Several modifications of scatter-plot-based method for mixed noise parameters estimation are proposed. The modifications relate to the stage of image segmentation and they are intended to adaptively separate image blocks into clusters taking into account image peculiarities and to choose a required number of clusters. Comparative performance analysis of the proposed modifications for images from TID2008 database is performed. It is shown that the best estimation accuracy is provided by a method with automatic determination of a required number of clusters followed by block separation into clusters using k-means method. This modification allows improving the accuracy of noise characteristics estimation by up to 5% for both signal-independent and signal-dependent noise components in comparison to the basic method. The results for real-life data are presented.
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