Author(s)

Hayder Dibs¹, Shattri Mansor², Noordin Ahmad³, Nadhir Al-Ansari^4*

¹Water Resources Management Engineering Department, Faculty of Water Resources Engineering, Al-Qasim Green University, Babylon, Iraq.
²Faculty of Engineering, Geospatial Information Science Research Centre, Department of Civil Engineering, University Putra Malaysia, Selangor, Malaysia.
³National Space Agency Malaysia (ANGKASA), Kementerian Sains, Teknologi dan Inovasi, Pusat Angkasa Negara, Selangor, Malaysia.
⁴Department of Civil Environmental and Natural Resources Engineering, Lulea University of Technology, Lulea, Sweden.

The Near-equatorial orbit (NEqO) satellite represents a new generation of optical satellite images characterized by nonlinear distortion when captured. Conventional modeling techniques are insufficient to overcome the geometric distortion in these satellite images. This study proposes a new methodology for overcoming the geometric distortion of the NEqO images. The data used are obtained from RazakSAT and SPOT-5 satellite images in Malaysia. The method starts with applying the RI-SIFT algorithm to extract control points (CPs) automatically. These CPs are used to solve for the transformation parameters of the geometric correction model by applying spline transformations. The result is verified through statistical comparison: 1) geometric correction on the RazakSAT image is performed with Spot satellite image with using first-order polynomial trans-formation. 2) Then calculate the root mean square error (RMSE). 3) Compare the calculated RMSE with that obtained from the first step with that of the proposed method. The RMSE value of the geometric corrections using the proposed method was 7.08 × 10⁻⁹ m. The proposed method provides promising results.

Near Equatorial Satellite, Geometric Correction, Automatic Extraction of CPs, RI-SIFT, Sum of Absolute Difference

Dibs, H. , Mansor, S. , Ahmad, N. and Al-Ansari, N. (2022) Geometric Correction Analysis of Highly Distortion of Near Equatorial Satellite Images Using Remote Sensing and Digital Image Processing Techniques. Engineering, 14, 1-8. doi: 10.4236/eng.2022.141001.