Paper
29 December 2008 Research on data fusion for monitoring ground subsidence using InSAR
Jing Ma, Qin Zhang, Xianglei Liu, Chaoying Zhao
Author Affiliations +
Proceedings Volume 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA); 72855C (2008) https://doi.org/10.1117/12.815262
Event: International Conference on Earth Observation Data Processing and Analysis, 2008, Wuhan, China
Abstract
Interferometric Synthetic Aperture Radar (InSAR) magtitude map, extracted from Differential- Interferometric Syntheric Aperture Radar (D-InSAR) technology, has a low-resolution, so it has a certain limitation to the explanation and analysis of subsiding area. In order to solve the problem of lacking enough spatial information of D-InSAR image, in this essay we take a data fusion between D-InSAR image and high resolution Remote Sensing (RS) image, obtaining an image containing subsiding information and high-resolution spatial information. This paper mainly focuses on the study of a Mag-Phase algorithm (MPH) algorithm and other fusion algorithms including Hue-Intensity-Saturation (HIS) transformation, Principal Component Analysis (PCA) transformation, Product fusion, Ratio fusion, Wavelet fusion for magtitude map and deformation map, and we take the deformation map and panchromatic (PAN) image of Enhanced Thematic Mapper + (ETM+) (magtitude map) of Xi'an area as an example to do data fusion according to the algorithms above. At last, a comprehensive evaluation and analysis for fusion images is made with subjective and objective evaluation criteria, and a conclusion that MPH fusion algorithm is better than others is also obtained.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jing Ma, Qin Zhang, Xianglei Liu, and Chaoying Zhao "Research on data fusion for monitoring ground subsidence using InSAR", Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855C (29 December 2008); https://doi.org/10.1117/12.815262
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KEYWORDS
Image fusion

Data fusion

Interferometric synthetic aperture radar

Image processing

Image information entropy

Information fusion

Principal component analysis

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