COMPARATIVE ANALYSIS OF BIONIC ALGORITHMS OPTIMIZATION PARAMETERS OF FILTERS FOR DENOISING IMAGES WITH IMPULSE NOISE
DOI:
https://doi.org/10.34185/1991-7848.itmm.2026.01.030Keywords:
information technology, image denoising, bionic algorithms, optimizationAbstract
The paper investigates the effectiveness of bionic algorithms for optimizing image denoising filter parameters in conditions of salt & pepper impulse noise. A comparative analysis of the HHO, GWO, WOA and ACO algorithms when setting the parameters of Gaussian and Adaptive Median filters is carried out. Experiments are performed on standard test images Lena and Barbara with different noise levels using the PSNR, convergence_iter and runtime metrics. It is shown that the Adaptive Median filter provides significantly higher restoration quality (≈32.7 dB) compared to the Gaussian filter (≈24.7 dB), while achieving convergence already in the initial iterations. It is established that the type of filter has a decisive influence on the quality of denoising, while bionic optimization algorithms mainly affect the convergence speed and computational efficiency.
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