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Proceedings Paper

Study on Spot5 remote sensing imagery automatic registration methods based on texture feature points
Author(s): Chengzan Chu; Dongmei Yan; Chao Wang; Hong Zhang
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Paper Abstract

Due to the problem of lower-efficiency and subjective error generated by manual operation in the process of Spot5 remote sensing satellite imagery matching, a new efficient automatic registration scheme based on imagery characteristic points was proposed. Firstly, the preprocessed 1A level multispectral imagery and panchromatic imagery were registered coarsely based on affine transformation in this workflow using the ephemeris in metadata files. Secondly, the grid constrained feature points were extracted from the two images by improved Forstner operator, and tie-points pairs were obtained by a coarse-to-fine matching using Euclid distance and correlation. Finally, error pairs were eliminated by least median of squares (LSM). After getting enough control point pairs which were high-precision matched and distributed evenly, coarse-registered multispectral imagery was rectified in local small region based on Delaunay triangulation network. Experiments were performed on many volume images, and the results show that the root mean square errors (RMSE) of the check points are less than 0.5 pixels.

Paper Details

Date Published: 24 November 2008
PDF: 7 pages
Proc. SPIE 7123, Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China, 71230B (24 November 2008); doi: 10.1117/12.816167
Show Author Affiliations
Chengzan Chu, Ctr. for Earth Observation and Digital Earth (China)
Dongmei Yan, Ctr. for Earth Observation and Digital Earth (China)
Institute of Automation (China)
Chao Wang, Ctr. for Earth Observation and Digital Earth (China)
Hong Zhang, Ctr. for Earth Observation and Digital Earth (China)


Published in SPIE Proceedings Vol. 7123:
Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China
Qingxi Tong, Editor(s)

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