scholarly journals A Novel Airborne Dual-Antenna InSAR Calibration Method for Backprojection Imaging Model

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 43001-43012
Author(s):  
Xiaoning Hu ◽  
Bingnan Wang ◽  
Maosheng Xiang ◽  
Zhongbin Wang
Keyword(s):  
Calibration Method ◽  
Imaging Model

A Bridging Method between 2D and 3D Cephalometry Using Computed Tomography Synthesized Cephalograms

2013 ◽  
Vol 284-287 ◽  
pp. 1589-1595
Author(s):  
Jing Jing Fang ◽  
Jia Kuang Liu ◽  
Chia Wei Chang ◽  
Yu Cheng Lin
Keyword(s):  
Computed Tomography ◽  
Random Order ◽  
Calibration Method ◽  
Interactive System ◽  
Average Error ◽  
Imaging Method ◽  
X Rays ◽  
X Ray ◽  
Imaging Model ◽  
3D Cephalometry

Traditional cephalograms are X-ray films, which provide either frontal or lateral overlapped perspective medical imaging. Although computed tomography imaging provides more information in 3-dimensional anatomy, the landmarks for cephalometry are located in space which does not carry normal standards in 3-D cephalometry. The CT natural imaging method is different from X-ray in that they respectively use orthogonal and perspective projections. Thus, we cannot apply the statistical normal values gathered from traditional 2D cephometry to 3D cephalometry. This study makes use of calibrated synthesized cephalograms from computed tomography to construct a cephalometry bridge between 2-D and 3-D. In this thesis, we first review the imaging model of a specific X-ray machine (Asahi OrthoStage AUTO IIIN) by a camera calibration method. We then construct a reference system for a virtual head, and synthesize calibrated X-ray cephalograms using the volume rendering algorithm. System accuracy for the synthesis X-ray cephalograms is verified through an interactive corresponding landmark system between 2-D and 3-D. An experimental clinician was invited to manually place 17 landmarks on the X-rays and their corresponding, shuffled in random order. The systematic error, average error, and standard deviation of landmark positions are 0.15 mm, 0.97 mm, and 0.45 mm, respectively. The interactive system bridges the transformation from orthogonal 3-D to perspective 2-D cephalometry.

scholarly journals Accurate binocular stereo underwater measurement method

2019 ◽  
Vol 16 (5) ◽  
pp. 172988141986446
Author(s):  
Xiaojun Wu ◽  
XingCan Tang
Keyword(s):  
Measurement Accuracy ◽  
Calibration Method ◽  
Correction Method ◽  
Image Correction ◽  
Underwater Imaging ◽  
Epipolar Constraint ◽  
Imaging Model ◽  
Internal Parameters ◽  
Extrinsic Parameters ◽  
Binocular Stereo

Light changes its direction of propagation before entering a camera enclosed in a waterproof housing owing to refraction, which means that perspective imaging models in the air cannot be directly used underwater. In this article, we propose an accurate binocular stereo measurement system in an underwater environment. First, based on the physical underwater imaging model without approximation and Tsai’s calibration method, the proposed system is calibrated to acquire the extrinsic parameters, as the internal parameters can be pre-calibrated in air. Then, based on the calibrated camera parameters, an image correction method is proposed to convert the underwater images to air images. Thus, the epipolar constraint can be used to search the matching point directly. The experimental results show that the proposed method in this article can effectively eliminate the effect of refraction in the binocular vision and the measurement accuracy can be compared with the measurement result in air.

Calibration Method Based on General Imaging Model for Micro-Object Measurement System

2016 ◽  
Vol 36 (9) ◽  
pp. 0912003
Author(s):  
孔玮琦 Kong Weiqi ◽  
刘京南 Liu Jingnan ◽  
达飞鹏 Da Feipeng ◽  
饶立 Rao Li
Keyword(s):  
Measurement System ◽  
Calibration Method ◽  
Imaging Model

Rapid Calibration Method for 3D Laser Scanner

2020 ◽  
Vol 14 (2) ◽  
pp. 234-241
Author(s):  
Bin Liu ◽  
Qian Qiao ◽  
Fangfang Han
Keyword(s):  
Laser Scanner ◽  
Vertical Direction ◽  
Calibration Method ◽  
Intrinsic Parameters ◽  
Average Value ◽  
Light Plane ◽  
Imaging Model ◽  
Reference Target ◽  
Camera Intrinsic Parameters ◽  
Rapid Calibration

Background: The 3D laser scanner is a non-contact active-sensing system, which has a number of applications. Many patents have been filed on the technologies for calibrating 3D laser scanner. A precise calibration method is important for measuring the accuracy of the 3D laser scanner. The system model contains three categories of parameters to be calibrated which include the camera intrinsic parameters, distortion coefficients and the light plane parameters. Typically, the calibration process is completed in two steps. Based on Zhang’s method, the calibration of the camera intrinsic parameters and distortion coefficients can be performed. Then, 3D feature points on the light plane should precisely be formed and extracted. Finally, the points are used to calculate the light plane parameters. Methods: In this paper, a rapid calibration method is presented. Without any high precision auxiliary device, only one coplanar reference target is used. By using a group of captured images of the coplanar reference target placed in the field of view arbitrarily, calibration can be performed in one step. Based on the constraint from the planes formed by the target in different directions and the camera imaging model, a large amount of 3D points on the light plane can easily be obtained. The light plane equation in the camera coordinates system can be gathered by executing plane fitting to the 3D points. Results: During the experimental process, the developed 3D laser scanner was calibrated by the proposed method. Then, the measuring accuracy of the system was verified with known distance in vertical direction of 1mm with sequential shifting motion generated by precision translation stage. The average value of the measured distances was found to be 1.010mm. The standard deviation was 0.008mm. Conclusion: Experimental results prove that the proposed calibration method is simple and reliable.

Measurement of Cam Spacing on Assembled Camshaft Based on Improved Fundamental Matrix Calibration

2013 ◽  
Vol 850-851 ◽  
pp. 241-244
Author(s):  
Guan Nan Li ◽  
Qing Chang Tan ◽  
Si Yuan Liu
Keyword(s):  
Fundamental Matrix ◽  
Ccd Camera ◽  
Calibration Method ◽  
Measurement Model ◽  
Pinhole Camera ◽  
Epipolar Line ◽  
Camera Model ◽  
Distortion Model ◽  
Imaging Model ◽  
Measurement Results

Imaging model of double CCD camera based on pinhole camera model and distortion model is introduced, and the fundamental matrix is presented. Distortion model is led into the fundamental matrix calibration. Based on the imaging model of Z. Zhangs calibration method, fundamental matrix is carried out. Pixel coordinate for calibration is modified by cameras interior parameters and distortion coefficients. Base on the imaging model of double CCD camera, measurement model for cam spacing is established. Cam spacing is measured by the feature of cam edge. In experiments, accurate pixel coordinates of model plane were used in calibration. The distance between a point and its corresponding epipolar line was estimated as the error. The measurement results show that the accuracy of proposed method satisfied the monitoring requirements of the axial positioning error of the cam piece.

scholarly journals Proposal of a Geometric Calibration Method Using Sparse Recovery to Remove Linear Array Push-Broom Sensor Bias

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4003 ◽  
Author(s):  
Chen ◽  
Sha ◽  
Yang ◽  
An
Keyword(s):  
Linear Array ◽  
Image Data ◽  
Calibration Method ◽  
Sparse Recovery ◽  
Sensor Calibration ◽  
Recovery Method ◽  
Geometric Calibration ◽  
Imaging Model ◽  
Short Period ◽  
Earth Observation Satellites

The rational function model (RFM) is widely used in the most advanced Earth observation satellites, replacing the rigorous imaging model. The RFM method achieves the desired calibration performance when image distortion is caused by long-period errors. However, the calibration performance of the RFM method deteriorates when short-period errors—such as attitude jitter error—are present, and the insufficient and uneven ground control points (GCPs) can also lower the calibration precision of the RFM method. Hence, this paper proposes a geometric calibration method using sparse recovery to remove the linear array push-broom sensor bias. The most important issue regarding this method is that the errors related to the imaging process are approximated to the equivalent bias angles. By using the sparse recovery method, the number and distribution of GCPs needed are greatly reduced. Meanwhile, the proposed method effectively removes short-period errors by recognizing periodic wavy patterns in the first step of the process. The image data from Earth Observing 1 (EO-1) and the Advanced Land Observing Satellite (ALOS) are used as experimental data for the verification of the calibration performance of the proposed method. The experimental results indicate that the proposed method is effective for the sensor calibration of both satellites.

scholarly journals Calibration Method of Orthogonally Splitting Imaging Pose Sensor Based on General Imaging Model

2018 ◽  
Vol 8 (8) ◽  
pp. 1399 ◽  
Author(s):  
Na Zhao ◽  
Changku Sun ◽  
Peng Wang
Keyword(s):  
Coordinate System ◽  
Radial Basis Function ◽  
Basis Function ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Distortion Correction ◽  
Imaging Model ◽  
The World ◽  
Radial Basis ◽  
Pinhole Imaging

Orthogonally splitting imaging pose sensor is a new sensor with two orthogonal line array charge coupled devices (CCDs). Owing to its special structure, there are distortion correction and imaging model problems during the calibration procedure. This paper proposes a calibration method based on the general imaging model to solve these problems. The method introduces Plücker Coordinate to describe the mapping relation between the image coordinate system and the world coordinate system. This paper solves the mapping relation with radial basis function interpolation and adaptively selecting control points with Kmeans clustering method to improve the fitting accuracy. This paper determines the appropriate radial basis function and its shape parameter by experiments. And these parameters are used to calibrate the orthogonally splitting imaging pose sensor. According to the calibration result, the root mean square (RMS)of calibration dataset and the RMS of test dataset are 0.048 mm and 0.049 mm. A comparative experiment is conducted between the pinhole imaging model and the general imaging model. Experimental results show that the calibration method based on general imaging model applies to the orthogonally splitting imaging pose sensor. The calibration method requires only one image corresponding to the target in the world coordinates and distortion correction is not required to be taken into account. Compared with the calibration method based on the pinhole imaging model, the calibration procedure based on the general imaging model is easier and accuracy is greater.

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