  In this paper, we present a novel approach to the estimation of strongly
varying backgrounds in astronomical images by means of small objects removal
and subsequent missing pixels interpolation. The method is based on the
analysis of a pixel local neighborhood and utilizes the morphological distance
transform. In contrast to popular background estimation techniques, our
algorithm allows for accurate extraction of complex structures, like galaxies
or nebulae. Moreover, it does not require multiple tuning parameters, since it
relies on physical properties of CCD image sensors - the gain and the read-out
noise characteristics. The comparison with other widely used background
estimators revealed higher accuracy of the proposed technique. The superiority
of the novel method is especially significant for the most challenging
fluctuating backgrounds. The size of filtered out objects is tunable, therefore
the algorithm may eliminate a wide range of foreground structures, including
the dark current impulses, cosmic rays or even entire galaxies in deep field
images.
