no code implementations • 15 Sep 2022 • Eduarda T. C. Chagas, Alejandro. C. Frery, Juliana Gambini, Magdalena M. Lucini, Heitor S. Ramos, Andrea A. Rey
The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce.
no code implementations • 23 Apr 2019 • Alejandro C. Frery, Juliana Gambini
The $\mathcal{G}^0$ distribution is widely used for monopolarized SAR image modeling because it can characterize regions with different degree of texture accurately.
no code implementations • 29 Sep 2018 • Débora Chan, Andrea Rey, Juliana Gambini, Alejandro C. Frery
It is well-known that these images are affected by speckle, and prone to contamination as double bounce and corner reflectors.
no code implementations • 1 Jan 2017 • José Naranjo-Torres, Juliana Gambini, Alejandro C. Frery
This paper presents a new proposal for feature extraction and region discrimination in SAR imagery, using the geodesic distance as a measure of dissimilarity between $\mathcal{G}_I^0$ models.
no code implementations • 11 Jul 2016 • Mario Mastriani, Juliana Gambini
In the second one, we apply the Fast Cosine Transform to the image, and then the transformed image is divided in blocks which are collected according to zig-zag scan too.