtained after the additional continuum subtraction. While the noise features look similar, the continuum subtraction is obviously improved.

![The S-G filter (top row) and examples of the convolution effect on simple functions. The area under the S-G filter in the top row is normalised. From the second to the bottom row, the dark grey curves are linear, second order polynomial and third order polynomial functions and a flat line with a spike on one side. The magenta curves are the result of the grey curves convolved with the S-G filter. The horizontal dashed lines mark the y axis position of 0, and the vertical lines mark the channels 34 and 114.[]{data-label="fig:sgfilter"}](plot/sgfilter.ps){width="8cm"}

![Examples of spectra before (black lines) and after applying the S-G filter (magenta lines). The dashed lines mark the zero level.[]{data-label="fig:subcont"}](plot/fitcont.ps){width="8cm"}

![ An example of an x-z projection from an original 