IRAF/STECF 2-D spectrum point source / background decomposition package ST-ECF

SPECRES - Point Source Extraction and Background Decomposition of 2-D Spectra


Jeremy R. Walsh


Introduction

In the spectrometry of point sources, the advantage of obtaining long slit spectra over using single aperture spectra is that it provides a simultaneous spectrum of the background on both sides of the point source. The spectrum of the point source can be extracted from the larger-scale scene by many methods, from simple box extraction (summing of a number of lines in the spatial direction) to more refined methods such as optimal weighting (Horne 1986; Robertson 1986). However none of these methods provide an answer to how to estimate the background "under" the point source.

When the background is simple, such as a flat or sloping background, a linear interpolation of the values from both sides of the source is sufficient, but in the case of complex backgrounds, such as galactic nuclei with strong gradients, higher order fitting is required. The general problem is one of spectral decomposition - of separating the spectra of the point sources from the background. If the spatial profile of the point source(s) with wavelength is available, then it can be used with a restoration technique to decompose the point source spectra from the background spectrum. This is analagous to the image restoration case of a known Point Spread Function (PSF); for long slit spectra the Point Spread Function along the slit is referred to here as the Slit Spread Function, SSF.

There are many astrophysically useful applications of spectral decomposition from the simple one of subtracting the sky spectrum, to more complex ones such as determining the spectrum of the cusp of a galaxy nucleus, extracting spectra of closely separated stellar sources, such as binaries, or extracting multiple stellar spectra in crowded regions and extracting emission line spectra from high continuum complex scenes (see Walsh 2001 and Lucy and Walsh 2002). In addition, there are a variety of applications in nebular spectrometry when it may be the complete background spectrum, with the point sources removed, which is of scientific interest.

The "specres" package provides software tools to extract point source spectra from longslit or 2-D spectra with a known SSF. The technique is an extension of familiar image restoration methods used to improve the spatial resolution of imaging data. It can be simply thought of as multiple 1-D image restoration, where the single dimension is the signal distribution along the slit (the cross-dispersion direction) and the multiplicity is provided by the number of channels in the dispersion direction. It must be emphasized that there is no spectral restoration being undertaken, i.e. the spectral resolution remains unchanged as a result of these purely spatial restorations.

The STECF IRAF layered package "specres" provides two tasks to extract point source spectra from 2-D images (either longslit, multislit or cross-dispersed) and decompose the full background over the image. The tasks use the Richardson-Lucy (Lucy, 1974; Richardson 1972) iterative restoration algorithm to perform a maximum likelihood estimation and are fully described in Lucy & Walsh (2002). The codes employ adaptions of the Lucy-Hook (Hook & Lucy 1994) two-channel restoration technique, whereby a smoothing kernel is used to distinguish the extended source from the designated point sources. One of the codes utilises the (strong) constraint that the spectrum of the background is spatially unchanging (the "homogeneous" case). The other code uses the R-L scheme for the decomposition of the point source(s) and background applied independently to each spectral channel (the "inhomogeneous" case). Neither code however employs an entropy constraint in contrast to the Lucy-Hook technique.

The output products are the extracted spectra of the designated point source(s) and the estimated background image. A Point Source Function spectrum image is required as a 2-D spectrum. A task is also provided in the package to produce an SSF image from sets of (2-D spatial) PSF's, by simulating the spatial profile produced by placing a long slit over the PSF images and interpolating between the wavelengths of the individual PSF's.

Components of Package

See the demo directory to try out the package.

Examples of simulated and real data

  • Figure 1. Longslit PSF image formed from three Gaussian spatial Point Spread Function Images of FWHM 4.0, 6.0 and 8.0 pixels at wavelengths of 7150, 7750 and 8300A. The wavelength coverage of the reference image was 7100 to 8345A and the SSF has been subsampled by a factor of 4 with respect to the input PSF images. The output SSF is centred at Y pixel 104.75 (256x256 image).


  • Figure 2. Left figure shows a simulated image consisting of three point sources of Gaussian FWHM 4.0 pixels with fluxes in ratio 1.0:5.0:0.5 (bottom to top) on a tilted elliptical background and with a simulated night sky spectrum. The upper and lower point source spectra are tilted. The image has random Gaussian noise.
    Right figure shows the resulting background fit for a specinholucy restoration with 50 iterations. The positions of the point sources was exactly given by the input table specifying their positions. The FWHM of the background smoothing kernel was 11.8 pixels and the PSF was not subsampled.
    Below are shown the three restored spectra of the point sources (The simulated fluxes were 1000, 5000 and 500 counts):


  • Figure 3. Left figure shows a simulated image consisting of three point sources of Gaussian FWHM 4.0 pixels with fluxes in ratio 1.0:5.0:0.5 (bottom to top) on a broad pedestal, whose spatial profile is wavelength independent, and with "sky" lines included. The image has random Gaussian noise.
    Right figure shows the resulting background fit for a specholucy restoration with 50 iterations for the point sources and background spectra and the collapsed background. The position of the point sources was exactly given by the input table specifying their positions. The FWHM of the background smoothing kernel was 19 pixels and the PSF was not subsampled.
    Below are shown the three restored spectra of the point sources (The simulated fluxes were 1000, 5000 and 500 counts):


  • Figure 4. Left figure shows an HST STIS G430M spectrum of the nucleus of the Seyfert galaxy NGC 4151 (PI: J. Hutchings, Programme 7569; see Hutchings et al. 1998, ApJ, 492, 115). The spectral range is 4820 to 5100A and shows the H-beta and [O III] 4959 & 5007A emission lines.
    Right figure shows the background with the nuclear point source removed using the specnlucy code. The PSF was provided by TinyTim. A high quality removal of the very bright point source is achieved; the mis-match is caused by the inadequacy of the Tiny Tim PSF model for this very high signal-to-noise (>200) continuum source.
    Below is shown the extracted point source spectrum of the NGC 4151 nucleus.


  • Figure 5. Left figure shows an HST STIS G750M longslit spectrum of the nucleus of the active galaxy M 81 (NGC 3031) taken in Programme 7350 (PI: G. Bower). The image was formed by shifting and combining 12 separate images taken with a series of offsets of the nucleus of M 81 along the slit. The spectral range is 8275 to 8850A to include the Ca II triplet absorption lines. The ugly sets of bad pixels arise from incompletely elimated hot pixels in the individual images. These pixels have been appropriately flagged in the data quality image and so are not considered in the restoration.
    Right figure shows the background with the nuclear point source removed using the specslucy code. The PSF was again provided by TinyTim.
    Below is shown the extracted point source spectrum of the M 81 nucleus with an asymmetric emission line of [Fe II] 8617A, not present in the underlying galaxy continuum.


  • Figure 6. The top left image shows a slit spectrum of a planetary nebula in the nearby elliptical galaxy NGC 5128 (Cen-A) taken with FORS1 on the VLT in multi-slit mode. The planetary nbeula is an unresolved point source at the distance of this galaxy (3.5Mpc). The strong background is composed of both sky and galaxy stellar continuum.
    The top right image shows the sky+galaxy background image from a specholucy restoration. The Point Spread Function was provided by a star on the slit.
    The image on the right shows the intrinsic spectrum of the planetary nebula formed by subtracting the restored background image (top right) from the observed longslit spectrum (top left). Weak emission lines, such as [O III]4363A, are detectable.

    References

    Hook, R.N., Lucy. L.B., Stockton, A. & Ridgway, S., 1994. "Two Channel Photometric Image Restoration", ST-ECF Newsletter 21, pp. 16-18.
    Hook, R.N. & Lucy. L.B., 1994. "Image Restorations of High Photometric Quality. II. Examples", Proc. The Restoration of HST Images and Spectra, (eds. R.J. Hanisch & R.L. White), STScI, pp. 86-94.
    Lucy, L. B., 1974. "An iterative technique for the rectification of observed distributions", AJ, 79, 745
    Lucy. L.B., 1994. "Image Restorations of High Photometric Quality.", Proc. The Restoration of HST Images and Spectra, (eds. R.J. Hanisch & R.L. White), STScI, pp. 79-85.
    Lucy, L. B., Walsh, J. R., 2002. "Iterative techniques for the decomposition of long-slit spectra". Submitted to AJ.
    Richardson, W. H., 1972. "Bayesian-Based Iterative Method of Image Restoration", Jou. Opt. Soc. Am., 62, 55.
    Walsh, J. R., 2001. "Long-slit extraction using restoration", ST-ECF Newsletter, 28, pp. 5-6.

    Directory of demos


    Last updated 05 December 2002


    [STECF HOME] Maintained by Jeremy Walsh Jeremy.Walsh@eso.org