Laboratory geometric calibration of areal digital aerial camera

Yuan, F.; Qi, Weijun; Fang, Aiping

doi:10.1088/1755-1315/17/1/012196

Cited by 11 publications

(7 citation statements)

References 2 publications

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“…On the basis of the distortion theory of an optical camera and the geometric imaging relationship, a least squares method can be used to calculate the principal distance and the principal point, which can be expressed as [17][18][19][20] : (1) and (2) . The calibration accuracy depends mainly on the positional accuracy of the measured image coordinates (x i ,y i ).…”

Section: Methodsmentioning

confidence: 99%

“…The recorded rotation angle and image coordinates are used to construct an equation that relates each star point to its corresponding location in the image. On the basis of an analysis of camera distortion, the optical camera has its minimum distortion at the location of its principal plane [17][18][19] . A least squares method is used to solve the imaging equations to calculate the principal distance and the location of the principal point.…”

Section: Introductionmentioning

confidence: 99%

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Optical focal plane based on MEMS light lead-in for geometric camera calibration

Liu

2017

Microsyst Nanoeng

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The focal plane of a collimator used for the geometric calibration of an optical camera is a key element in the calibration process. The traditional focal plane of the collimator has only a single aperture light lead-in, resulting in a relatively unreliable calibration accuracy. Here we demonstrate a multi-aperture micro-electro-mechanical system (MEMS) light lead-in device that is located at the optical focal plane of the collimator used to calibrate the geometric distortion in cameras. Without additional volume or power consumption, the random errors of this calibration system are decreased by the multi-image matrix. With this new construction and a method for implementing the system, the reliability of high-accuracy calibration of optical cameras is guaranteed.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optical focal plane based on MEMS light lead-in for geometric camera calibration

Liu

2017

Microsyst Nanoeng

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“…We used the on-ground calibration method based on measuring angles to calibrate the reference value of the principal distance and the principal point. The laboratory measuring angle method is widely used in the calibration of IOPs of remote sensing cameras [ 42 , 43 , 44 ]. In this method, an uncalibrated optical camera is placed on a precision turntable to capture the parallel lights of star points emitted by a collimator.…”

Section: Experiments and Analysismentioning

confidence: 99%

High-Accuracy Self-Calibration for Smart, Optical Orbiting Payloads Integrated with Attitude and Position Determination

Xing

Chu

et al. 2016

Sensors

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A high-accuracy space smart payload integrated with attitude and position (SSPIAP) is a new type of optical remote sensor that can autonomously complete image positioning. Inner orientation parameters (IOPs) are a prerequisite for image position determination of an SSPIAP. The calibration of IOPs significantly influences the precision of image position determination of SSPIAPs. IOPs can be precisely measured and calibrated in a laboratory. However, they may drift to a significant degree because of vibrations during complicated launches and on-orbit functioning. Therefore, laboratory calibration methods are not suitable for on-orbit functioning. We propose an on-orbit self-calibration method for SSPIAPs. Our method is based on an auto-collimating dichroic filter combined with a micro-electro-mechanical system (MEMS) point-source focal plane. A MEMS procedure is used to manufacture a light transceiver focal plane, which integrates with point light sources and a complementary metal oxide semiconductor (CMOS) sensor. A dichroic filter is used to fabricate an auto-collimation light reflection element. The dichroic filter and the MEMS point light sources focal plane are integrated into an SSPIAP so it can perform integrated self-calibration. Experiments show that our method can achieve micrometer-level precision, which is good enough to complete real-time calibration without temporal or spatial limitations.

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“…Existing RSC calibration techniques can be classified into two methods. The first technique involves angle measurements in the laboratory [34][35][36], where a single-pixel illumination through collimated light combined with a turntable is used as a calibration target. Recently, multiple pixels illumination in a laboratory was used to replace the single-pixel version for avoiding the turntable vibration influence on RSC calibration [37].…”

Section: Introductionmentioning

confidence: 99%

Efficient camera self-calibration method for remote sensing photogrammetry

Liu

2018

Opt. Express

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Internal parameter calibration of remote sensing cameras (RSCs) is a necessary step in remote sensing photogrammetry. On-orbit camera calibration widely adopts external ground control points (GCPs) to measure its internal parameters. However, accessible and available GCPs are not easy to achieve when cameras work on a satellite platform. In this paper, we propose an efficient camera self-calibration method using a micro-transceiver in conjunction with deep learning. A supervised learning set is produced by the micro-transceiver, where multiple two-dimensional diffraction grids are produced and transformed into multiple auto-collimating sub-beams equivalent to infinite target-point training examples. A deep learning network is used to invert the learnable internal parameters. The micro-transceiver can be easily integrated into the internal structure of RSCs allowing to calibrate them independently on external ground control targets.

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Laboratory geometric calibration of areal digital aerial camera

Cited by 11 publications

References 2 publications

Optical focal plane based on MEMS light lead-in for geometric camera calibration

Optical focal plane based on MEMS light lead-in for geometric camera calibration

High-Accuracy Self-Calibration for Smart, Optical Orbiting Payloads Integrated with Attitude and Position Determination

Efficient camera self-calibration method for remote sensing photogrammetry

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