Automatic Feature Extraction from Satellite Imagery for Remote Sensing

D. D. Mary, Nandana. S Nair, Mohana, S. Revathy, L. Gladence, Bernatin T
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Abstract

Feature extraction from satellite images has steadily but progressively grown in recent years. Numerous feature extraction techniques have been created as a result of the increase. The loss of certain features is one of the various obstacles that must be overcome while selecting the best path for feature extraction. This study suggests utilizing a Convolutional Neural Network (CNN) approach to tackle these issues and extract attributes from satellite images supplied by an open source dataset called MLRSNet. Images with labels explaining each image's characteristics are displayed in the output. This makes it simpler to recognize and understand different components in satellite images.
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遥感卫星图像特征自动提取
近年来,卫星图像特征提取技术稳步发展。由于这一增长,已经创建了许多特征提取技术。在选择特征提取的最佳路径时,某些特征的丢失是必须克服的障碍之一。本研究建议利用卷积神经网络(CNN)方法来解决这些问题,并从一个名为MLRSNet的开源数据集提供的卫星图像中提取属性。输出中显示带有解释每个图像特征的标签的图像。这使得识别和理解卫星图像中的不同组件变得更加简单。
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