Janeth Alpala;Abraão D. C. Nascimento;Alejandro C. Frery
{"title":"利用rsamnyi熵量化SAR图像的异质性","authors":"Janeth Alpala;Abraão D. C. Nascimento;Alejandro C. Frery","doi":"10.1109/LGRS.2025.3581855","DOIUrl":null,"url":null,"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 nonparametric 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.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":4.4000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantifying Heterogeneity in SAR Imagery With the Rényi Entropy\",\"authors\":\"Janeth Alpala;Abraão D. C. Nascimento;Alejandro C. Frery\",\"doi\":\"10.1109/LGRS.2025.3581855\",\"DOIUrl\":null,\"url\":null,\"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 nonparametric 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.\",\"PeriodicalId\":91017,\"journal\":{\"name\":\"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society\",\"volume\":\"22 \",\"pages\":\"1-5\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11045765/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11045765/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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 nonparametric 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.