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IMAGE QUATY ASSESSMENT FOR VHR REMOTE SENSING IMAGE CLASSIFICATION

机译：VHR遥感图像分类的图像质量评估

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摘要

The data from remote sensing images are widely used for characterizing land use and land cover at present. With the increasing availability of very high resolution (VHR) remote sensing images, the remote sensing image classification becomes more and more important for information extraction. The VHR remote sensing images are rich in details, but high within-class variance as well as low between-class variance make the classification of ground cover a difficult task. What's more, some related studies show that the quality of VHR remote sensing images also has a great influence on the ability of the automatic image classification. Therefore, the research that how to select the appropriate VHR remote sensing images to meet the application of classification is of great significance. In this context, the factors of VHR remote sensing image classification ability are discussed and some indices are selected for describing the image quality and the image classification ability objectively. Then, we explore the relationship of the indices of image quality and image classification ability under a specific classification framework. The results of the experiments show that these image quality indices are not effective for indicating the image classification ability directly. However, according to the image quality metrics, we can still propose some suggestion for the application of classification.
机译：来自遥感图像的数据广泛用于表征目前的土地利用和陆地覆盖。随着越来越高的分辨率（VHR）遥感图像的可用性增加，遥感图像分类对于信息提取而变得越来越重要。 VHR遥感图像的细节丰富，但课堂内差异高，并且级别之间的级别方差使得地面的分类覆盖了一项艰巨的任务。更重要的是，一些相关的研究表明，VHR遥感图像的质量也对自动图像分类的能力产生了很大的影响。因此，研究如何选择适当的VHR遥感图像以满足分类的应用具有重要意义。在这种情况下，讨论了VHR遥感图像分类能力的因素，并且选择了一些指标用于客观地描述图像质量和图像分类能力。然后，我们在特定分类框架下探索图像质量和图像分类能力指数的关系。实验结果表明，这些图像质量指标直接指示图像分类能力无效。但是，根据图像质量指标，我们仍然可以提议一些建议进行分类的应用。

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