Multisource remote sensing data fusion based on wavelet transformation algorithm

Jianli Ding; Qijiang Zhu; Ying Zhang; Tashpolat Tiyip; Chuansheng Liu; Rui Sun; Xiaoling Pan

doi:10.1117/12.466699

14 July 2003 Multisource remote sensing information fusion based on wavelet transformation algorithm

Jianli Ding, Qijiang Zhu, Ying Zhang, Tashpolat Tiyip, Chuansheng Liu, Rui Sun, Xiaoling Pan

Proceedings Volume 4890, Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land; (2003) https://doi.org/10.1117/12.466699
Event: Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2002, Hangzhou, China

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.

Citation Download Citation

Jianli Ding, Qijiang Zhu, Ying Zhang, Tashpolat Tiyip, Chuansheng Liu, Rui Sun, and 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); https://doi.org/10.1117/12.466699

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KEYWORDS

Image fusion

Wavelets

Data fusion

Image enhancement

Principal component analysis

Remote sensing

Spatial resolution

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