人工智能
图像融合
图像分辨率
像素
计算机视觉
计算机科学
图像配准
传感器融合
保险丝(电气)
遥感
多分辨率分析
图像(数学)
模式识别(心理学)
地质学
小波变换
小波
离散小波变换
电气工程
工程类
作者
Β. Zhukov,D. Oertel,F. Lanzl,G. Reinhackel
摘要
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.
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