Investigation and Comparative Analysis of the Adaptive Rolling Ball Method for Histological Image Quality Enhancement

The study analyses and compares the Rolling Ball algorithm, which is widely used to enhance histological images. Its primary aim is to quantitatively assess the effectiveness of this background-correction technique during the image-preprocessing stage of histological analysis. We compared the classical algorithm with an improved adaptive variant. Processing quality was assessed using the Signal-to-noise ratio (SNR), Background dispersion and Image entropy. The results show that the Rolling Ball method - particularly in its adaptive implementation - effectively suppresses background inhomogeneity while preserving the morphological detail of cellular structures. Consequently, it is a promising tool for improving the accuracy of subsequent segmentation and morphometric analysis in digital pathomorphology. This study therefore contributes to the development of more reliable preprocessing algorithms for medical microscopy images.

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