14 July 2003 Multisource remote sensing information fusion based on wavelet transformation algorithm
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Abstract
This paper presents the results of an intercomparison study of data fusion methods. Three data fusion techniques, based respectively on the Daubechies wavelet basis method, the IHS transform, and the Principle Component Analysis (PCA), are compared with each other. According to the data set we used in this study, the Daubechies Wavelet Basis method is far more efficient than the PCA and the IHS transform, It thus establishes the advantages for data fusion, formally called multiple resolution analysis. This method is the best among the three for image sharpening and for maintaining the information of the original data. We conclude with the result from this study that the Daubechies Wavelet Basis method has the largest application potential for merging the spatial and spectral characteristics of multiple resolution remote sensing data with high efficiency.
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Jianli Ding, Jianli Ding, Qijiang Zhu, Qijiang Zhu, Ying Zhang, Ying Zhang, Tashpolat Tiyip, Tashpolat Tiyip, Chuansheng Liu, Chuansheng Liu, Rui Sun, Rui Sun, Xiaoling Pan, Xiaoling Pan, } "Multisource remote sensing information fusion based on wavelet transformation algorithm", Proc. SPIE 4890, Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land, (14 July 2003); doi: 10.1117/12.466699; https://doi.org/10.1117/12.466699
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