Automatic centroid extraction method for noisy star image

Gou, Bin; Chen, Yongmei

doi:10.1049/iet-ipr.2017.0979

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…The target plane is placed in 27 positions and 27 images of laser spots are captured. 27 sets of pixel coordinates of laser spots on the imaging plane [24][25][26] and measurement distances generated from LRF are obtained. The corresponding relationships are fitted by Levenberg-Marquardt method [27][28][29][30].…”

Section: Methodsmentioning

confidence: 99%

Calibration method of 1D laser rangefinder for large-scale 3D measurement under harsh environment

Kang

Wang

2020

IEICE Electron. Express

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Vision measurement has encountered the bottlenecks in capturing and processing the images of laser spots under harsh working environment of strong sunshine and complex background. Breaking through the camera calibration, we propose that the corresponding relationship between pixel coordinates of laser spots, but not the camera, and measurement distances generated from laser rangefinder is directly calibrated under good working environment. The pixel coordinates of laser spots can be obtained from the calibration model and measurement distances during practical measurement. The imaging of laser spots by camera is no longer needed. Experimental results demonstrate that the measurement errors are in the millimeter level within 20 m distance outdoors.

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Section: Methodsmentioning

confidence: 99%

Calibration method of 1D laser rangefinder for large-scale 3D measurement under harsh environment

Kang

Wang

2020

IEICE Electron. Express

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“…The noise case can be addressed by introducing a regularization term into the objective function to avoid noise amplification [33]. Sparse representation is utilized to remove the Poisson-Gaussian mixed noise of the low-resolution star image [34]. However, the methods are complex for obtaining the PSF.…”

Section: Related Workmentioning

confidence: 99%

Blind Deblurring Using Space Target Features

et al. 2019

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The star image suffers inevitably from degradation due to the high-speed motion of the space target and the long exposure time of the camera, therefore the attitude information of the star is hard to accurately obtain. This paper proposes a blind deblurring algorithm that combines shape features of space targets. First, the astronomical image is preprocessed using saliency detection. Then, considering the shape characteristics of space targets, the Minimum Bounding Rectangle (MBR) is introduced to describe the space targets. Next, the parameters of the MBR are used to estimate the point spread function (PSF). Finally, a regularization method is employed to recover the astronomical images. Experimental results on both simulation and real star images demonstrate that the proposed method reduces the error of point spread function estimation and decreases the error rate of identified space targets. At the same time, the accuracy of the star centroid extraction improves 0.2786 on average and the error of the star centroid location extraction reduces 0.059 comparing to the state-of-art method. The proposed method is of great significance for positioning, recognition and attitude determination of space targets. INDEX TERMS Blind deblurring, minimum bounding rectangle, point spread function, star image restoration.

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“…However, the discretization of SPD signals is very detrimental to the CA. The traditional CA suffers from significant systematic and random errors when dealing with the centroid problem of discrete data [19,20]. To solve the error problem and to obtain more robust intermediate variables, a linear interpolation-based CA is proposed in this paper.…”

Section: Introductionmentioning

confidence: 99%

Enhancing precision of chromatic confocal measurement through linear interpolation based centroid algorithm

Lu,

Dai,

Zeng

et al. 2024

Surf. Topogr.: Metrol. Prop.

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In chromatic confocal measurement (CCM), the accuracy and precision of the results rely on the robustness of the spectral power distribution (SPD) signal resolution. However, traditional centroid algorithms struggle with the inherent discretization of the SPD signal, leading to significant measurement errors. To address this issue, a linear interpolation based centroid algorithm is proposed to improve the robustness of the results. In the precision calibration experiment conducted with the in-house developed chromatic confocal sensors, the proposed algorithm demonstrates good robustness. Moreover, it achieves a 50% enhancement in the accuracy of a 4 mm range, improving from 1µm to 0.5µm.

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Automatic centroid extraction method for noisy star image

Cited by 5 publications

References 31 publications

Calibration method of 1D laser rangefinder for large-scale 3D measurement under harsh environment

Calibration method of 1D laser rangefinder for large-scale 3D measurement under harsh environment

Blind Deblurring Using Space Target Features

Enhancing precision of chromatic confocal measurement through linear interpolation based centroid algorithm

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