Distinguishing Samples from the GI0 Distribution by using Tsallis Entropy
| dc.creator | Rey, Andrea | |
| dc.creator | Gambini, Juliana | |
| dc.creator.orcid | 0000-0002-9185-1382 | |
| dc.creator.orcid | 0000-0002-4534-1402 | |
| dc.date.accessioned | 2026-03-06T11:54:53Z | |
| dc.date.issued | 2024-10-08 | |
| dc.description.abstract | Automatic Synthetic Aperture Radar image interpretation is an important issue in image processing because of its multiple applications in environmental monitoring. This type of image is contaminated with speckle noise, which obstructs classical image analysis. However, it has been widely proved that they can be properly modeled with the G0 distribution. This work is dedicated to developing methods for discriminating SAR image regions with different levels of texture. A hypothesis test is constructed based on the Tsallis entropy of the G0 distribution for intensity data. A series of tests are carried out with synthetic data. The obtained results are encouraging. | |
| dc.description.affiliation | Rey, Andrea. Universidad Nacional de Hurlingham (UNAHUR). Laboratorio de Investigación y Desarrollo Experimental en Computación; Argentina. Universidad Tecnológica Nacional (UTN). Centro de Procesamiento de Señales e Imágenes; Argentina. | |
| dc.description.affiliation | Gambini, Juliana. Universidad Nacional de Hurlingham (UNAHUR). Laboratorio de Investigación y Desarrollo Experimental en Computación; Argentina. Universidad Tecnológica Nacional (UTN). Centro de Procesamiento de Señales e Imágenes; Argentina. | |
| dc.format | ||
| dc.identifier.citation | 2024 L Latin American Computer Conference (CLEI) | |
| dc.identifier.doi | 10.1109/CLEI64178.2024.10700078 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12272/14673 | |
| dc.language.iso | en_US | |
| dc.publisher | IEEE | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.rights.use | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Maximum likelihood estimation, Machine learning algorithms, Noise, Speckle, Entropy, Radar polarimetry, Vectors, Indexes, Synthetic aperture radar, Synthetic data | |
| dc.title | Distinguishing Samples from the GI0 Distribution by using Tsallis Entropy | |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.type.version | publisherVersion |