2D Gradient Algorithms for Noise Reduction in Radiological Images





2D adaptive filter, Noise cancellation, Signal processing, Radiological images, Gradient algorithm


In areas such as biomedical image processing, the techniques or methods used to recover the content in noise-contaminated signals are essential. One of them has been adaptive filtering, which, by adjusting to the desired signal through real-time updating of the coefficients, allows improvement and deconvolution in the recovery of degraded or contaminated images, attracting the attention of researchers in inverse problems. In this paper, the 2D-AR  gradient algorithm is used in noise reduction in dental radiological images, for which simulations are performed to obtain the best configuration of the hyperparameters, and a statistical analysis of the values obtained is performed. Based on the simulation results and the established metrics, it is demonstrated that the algorithm achieves a slightly higher noise reduction than the other 2D gradient algorithms (LMS and NLMS).


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Collazos-Ramírez, J, Jojoa, P-E, & Hoyos, J-P. (2023). 2D Gradient Algorithms for Noise Reduction in Radiological Images. Revista Facultad de Ingeniería, 32(65), e16178. https://doi.org/10.19053/01211129.v32.n65.2023.16178