This article analyzes the possibilities of developing and applying a filtering algorithm to remove noise from images using one of the digital filters — the median digital filter. The median digital filter effectively reduces noise in signal and image processing while precisely preserving their contours and structures. Considering the effective features of the digital filter, this approach ensures maximum noise elimination and complete signal recovery in the field of biomedical signal and image processing. The article provides a detailed analysis of the theoretical foundations of filtering and develops a mathematical model. Using this model, studies are conducted on the efficiency of biomedical image processing, particularly focusing on preserving image quality, minimizing noise, and achieving interpolation accuracy. The practical application of the developed algorithm is assessed based on its role in improving diagnostic outcomes in real-life medical image processing. Additionally, the article explores new opportunities for applying this approach in biomedicine and other technical fields.

Median filter, signal processing, biomedical signals, image quality preservation, noise reduction, interpolation, mathematical model, medical diagnostics.

Zaynidinov, H., Xuramov, L., Khodjaeva, D. Intelligent algorithms of digital processing of biomedical images in wavelet methods // Artificial Intelligence, Blockchain, Computing and Security - Proceedings of the International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023, 2024, 2, страницы 648–653

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