  The MOST, CoRoT, and Kepler space missions led to the discovery of a large
number of intriguing, and in some cases unique, objects among which are
pulsating stars, stars hosting exoplanets, binaries, etc. Although the space
missions deliver photometric data of unprecedented quality, these data are
lacking any spectral information and we are still in need of ground-based
spectroscopic and/or multicolour photometric follow-up observations for a solid
interpretation. Both faintness of most of the observed stars and the required
high S/N of spectroscopic data imply the need of using large telescopes, access
to which is limited. In this paper, we look for an alternative, and aim for the
development of a technique allowing to denoise the originally low S/N
spectroscopic data, making observations of faint targets with small telescopes
possible and effective. We present a generalization of the original
Least-Squares Deconvolution (LSD) method by implementing a multicomponent
average profile and a line strengths correction algorithm. The method was
successfully tested on the high resolution spectra of Vega and a Kepler star,
KIC04749989. Application to the two pulsating stars, 20 Cvn and HD189631,
showed that the technique is also applicable to intrinsically variable stars:
the results of frequency analysis and mode identification from the LSD model
spectra for both objects are in good agreement with the findings from
literature. Depending on S/N of the original data and spectral characteristics
of a star, the gain in S/N in the LSD model spectrum typically ranges from 5 to
15 times. The restored LSD model spectra contain all the information on line
profile variations present in the original spectra. The method is applicable to
both high- (>30 000) and low- (<30 000) resolution spectra, though the
information that can be extracted from the latter is limited by the resolving
power itself.
