RT journal article
T1 4DCAF: A Temporal Approach for Denoising  Hyperspectral Image Sequences
A1 Priego Torres, Blanca María
A1 Duro, Richard J.
A1 Chanussot, Jocelyn
A2 Ingeniería en AutomáticaElectrónica, Arquitectura y Redes de Computadores
K1 Hyperspectral
K1 Temporal denoising
K1 Cellular automata
K1 4DCAF
AB Due to the rapid advancement of sensor technology over the past decade, it is now feasible to capture sequences of hyperspectral images at acceptable frame rates. Nonetheless, these sequences can be heavily affected by noise, particularly when the data spans the thermal spectrum. Although there is extensive research on denoising standard video sequences and still hyperspectral images, there is limited work on denoising hyperspectral sequences. This paper introduces a new denoising technique specifically designed for actual hyperspectral sequences. The method utilizes spatio-spectral-temporal cellular automata-based filtering, offering several advantages. Notably, the cellular automaton employed can incorporate information about the type of noise present by using specific sequences to fine-tune the algorithm. Additionally, it accounts for temporal information through a spatio-temporal neighborhood when processing each pixel in the sequence. The proposed method surpasses several leading algorithms on both simulated and real sequences.
PB Elsevier
SN 0031-3203
YR 2017
FD 2017
LK http://hdl.handle.net/10498/34693
UL http://hdl.handle.net/10498/34693
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 10-may-2026