Share Email Print
cover

Proceedings Paper

An experimental comparison of ETM+ image geometric correction methods in the mountainous areas of Yunnan Province, China
Author(s): Jinliang Wang; Xuejiao Wu
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Geometric correction of imagery is a basic application of remote sensing technology. Its precision will impact directly on the accuracy and reliability of applications. The accuracy of geometric correction depends on many factors, including the used model for correction and the accuracy of the reference map, the number of ground control points (GCP) and its spatial distribution, resampling methods. The ETM+ image of Kunming Dianchi Lake Basin and 1:50000 geographical maps had been used to compare different correction methods. The results showed that: (1) The correction errors were more than one pixel and some of them were several pixels when the polynomial model was used. The correction accuracy was not stable when the Delaunay model was used. The correction errors were less than one pixel when the collinearity equation was used. (2) 6, 9, 25 and 35 GCP were selected randomly for geometric correction using the polynomial correction model respectively, the best result was obtained when 25 GCPs were used. (3) The contrast ratio of image corrected by using nearest neighbor and the best resampling rate was compared to that of using the cubic convolution and bilinear model. But the continuity of pixel gravy value was not very good. The contrast of image corrected was the worst and the computation time was the longest by using the cubic convolution method. According to the above results, the result was the best by using bilinear to resample.

Paper Details

Date Published: 3 November 2010
PDF: 10 pages
Proc. SPIE 7840, Sixth International Symposium on Digital Earth: Models, Algorithms, and Virtual Reality, 784021 (3 November 2010); doi: 10.1117/12.872968
Show Author Affiliations
Jinliang Wang, Yunnan Normal Univ. (China)
Xuejiao Wu, Yunnan Normal Univ. (China)
Cold and Arid Regions Environmental and Engineering Research Institute (China)


Published in SPIE Proceedings Vol. 7840:
Sixth International Symposium on Digital Earth: Models, Algorithms, and Virtual Reality
Huadong Guo; Changlin Wang, Editor(s)

© SPIE. Terms of Use
Back to Top