RT journal article
T1 A cellular automata-based filtering approach to multi-temporal image denoising
A1 Priego Torres, Blanca María
A1 Prieto, Abraham
A1 Duro, Richard J.
A1 Chanussot, Jocelyn
A2 Ingeniería en AutomáticaElectrónica, Arquitectura y Redes de Computadores
K1 Cellular automata
K1 Low-dose x-ray image
K1 Signal dependent noise
K1 Spatio-temporal denoising
AB This work tackles the challenge of denoising image sequences by employing a spatio-temporal filtering approach based on cellular automata. The proposed algorithm, known as st-CAF, is distinguished by its use of a spatio-temporal neighborhood when processing each pixel in the sequence. Another significant feature of this method is the evolutionary process used to determine the rule sets for the cellular automata, enabling effective adaptation to various types of images and noise through the use of a suitable training set. This adaptability provides a significant advantage over traditional single-frame denoising methods described in the literature, as well as their adaptations for sequences. The paper highlights this advantage by demonstrating the algorithm's performance on different types of noisy images and comparing it with other techniques.
PB Wiley
SN 1468-0394
YR 2017
FD 2017
LK http://hdl.handle.net/10498/34699
UL http://hdl.handle.net/10498/34699
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 10-may-2026