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Machine Learning based Image Processing Techniques for Satellite Image Analysis -A Survey

机译:基于机器学习的卫星图像分析图像处理技术

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This paper presents the detailed comparison of various image processing techniques for analyzing satellite images. The satellite images are large in size, acquired from long distances and are affected by noise and other environmental conditions. Hence it is necessary to process them so that they can be used by the researchers for analysis. Satellite images are widely used in many real time applications such as in agriculture land detection, navigation and in geographical information systems. In this paper, a review of some popular machine learning based image processing techniques is presented. Also a detailed comparison of various techniques is performed. Limitations in each image processing method are also described. In addition to reviewing of different methods, different metrics for performance evaluation in each of the image processing areas is studied.
机译:本文介绍了用于分析卫星图像的各种图像处理技术的详细比较。卫星图像尺寸较大,可以从远距离获取,并且受噪声和其他环境条件的影响。因此,有必要对其进行处理,以便研究人员可以将其用于分析。卫星图像广泛用于许多实时应用中,例如在农业土地检测,导航和地理信息系统中。在本文中,对一些流行的基于机器学习的图像处理技术进行了概述。还进行了各种技术的详细比较。还描述了每种图像处理方法中的限制。除了审查不同的方法外,还研究了每个图像处理领域中用于性能评估的不同指标。

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