论文部分内容阅读
星载被动微波遥感数据以其全天候、穿透性以及不受云干扰等特点,在全球变化研究领域取得了广泛的应用,然而其较低的空间分辨率,限制了后期地物参数的反演精度。对国内外被动微波遥感数据空间分辨率提高方法进行介绍,重点介绍了基于图像处理技术的超分辨率增强和混合像元分解方法。通过对两类方法的介绍和评价,展望被动微波遥感数据混合像元分解方法的研究前景。被动微波遥感数据空间分辨率的有效提高,可以为更多的研究和应用领域服务。
Space-borne passive microwave remote sensing data has been widely used in the field of global change research due to its characteristics of all-weather, penetrating and free from cloud interference. However, its low spatial resolution limits the retrieval of later terrain parameters Accuracy. The methods of improving the spatial resolution of passive microwave remote sensing data at home and abroad are introduced. The methods of super resolution enhancement and mixed pixel decomposition based on image processing are introduced. Through the introduction and evaluation of two kinds of methods, the prospect of mixed pixel decomposition of passive microwave remote sensing data is prospected. The effective improvement of the spatial resolution of passive microwave remote sensing data can serve more research and application fields.