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Vol. 32 No. 65 (2023)
July-September 2023 (Continuous Publication)

Papers

2D Gradient Algorithms for Noise Reduction in Radiological Images

https://doi.org/10.19053/01211129.v32.n65.2023.16178

Published 2023-04-04

Jhonatan Collazos-Ramírez
Universidad del Cauca

Pablo-Emilio Jojoa
Universidad del Cauca

Juan-Pablo Hoyos
Universidad Nacional de Colombia

Abstract

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).

Keywords

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

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