Full‐field deformation measurement by videogrammetry using self‐adaptive window matching

Gao, Su; Tong, Xiaohua; Chen, Peng; Ye, Zhen; Hu, Ouling; Wang, Benkang; Zhao, Cheng; Liu, Shijie; Xie, Huan; Jin, Yanmin; Xu, Xiong; Wei, Chao

doi:10.1111/phor.12268

Cited by 8 publications

(6 citation statements)

References 69 publications

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“…The patch size will not affect the presence of systematic errors [28]. Several adaptive strategies for adjusting patch size have been developed based on local structural statistics [14,76] or hierarchical variation [34,77]. The performance of various matching algorithms with varying patch sizes or adaptive strategies will be investigated in future work.…”

Section: Summary and Discussionmentioning

confidence: 99%

“…In addition, the quality of the sensor and geometric processing can be assessed according to the displacement fields, reflecting the sensor distortions [9], the attitude variations [10], the inconsistencies after correction or stitching [11], and other information. Therefore, dense image matching is an indispensable study area and has been broadly used in a variety of applications in the remote sensing community [12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

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Area-Based Dense Image Matching with Subpixel Accuracy for Remote Sensing Applications: Practical Analysis and Comparative Study

Xu²,

Chen

et al. 2020

Remote Sensing

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Dense image matching is a crucial step in many image processing tasks. Subpixel accuracy and fractional measurement are commonly pursued, considering the image resolution and application requirement, especially in the field of remote sensing. In this study, we conducted a practical analysis and comparative study on area-based dense image matching with subpixel accuracy for remote sensing applications, with a specific focus on the subpixel capability and robustness. Twelve representative matching algorithms with two types of correlation-based similarity measures and seven types of subpixel methods were selected. The existing matching algorithms were compared and evaluated in a simulated experiment using synthetic image pairs with varying amounts of aliasing and two real applications of attitude jitter detection and disparity estimation. The experimental results indicate that there are two types of systematic errors: displacement-dependent errors, depending on the fractional values of displacement, and displacement-independent errors represented as unexpected wave artifacts in this study. In addition, the strengths and limitations of different matching algorithms on the robustness to these two types of systematic errors were investigated and discussed.

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Section: Summary and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Area-Based Dense Image Matching with Subpixel Accuracy for Remote Sensing Applications: Practical Analysis and Comparative Study

Xu²,

Chen

et al. 2020

Remote Sensing

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“…However, the requirements of template size to obtain valid results are diverse for different grid positions, since a small template size is adequate for certain positions. Therefore, an adaptive strategy for adjusting template size based on local structural statistics is highlighted [62,64]. Future work will explore the combination of the presented LUGC method with adaptive template strategies to ensure both the correctness in low textured areas and the locality in areas with strong velocity gradient.…”

Section: Comparison With Other Matching Methodsmentioning

confidence: 99%

Glacier Surface Motion Estimation from SAR Intensity Images Based on Subpixel Gradient Correlation

et al. 2020

Sensors

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With the current extensive availability of synthetic-aperture radar (SAR) datasets with high temporal (e.g., a repeat cycle of a few or a dozen days) and spatial resolution (e.g., in the order of ∼1 m), radar remote sensing possesses an increasing potential for the monitoring of glacier surface motion thanks to the nearly weather and time-independent advantages. This paper proposes a robust subpixel frequency-based image correlation method for dense matching and integrates the improved matching into a workflow of glacier surface motion estimation using SAR intensity images with specific pre-processing and post-processing steps. The proposed matching method combines complex edge maps and local upsampling in the frequency domain for subpixel intensity tracking, which ensure the accuracy and robustness of glacier surface motion estimation. Experiments were carried out with TerraSAR-X and Sentinel-1 images covering two glacier areas in pole and alpine regions. The results of the monitoring and investigation of glacier motion validate the feasibility and reliability of the presented motion estimation method based on subpixel gradient correlation. The comparative results using both simulated and real SAR data indicate that the proposed matching method outperforms commonly used correlation-based matching methods in terms of matching accuracy and the ability to obtain correct matches.

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“…In order to achieve the purpose of on-site computing, the parallel computing is necessary to improve the computing efficiency (Gao et al, 2019). In our measurement system, each high-speed camera is equipped with a minicomputer, and a principal controller is used to manage these minicomputers.…”

Section: Distributed Parallel Computingmentioning

confidence: 99%

Development of a High-Speed Videogrammetric Measurement System With Application in Large-Scale Shaking Table Test

Gao

Wei

et al. 2019

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> The high-speed videogrammetric measurement system, which provides a convenient way to capture three-dimensional (3D) dynamic response of moving objects, has been widely used in various applications due to its remarkable advantages including non-contact, flexibility and high precision. This paper presents a distributed high-speed videogrammetric measurement system suitable for monitoring of large-scale structures. The overall framework consists of hardware and software two parts, namely observation network construction and data processing. The core component of the observation network is high-speed cameras to provide multiview image sequences. The data processing part automatically obtains the 3D structural deformations of the key points from the captured image sequences. A distributed parallel processing framework is adopted to speed up the image sequence processing. An empirical experiment was conducted to measure the dynamics of a double-tube five-layer building structure on the shaking table using the presented videogrammetric measurement system. Compared with the high-accuracy total station measurement, the presented system can achieve a sub-millimeter level of coordinates discrepancy. The 3D deformation results demonstrate the potential of the non-contact high-speed videogrammetric measurement system in dynamic monitoring of large-scale shake table tests.</p>

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Full‐field deformation measurement by videogrammetry using self‐adaptive window matching

Cited by 8 publications

References 69 publications

Area-Based Dense Image Matching with Subpixel Accuracy for Remote Sensing Applications: Practical Analysis and Comparative Study

Area-Based Dense Image Matching with Subpixel Accuracy for Remote Sensing Applications: Practical Analysis and Comparative Study

Glacier Surface Motion Estimation from SAR Intensity Images Based on Subpixel Gradient Correlation

Development of a High-Speed Videogrammetric Measurement System With Application in Large-Scale Shaking Table Test

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