Quantifying Heterogeneity in SAR Imagery With the Rényi Entropy

Quantifying heterogeneity in synthetic aperture radar (SAR) data is critical for accurate geophysical interpretation and remote sensing applications. We propose a test statistic based on a non-parametric estimation of Rényi entropy to characterize return heterogeneity from SAR intensity data. The statistic is refined using bootstrap to improve its stability, size, and power. This approach enhances heterogeneity quantification by capturing scale-dependent variations and addressing data-driven uncertainty. Experimental results establish the robustness of the proposed method in distinguishing heterogeneity patterns.

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Publication Details

Journal
IEEE Geoscience and Remote Sensing Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lgrs.2025.3581855
Primary Topic
Advanced SAR Imaging Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Quantifying Heterogeneity in SAR Imagery With the Rényi Entropy

Alejandro C. Frery, Janeth Alpala, Abraão D. C. Nascimento
IEEE Geoscience and Remote Sensing Letters
Advanced SAR Imaging Techniques
article

Quantifying Heterogeneity in SAR Imagery With the Rényi Entropy

Alejandro C. Frery, Janeth Alpala, Abraão D. C. Nascimento
article en

Abstract

Quantifying heterogeneity in synthetic aperture radar (SAR) data is critical for accurate geophysical interpretation and remote sensing applications. We propose a test statistic based on a non-parametric estimation of Rényi entropy to characterize return heterogeneity from SAR intensity data. The statistic is refined using bootstrap to improve its stability, size, and power. This approach enhances heterogeneity quantification by capturing scale-dependent variations and addressing data-driven uncertainty. Experimental results establish the robustness of the proposed method in distinguishing heterogeneity patterns.

IEEE Geoscience and Remote Sensing LettersVol. 22
Universidade Federal de Pernambuco (BR), Victoria University of Wellington (NZ)
Faculty of Science, Victoria University of Wellington, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco
Openalex Percentile: Top 81%
Advanced SAR Imaging Techniques
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