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Article

Pixel-Level Decision Fusion for Land Cover Classification Using PolSAR Data and Local Pattern Differences

by
Spiros Papadopoulos
,
Vassilis Anastassopoulos
* and
Georgia Koukiou
Electronics Laboratory, Physics Department, University of Patras, 26504 Patras, Greece
*
Author to whom correspondence should be addressed.
Electronics 2024, 13(19), 3846; https://doi.org/10.3390/electronics13193846 (registering DOI)
Submission received: 27 August 2024 / Revised: 24 September 2024 / Accepted: 26 September 2024 / Published: 28 September 2024
(This article belongs to the Special Issue Artificial Intelligence in Image Processing and Computer Vision)

Abstract

Combining various viewpoints to produce coherent and cohesive results requires decision fusion. These methodologies are essential for synthesizing data from multiple sensors in remote sensing classification in order to make conclusive decisions. Using fully polarimetric Synthetic Aperture Radar (PolSAR) imagery, our study combines the benefits of both approaches for detection by extracting Pauli’s and Krogager’s decomposition components. The Local Pattern Differences (LPD) method was employed on every decomposition component for pixel-level texture feature extraction. These extracted features were utilized to train three independent classifiers. Ultimately, these findings were handled as independent decisions for each land cover type and were fused together using a decision fusion rule to produce complete and enhanced classification results. As part of our approach, after a thorough examination, the most appropriate classifiers and decision rules were exploited, as well as the mathematical foundations required for effective decision fusion. Incorporating qualitative and quantitative information into the decision fusion process ensures robust and reliable classification results. The innovation of our approach lies in the dual use of decomposition methods and the application of a simple but effective decision fusion strategy.
Keywords: land cover classification; decision fusion; local pattern differences; fully PolSAR land cover classification; decision fusion; local pattern differences; fully PolSAR

Share and Cite

MDPI and ACS Style

Papadopoulos, S.; Anastassopoulos, V.; Koukiou, G. Pixel-Level Decision Fusion for Land Cover Classification Using PolSAR Data and Local Pattern Differences. Electronics 2024, 13, 3846. https://doi.org/10.3390/electronics13193846

AMA Style

Papadopoulos S, Anastassopoulos V, Koukiou G. Pixel-Level Decision Fusion for Land Cover Classification Using PolSAR Data and Local Pattern Differences. Electronics. 2024; 13(19):3846. https://doi.org/10.3390/electronics13193846

Chicago/Turabian Style

Papadopoulos, Spiros, Vassilis Anastassopoulos, and Georgia Koukiou. 2024. "Pixel-Level Decision Fusion for Land Cover Classification Using PolSAR Data and Local Pattern Differences" Electronics 13, no. 19: 3846. https://doi.org/10.3390/electronics13193846

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