(eng): The knowledge of image’s geometric history plays an important role in image signal compression, image registration, image retrieval and especially in image forensics. In this paper we focus on scaling and show that images that have undergone scaling contain hidden cyclostationary features. This makes possible employing the well–developed theory and efficient methods of cyclostationarity for a blind analyzing of the history of images in respect to scaling transformation. To verify this, we also propose a cyclostationarity detection method applied to our problem and show how the traces of scaling can be detected and the specific parameters of the transformation estimated. The method is based on the fact that a cyclostationary signal has a frequency spectrum correlated with a shifted version of itself. A quantitative measure of the efficiency of the method is proposed as well.