Next Article in Journal
Model Based Open-Loop Wind Farm Control Using Active Power for Power Increase and Load Reduction
Previous Article in Journal
Effect of Molybdenum on the Microstructures and Properties of Stainless Steel Coatings by Laser Cladding
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(10), 1066; https://doi.org/10.3390/app7101066

Automatic Matching of Multi-Source Satellite Images: A Case Study on ZY-1-02C and ETM+

1
College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2
Tianjin Key Laboratory of Intelligent Information Processing in Remote Sensing, Tianjin 300000, China
*
Author to whom correspondence should be addressed.
Received: 8 September 2017 / Revised: 11 October 2017 / Accepted: 12 October 2017 / Published: 15 October 2017
(This article belongs to the Section Computer Science and Electrical Engineering)
View Full-Text   |   Download PDF [4422 KB, uploaded 17 October 2017]   |  

Abstract

The ever-growing number of applications for satellites is being compromised by their poor direct positioning precision. Existing orthoimages, such as enhanced thematic mapper (ETM+) orthoimages, can provide georeferences or improve the geo-referencing accuracy of satellite images, such ZY-1-02C images that have unsatisfactory positioning precision, thus enhancing their processing efficiency and application. In this paper, a feasible image matching approach using multi-source satellite images is proposed on the basis of an experiment carried out with ZY-1-02C Level 1 images and ETM+ orthoimages. The proposed approach overcame differences in rotation angle, scale, and translation between images. The rotation and scale variances were evaluated on the basis of rational polynomial coefficients. The translation vectors were generated after blocking the overall phase correlation. Then, normalized cross-correlation and least-squares matching were applied for matching. Finally, the gross errors of the corresponding points were eliminated by local statistic vectors in a TIN structure. Experimental results showed a matching precision of less than two pixels (root-mean-square error), and comparison results indicated that the proposed method outperforms Scale-Invariant Feature Transform (SIFT), Speeded Up Robust Features (SURF), and Affine-Scale Invariant Feature Transform (A-SIFT) in terms of reliability and efficiency. View Full-Text
Keywords: image matching; ZY-1-02C; ETM+; positioning precision image matching; ZY-1-02C; ETM+; positioning precision
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Wang, B.; Peng, J.; Wu, X.; Bao, J. Automatic Matching of Multi-Source Satellite Images: A Case Study on ZY-1-02C and ETM+. Appl. Sci. 2017, 7, 1066.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top