[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Contact us::
Site Facilities::
Search in website

Advanced Search
Receive site information
Enter your Email in the following box to receive the site news and information.
:: Volume 4, Issue 2 (9-2016) ::
jgit 2016, 4(2): 47-64 Back to browse issues page
Determining regularization parameter in high resolution images georefrencing with Rational Functions
Amir Zafari * , Alireza Amiri simkooei , Mehdi Momeni
Isfahan University
Abstract:   (3852 Views)

High-resolution satellite images are extensively used in different fields. Geo-referencing process, as innate part of extraction of topographic terrains through these images, has been studied in many researches. In geo-referencing of satellite images, different models can be used, but rational functions are the most suitable options. Determining co-efficiency of rational functions is ill-condition problem, so to solve this problem Tikhonov regularization method has been used. In such regularization method, regularization selection parameter is very important. In present study, this parameter was calculated through two methods including: minimizing root mean square of errors (RMSE) and the L-curve for determining co-efficiency of rational functions. Then these two methods have been used in least standard squares of parametric model. Also combined model has been used to determine co-efficiency of rational functions in geo-referencing process. These calculations have been done for two different control-points groups with various numbers and accuracies. Using these two models (parametric and combined), regularization parameter has been calculated through L-curve and root mean square of error methods by 55 points. The results show that the root mean square errors and L-curve methods in parametric model led to accuracy of 4.45 and 5.40 pixels, respectively. Also in the combined model, root mean square errors and L-curve methods showed accuracy of 3.42 and 5.10 pixels, respectively. Above calculations were repeated with 120 points. This time, results show approximately same accuracies for both root mean square errors and L-curve methods.

Keywords: High-Resolution Satellite Images, Rational Function, Ill-ondition Problem, regularization, L-curve.
Full-Text [PDF 1095 kb]   (1288 Downloads)    
Type of Study: Research | Subject: Geodesy
Received: 2015/09/30 | Accepted: 2016/08/10 | Published: 2017/01/15
Send email to the article author

XML   Persian Abstract   Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Zafari A, Amiri simkooei A, Momeni M. Determining regularization parameter in high resolution images georefrencing with Rational Functions. jgit 2016; 4 (2) :47-64
URL: http://jgit.kntu.ac.ir/article-1-140-en.html

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 4, Issue 2 (9-2016) Back to browse issues page
نشریه علمی-پژوهشی مهندسی فناوری اطلاعات مکانی Engineering Journal of Geospatial Information Technology
Persian site map - English site map - Created in 0.04 seconds with 36 queries by YEKTAWEB 4645