Unmixing-Based Landsat TM and MERIS FR Data Fusion
Unmixing-Based Landsat TM and MERIS FR Data Fusion
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DOI：
10.1109/lgrs.2008.919685
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发表时间：
2008-05
影响因子：
4.8
通讯作者：
R. Zurita-Milla;J. Clevers;M. Schaepman
中科院分区：
文献类型：
--
作者：
R. Zurita-Milla;J. Clevers;M. Schaepman
基于分解的数据融合技术被用于生成具有陆地卫星专题地图(TM)的空间分辨率和由中分辨率成像光谱仪(MERIS)传感器提供的光谱分辨率的图像。该方法需要对以下两个参数进行优化：用于TM图像分类的类数和用于求解分解方程的MERIS邻域的大小。ERGAS指数用于评估TM和MERIS空间分辨率的融合图像的质量，并帮助确定需要优化的两个参数的最佳组合。结果表明，在保持MERIS光谱分辨率的同时，成功地将MERIS全分辨率数据缩小到类似陆地卫星的空间分辨率是可能的。
An unmixing-based data fusion technique is used to generate images that have the spatial resolution of Landsat Thematic Mapper (TM) and the spectral resolution provided by the Medium Resolution Imaging Spectrometer (MERIS) sensor. The method requires the optimization of the following two parameters: the number of classes used to classify the TM image and the size of the MERIS ldquowindowrdquo (neighborhood) used to solve the unmixing equations. The ERGAS index is used to assess the quality of the fused images at the TM and MERIS spatial resolutions and to assist with the identification of the best combination of the two parameters that need to be optimized. Results indicate that it is possible to successfully downscale MERIS full resolution data to a Landsat-like spatial resolution while preserving the MERIS spectral resolution.