Geometric Correction Analysis of Highly Distortion of Near Equatorial Satellite Images Using Remote Sensing and Digital Image Processing Techniques

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.

Optimal combination of the correction model and parameters for the precision geometric correction of UAV hyperspectral images

Nowadays,with the rapid development of quantitative remote sensing represented by high-resolution UAV hyperspectral remote sensing observation technology,people have put forward higher requirements for the rapid preprocessing and geometric correction accuracy of hyperspectral images.The optimal geometric correction model and parameter combination of UAV hyperspectral images need to be determined to reduce unnecessary waste of time in the preprocessing and provide high-precision data support for the application of UAV hyperspectral images.In this study,the geometric correction accuracy under various geometric correction models(including affine transformation model,local triangulation model,polynomial model,direct linear transformation model,and rational function model)and resampling methods(including nearest neighbor resampling method,bilinear interpolation resampling method,and cubic convolution resampling method)were analyzed.Furthermore,the distribution,number,and accuracy of control points were analyzed based on the control variable method,and precise ground control points(GCPs)were analyzed.The results showed that the average geometric positioning error of UAV hyperspectral images(at 80 m altitude AGL)without geometric correction was as high as 3.4041 m(about 65 pixels).The optimal geometric correction model and parameter combination of the UAV hyperspectral image(at 80 m altitude AGL)used a local triangulation model,adopted a bilinear interpolation resampling method,and selected 12 edgemiddle distributed GCPs.The correction accuracy could reach 0.0493 m(less than one pixel).This study provides a reference for the geometric correction of UAV hyperspectral images.

Research on HJ-1A/B satellite data automatic geometric precision correction design

Developed independently by China,HJ-1A/B satellites have operated well on-orbit for five years and acquired a large number of high-quality observation data.The realization of the observation data geometric precision correction is of great significance for macro and dynamic ecological environment monitoring.The paper analyzed the parameter characteristics of HJ-1 satellite and geometric features of HJ-1 satellite level 2 data(systematic geo- corrected data).Based on this,the overall HJ- 1 multi- sensor geometric correction flow and charge-coupled device(CCD) automatic geometric precision correction method were designed.Actual operating data showed that the method could achieve good result for automatic geometric precision correction of HJ-1 satellite data,automatic HJ-1 CCD image geometric precision correction accuracy could be achieved within two pixels and automatic matching accuracy between the images of same satellite could be obtained less than one pixel.

Airborne geometry correction method for marine multispectrum data without attitude information

Marine airborne multispectrum scanner （MAMS） onboard the China marine surveillance plane can be used to survey marine environment, resources and disaster and provide the technical support for high-frequency, high-efficiency and high-resolution remote sensing monitoring for the coastal management. MAMS did not have the IMU/POS equipment, so it brought severe challenge for the geometry correction. One airborne geometry correction method is introduced for marine multi- spectrum data without the attitude information. First, it is the coarse geometry correction, which simulates the roll angle and pitch angle of plane according to the ideal flying model; the second step is the precise geometry correction by using the SPOT orthogonal projected data as the reference of registration, based on maximization of alignment metric method. With the validation, relative error of coarse correction is 81.42 m compared with SPOT data, and 11.3 m for precise correction. This method provides the high precision localization information for the oceanic remote sensing and application, and establishes the foundation for monitoring the marine resource and environment.

STUDY ON THE SIGNATURE OF GROUND MOVING TARGET FOR AIRBORNE SQUINT SAR IMAGING

Compared with the side-looking Synthetic Aperture Radar (SAR), the flexible beampointing of squint SAR makes great application value. This paper derives the image signature of the ground moving target after the processing of Range-Doppler (RD) algorithm, the SAR signatures of ground moving targets are analyzed, including the geometry correction, the offsets and defocusing in both range and azimuth direction. Finally, computer simulation results validate its effectiveness. The research results are especially significant for moving targets detection and parameters estimation in squint mode SAR.

Accuracy Analysis on Bundle Adjustment of Remote Sensing Images Based on Dual Quaternion

A bundle adjustment method of remote sensing images based on dual quaternion is presented,which conducted the uniform disposal corresponding location and attitude of sequence images by the dual quaternion.The constraint relationship of image itself and sequence images is constructed to compensate the systematic errors.The feasibility of this method used in bundle adjustment is theoretically tested by the analysis of the structural characteristics of error equation and normal equation based on dual quaternion.Different distributions of control points and stepwise regression analysis are introduced into the experiment for RC30 image.The results show that the adjustment accuracy can achieve 0.2min plane and 1min elevation.As a result,this method provides a new technique for geometric location problem of remote sensing images.

Diffusive Limit of Transport Equation in 3D Convex Domains

Consider neutron transport equations in 3D convex domains with in-flow boundary.We mainly study the asymptotic limits as the Knudsen number→0^(+).Using Hilbert expansion,we rigorously justify that the solution of steady problem converges to that of Laplace’s equation,and the solution of unsteady problem converges to that of heat equation.This is the most difficult case of a long-term project on asymptotic analysis of kinetic equations in bounded domains.The proof relies on a detailed analysis on the boundary layer effect with geometric correction.The upshot of this paper is a novel boundary layer decomposition argument in 3D and L^(2)−L^(2m)−L^(∞)bootstrapping method for time-dependent problem.