Estimation and analysis of along-track attitude jitter of ZiYuan-3 satellite based on relative residuals of tri-band multispectral imagery

Ye, Zhen; Xu, Yangsheng; Tong, Xiaohua; Zheng, Shouzhu; Zhang, Han; Xie, Huan; Stilla, Uwe

doi:10.1016/j.isprsjprs.2019.10.012

Cited by 15 publications

(16 citation statements)

References 30 publications

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“…In contrast, the displacement maps of other matching algorithms were visually similar to each other. From the results in Figure 10, it was observed that the stripe patterns of y-direction displacement maps were less apparent since the amplitude of attitude jitter of pitch angle is relatively small, and the jitter distortion is contaminated by topographic information due to the short baseline [69]. The displacement maps obtained by Centroid-NCC and SimiFit-SGM were noisy, and the results from the SimiFit-NCC, SimiFit-SGM, LSM, and Upsampling seemed to appear some artifacts.…”

Section: Results Of Real Application Onementioning

confidence: 99%

“…This subtle attitude variation can be transmitted to imaging sensors and result in image distortions. Attitude jitter can thus be effectively detected and estimated from short-time asynchronous image data [69]. In this process, the accuracy of dense image matching to retrieve the image distortions caused by attitude jitter is crucial.…”

Section: Real Application One: Attitude Jitter Detectionmentioning

confidence: 99%

See 1 more Smart Citation

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: Results Of Real Application Onementioning

confidence: 99%

Section: Real Application One: Attitude Jitter Detectionmentioning

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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“…The filtered disparity maps are further compensated with affine model to attenuate the relative linear bias resulted from other influence factors except jitter (Ye et al, 2019). Finally, the relative disparity ( ) g t can be obtained by averaging the disparity map at each line with three-sigma limits, and is then smoothed by a low-pass function.…”

Section: Jitter Detectionmentioning

confidence: 99%

Influence of Image Interpolation on Imagery-Based Detection and Compensation of Satellite Jitter

Xu²,

Wei

et al. 2020

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

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Abstract. Satellite jitter is a common and complicated phenomenon that degrades the geometric quality of high-resolution satellite images. Imagery-based detection and compensation of satellite jitter have recently been widely concerned. However, most of the existing studies overlook the issue of image interpolation in this topic involving subpixel measurements. In this study, the influence of image interpolation on imagery-based detection and compensation of satellite jitter is investigated. Four different interpolators are separately applied in dense least squares matching for jitter detection based on parallax observation and in intensity resampling for jitter distortion compensation. Experiments were carried out using ZiYuan-3 dataset to compare and analyze the results in the case of different image interpolation. The experimental results demonstrate the influence of image interpolation on imagery-based jitter processing. Inferior interpolators can induce pixel locking effect in subpixel matching and position-dependent systematic bias after image correction, which deteriorate the performance of jitter detection and compensation. To ensure the reliability, sophisticated interpolation algorithms with smaller phase errors are preferable in imagery-based jitter detection and compensation.

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“…The attitude jitter detection method based on the parallax observation configuration were proposed, which estimated attitude jitter from the relative registration errors of adjacent bands of ASTER short-wave infrared sensor (Teshima, Iwasaki, 2008). Similar methods were used for detecting jitter of many satellites, such as HiRISE, Mapping Satellite-1, ZiYuan-1, ZiYuan-3 (Kirk et al, 2008;Sun et al,2015;Jiang et al,2014;Tong et al, 2015aTong et al, , 2015bTong et al, , 2015cTong et al, , 2015dTong et al, , 2017Tong et al, , 2019Wang et al,2016;Pan et al, 2017;Zhu et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…It is generally believed that the matching window size affecting the jitter frequency detection. The maximum detectable frequency of ZiYuan-3 multispectral imagery can be up to , where the multispectral scanning rate sr is approximately 1250 Hz, the size of correlation window w is considered since the window is equivalent to low-pass filtering and is set as 16) (Ye et al, 2019). However, quantitative experimental analysis of matching window size on jitter detection has rarely been investigated.…”

Section: Introductionmentioning

confidence: 99%

Effect of Image Matching Window Size on Satellite Jitter Frequency Detection

Zhang

Liu

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Satellite attitude jitter is a common and complex phenomenon for high-resolution satellites and it is detectable by multi-temporal image matching. This paper analyses the effect of image matching window size on jitter frequency detection. First, two simulation images with a given short time lag and line scanning frequency affected by a modelled jitter are generated based on the principle of dynamic imaging model. Then, the relative image distortions are obtained by dense image matching with different matching window size and the frequency is estimated through spectrum analysis of the obtained image distortions. The experimental results demonstrated the feasibility and reliability of high frequency jitter detection based on dense image matching, and the results indicated that the maximum detectable frequency is almost not affected by the change of image matching window size, which provided useful demonstration of image-based satellite jitter detection capacity.

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Estimation and analysis of along-track attitude jitter of ZiYuan-3 satellite based on relative residuals of tri-band multispectral imagery

Cited by 15 publications

References 30 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

Influence of Image Interpolation on Imagery-Based Detection and Compensation of Satellite Jitter

Effect of Image Matching Window Size on Satellite Jitter Frequency Detection

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