Background Estimates

In most astronomical observations the image intensity consists of contributions from both object and sky background. Depending on the complexity of the field and the type of object, different methods are used to estimate and subtract the background intensity. For linear detectors this can be done directly on the intensity calibrated frame while special consideration must be given when a non-linear response transformation is used (i.e. for photographic emulsions) due to the non-gaussian noise distribution. In the latter case a fit is normally done to the original data and the fitted values then transformed to intensities and subtracted.

An accurate determination of the background is extremely important for the latter analysis. Therefore, one prefers to use all pixels, which are not contaminated by sources, and fit a low order polynomial surface to the background. Non-linear filters are often used to remove stellar images and other sharp features (see Section 2.2.1) while extended objects are very difficult to eliminate automatically. If only point like objects are analyzed background following methods like the recursive filter described by Martin and Lutz (1979) can be used.

Also $\kappa \sigma$-clipping techniques are applied in an iterative scheme where pixels with high residual compared to a low order polynomial fit to the frame are rejected (Capaccioli and Held 1979). In this method areas containing extended objects can be excluded before the iteration starts. In Figure 2.8, a field with extended objects is shown with the mask defining the areas to be omitted in the computations.

  

Figure 2.8: Background fitting with an iterative $\kappa \sigma$ technique: (A) original, (B) mask of included areas, and (C) fitted background.