2026-03-062024-10-082024 L Latin American Computer Conference (CLEI)https://hdl.handle.net/20.500.12272/14673Automatic 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.pdfen-USinfo:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Maximum likelihood estimation, Machine learning algorithms, Noise, Speckle, Entropy, Radar polarimetry, Vectors, Indexes, Synthetic aperture radar, Synthetic datainfo:eu-repo/semantics/conferenceObjecthttp://creativecommons.org/licenses/by-nc-nd/4.0/10.1109/CLEI64178.2024.10700078