Next Article in Journal
Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition
Previous Article in Journal
Land Cover Classification Based on Fused Data from GF-1 and MODIS NDVI Time Series
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2016, 8(9), 743; doi:10.3390/rs8090743

Rigorous Line-Based Transformation Model Using the Generalized Point Strategy for the Rectification of High Resolution Satellite Imagery

1,2,3,* and 1,2
1
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
2
Joint Spatial Information Research Laboratory of Wuhan University and Hong Kong Polytechnic University, Wuhan 430079, China
3
Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Academic Editors: Gonzalo Pajares, Xiaofeng Li and Prasad S. Thenkabail
Received: 8 June 2016 / Revised: 2 September 2016 / Accepted: 5 September 2016 / Published: 8 September 2016
View Full-Text   |   Download PDF [3426 KB, uploaded 8 September 2016]   |  

Abstract

High precision geometric rectification of High Resolution Satellite Imagery (HRSI) is the basis of digital mapping and Three-Dimensional (3D) modeling. Taking advantage of line features as basic geometric control conditions instead of control points, the Line-Based Transformation Model (LBTM) provides a practical and efficient way of image rectification. It is competent to build the mathematical relationship between image space and the corresponding object space accurately, while it reduces the workloads of ground control and feature recognition dramatically. Based on generalization and the analysis of existing LBTMs, a novel rigorous LBTM is proposed in this paper, which can further eliminate the geometric deformation caused by sensor inclination and terrain variation. This improved nonlinear LBTM is constructed based on a generalized point strategy and resolved by least squares overall adjustment. Geo-positioning accuracy experiments with IKONOS, GeoEye-1 and ZiYuan-3 satellite imagery are performed to compare rigorous LBTM with other relevant line-based and point-based transformation models. Both theoretic analysis and experimental results demonstrate that the rigorous LBTM is more accurate and reliable without adding extra ground control. The geo-positioning accuracy of satellite imagery rectified by rigorous LBTM can reach about one pixel with eight control lines and can be further improved by optimizing the horizontal and vertical distribution of control lines. View Full-Text
Keywords: High Resolution Satellite Imagery (HRSI); Line-Based Transformation Model (LBTM); rigorous affine transformation; image rectification; geo-positioning accuracy analysis High Resolution Satellite Imagery (HRSI); Line-Based Transformation Model (LBTM); rigorous affine transformation; image rectification; geo-positioning accuracy analysis
Figures

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 alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Hu, K.; Shi, W. Rigorous Line-Based Transformation Model Using the Generalized Point Strategy for the Rectification of High Resolution Satellite Imagery. Remote Sens. 2016, 8, 743.

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]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top