Quantitative approach for snowy feature detection using polarimetric analysis

Global Transitions Proceedings Pub Date : 2022-06-01 DOI:10.1016/j.gltp.2022.03.009

Plasin Francis Dias , R.M. Banakar

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Abstract

Synthetic aperture radar is an advanced remote sensing and imaging radar. It plays vital role in acquiring high resolution images of earth surface. The capturing of images by synthetic aperture radar is done in any season immaterial of weather conditions. This paper gives the details of the basic feature extraction for the snow images. The two sample images are analyzed to know the feature details of the object under consideration. Analytical details of variation in entropy and the polarization were considered. The scattering mechanism involved in the snow area is analyzed. The details of snow classification based on its layered structure along with its physical nature like moisture involved are presented. The results indicate a high value of entropy of 0.94 for the snow image. The reason for high entropy is because of more surface uniformity in the snow images. The flat surface structured snow basically exhibits the surface scattering mechanism.

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基于偏振分析的积雪特征定量检测方法

合成孔径雷达是一种先进的遥感成像雷达。它在获取高分辨率地球表面图像中起着至关重要的作用。合成孔径雷达的图像采集可以在任何季节进行，不受天气条件的影响。本文详细介绍了雪景图像的基本特征提取方法。对两个样本图像进行分析，以了解所考虑对象的特征细节。考虑了熵变和极化的分析细节。分析了积雪区散射机理。根据积雪的层状结构及其所涉及的水分等物理性质，详细介绍了积雪的分类方法。结果表明，该图像的熵值较高，为0.94。高熵的原因是由于雪图像的表面更均匀。平面结构雪基本表现为表面散射机制。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Global Transitions Proceedings

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