Optimal Bilateral Filtering of CT Images - Draganov, Ivo; Gancheva, Veska (2021 International Conference on Computational Science and Computational Intelligence (CSCI), 2021)
In this paper a general optimization algorithm is proposed for tuning the parameters of a bilateral filter when processing Computed Tomography images, containing Additive White Gaussian Noise. The Peak Signal to Noise Ratio and the Structural Similarity Index Measure are the target parameters during the optimization with the explicit aim of achieving their maximums. The operation of the optimal configuration of the bilateral filter is compared with the results from filtering of the same images with the Gaussian and average filters. Positive results are obtained and the proposed optimization is considered applicable not only for Computed Tomography images, but also for Magnetic Resonance Imaging, multispectral and hyperspectral images.