Next Article in Journal
High Quality Plasmonic Sensors Based on Fano Resonances Created through Cascading Double Asymmetric Cavities
Previous Article in Journal
Non-Enzymatic Glucose Sensing Using Carbon Quantum Dots Decorated with Copper Oxide Nanoparticles
Open AccessArticle

An Effective Correction Method for Seriously Oblique Remote Sensing Images Based on Multi-View Simulation and a Piecewise Model

1
School of Electronicand Electrical Engineering, Shanghai University of Engineering Science, Longteng Road No. 333, Shanghai 201620, China
2
School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai 200433, China
*
Author to whom correspondence should be addressed.
Academic Editor: Felipe Gonzalez Toro
Sensors 2016, 16(10), 1725; https://doi.org/10.3390/s16101725
Received: 13 July 2016 / Revised: 15 September 2016 / Accepted: 29 September 2016 / Published: 18 October 2016
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
Conventional correction approaches are unsuitable for effectively correcting remote sensing images acquired in the seriously oblique condition which has severe distortions and resolution disparity. Considering that the extraction of control points (CPs) and the parameter estimation of the correction model play important roles in correction accuracy, this paper introduces an effective correction method for large angle (LA) images. Firstly, a new CP extraction algorithm is proposed based on multi-view simulation (MVS) to ensure the effective matching of CP pairs between the reference image and the LA image. Then, a new piecewise correction algorithm is advanced with the optimized CPs, where a concept of distribution measurement (DM) is introduced to quantify the CPs distribution. The whole image is partitioned into contiguous subparts which are corrected by different correction formulae to guarantee the accuracy of each subpart. The extensive experimental results demonstrate that the proposed method significantly outperforms conventional approaches. View Full-Text
Keywords: sensor correction; feature points detection; multi-view simulation; visual difference compensation; piecewise correction sensor correction; feature points detection; multi-view simulation; visual difference compensation; piecewise correction
Show Figures

Figure 1

MDPI and ACS Style

Wang, C.; Liu, X.; Zhao, X.; Wang, Y. An Effective Correction Method for Seriously Oblique Remote Sensing Images Based on Multi-View Simulation and a Piecewise Model. Sensors 2016, 16, 1725.

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.

Article Access Map by Country/Region

1
Back to TopTop