Resumen

COLLAZOS-RAMIREZ, Jhonatan; JOJOA, Pablo-Emilio  y  HOYOS-SANCHEZ, Juan-Pablo. 2D Gradient Algorithms for Noise Reduction in Radiological Images. Rev. Fac. ing. [online]. 2023, vol.32, n.65, e2.  Epub 12-Ene-2024. ISSN 0121-1129.  https://doi.org/10.19053/01211129.v32.n65.2023.16178.

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 $\gamma$ 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).

Palabras clave : 2D adaptive filter; adaptive two-dimensional filter; gradient algorithm; noise cancellation; radiological images; signal processing.

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