Unmixing-based multisensor multiresolution image fusion
Unmixing-based multisensor multiresolution image fusion
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DOI：
10.1109/36.763276
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发表时间：
1999-05
期刊：
影响因子：
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通讯作者：
B. Zhukov;D. Oertel;F. Lanzl;G. Reinhäckel
中科院分区：
文献类型：
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作者：
B. Zhukov;D. Oertel;F. Lanzl;G. Reinhäckel
讨论了多传感器多分辨技术（MMT）的约束和无约束算法。它们可以应用于使用来自共配准的高分辨率图像的关于其像素组成的信息来解混低分辨率图像。这使得有可能融合低分辨率和高分辨率图像，以进行协同解释。约束解混保留了低分辨率图像的所有可用辐射信息。另一方面，在有噪声数据的情况下，无约束解混可能是优选的。MMT对传感器误差的敏感性分析表明，最高要求是数据的几何配准精度;配准误差不应超过低分辨率像素大小的0.1 - 0.2。约束和无约束算法的应用说明解混和融合的多分辨率反射和热波段的真实的TM/LANDSAT图像以及未来ASTER/EOS-AMI传感器的模拟图像的例子。
Constrained and unconstrained algorithms of the multisensor multiresolution technique (MMT) are discussed. They can be applied to unmix low-resolution images using the information about their pixel composition from co-registered high-resolution images. This makes it possible to fuse the low- and high-resolution images for a synergetic interpretation. The constrained unmixing preserves all the available radiometric information of the low-resolution image. On the other hand, the unconstrained unmixing may be preferable in case of noisy data. An analysis of the MMT sensitivity to sensor errors showed that the strongest requirement is the accuracy of geometric co-registration of the data; the co-registration errors should not exceed 0.1-0.2 of the low-resolution pixel size. Applications of the constrained and unconstrained algorithms are illustrated on examples of unmixing and fusion of the multiresolution reflective and thermal bands of a real TM/LANDSAT image as well as of a simulated image of the future ASTER/EOS-AMI sensor.