Coarse-to-Fine Image Matching-Based Footprint Camera Calibration of the GF-7 Satellite

The GF-7 satellite is China’s first high-resolution stereo mapping satellite that reaches sub-meter resolution, equipped with new-type payloads, such as an area array footprint camera that can achieve synchronization acquisition of laser spots. When the satellite is in space, the variation of camera parameters may occur due to launch vibration and environmental changes, and on-orbit geometric calibration thereby must be made. Coupled with the data from the GF-7 satellite, this paper constructs a geometric imaging model of the area array footprint camera based on the two-dimensional direction angle, and proposes a coarse-to-fine “LPM-SIFT + Phase correlation” matching strategy for the automatic extraction of calibration control points. The single-image calibration experiment shows that the on-orbit geometric calibration model of the footprint camera constructed in this paper is correct and effective. The matching method proposed is used to register the footprint images with the DOM (Digital Orthophoto Map) reference data to obtain dense control points. Compared with the calibration result using a small number of manually collected control points, the root mean square error (RMSE) of the residual of the control points is improved from half a pixel to 1/3, and the RMSE of the same orbit checkpoints in the image space is improved from 1 pixel to 0.7. It can be concluded that using the coarse-to-fine image matching method proposed in this paper to extract control points can significantly improve the on-orbit calibration accuracy of the footprint camera on the GF-7 satellite.

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GEOMETRIC CALIBRATION OF ZIYUAN-3 THREE-LINE CAMERAS COMBINING GROUND CONTROL POINTS AND LINES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b1-163-2016 ◽

2016 ◽

Vol XLI-B1 ◽

pp. 163-168

Author(s):

Jinshan Cao ◽

Xiuxiao Yuan ◽

Jianya Gong

Keyword(s):

Ground Control ◽

Calibration Model ◽

Control Points ◽

Charge Coupled Device ◽

Geometric Calibration ◽

Ground Control Points ◽

The Look ◽

Ccd Detectors ◽

True Values ◽

Better Than

Due to the large biases between the laboratory-calibrated values of the orientation parameters and their in-orbit true values, the initial direct georeferencing accuracy of the Ziyuan-3 (ZY-3) three-line camera (TLC) images can only reach the kilometre level. In this paper, a point-based geometric calibration model of the ZY-3 TLCs is firstly established by using the collinearity constraint, and then a line-based geometric calibration model is established by using the coplanarity constraint. With the help of both the point-based and the line-based models, a feasible in-orbit geometric calibration approach for the ZY-3 TLCs combining ground control points (GCPs) and ground control lines (GCLs) is presented. Experimental results show that like GCPs, GCLs can also provide effective ground control information for the geometric calibration of the ZY-3 TLCs. The calibration accuracy of the look angles of charge-coupled device (CCD) detectors achieved by using the presented approach reached up to about 1.0''. After the geometric calibration, the direct georeferencing accuracy of the ZY-3 TLC images without ground controls was significantly improved from the kilometre level to better than 11 m in planimetry and 9 m in height. A more satisfactory georeferencing accuracy of better than 3.5 m in planimetry and 3.0 m in height was achieved after the block adjustment with four GCPs.

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On-Orbit Geometric Calibration from the Relative Motion of Stars for Geostationary Cameras

Sensors ◽

10.3390/s21196668 ◽

2021 ◽

Vol 21 (19) ◽

pp. 6668

Author(s):

Linyi Jiang ◽

Xiaoyan Li ◽

Liyuan Li ◽

Lin Yang ◽

Lan Yang ◽

...

Keyword(s):

Relative Motion ◽

Calibration Method ◽

System Structure ◽

Calibration Model ◽

Control Points ◽

Penetration Process ◽

Geometric Calibration ◽

Positioning Errors ◽

Ground Control Points ◽

Motion Transformation

Affected by the vibrations and thermal shocks during launch and the orbit penetration process, the geometric positioning model of the remote sensing cameras measured on the ground will generate a displacement, affecting the geometric accuracy of imagery and requiring recalibration. Conventional methods adopt the ground control points (GCPs) or stars as references for on-orbit geometric calibration. However, inescapable cloud coverage and discontented extraction algorithms make it extremely difficult to collect sufficient high-precision GCPs for modifying the misalignment of the camera, especially for geostationary satellites. Additionally, the number of the observed stars is very likely to be inadequate for calibrating the relative installations of the camera. In terms of the problems above, we propose a novel on-orbit geometric calibration method using the relative motion of stars for geostationary cameras. First, a geometric calibration model is constructed based on the optical system structure. Then, we analyze the relative motion transformation of the observed stars. The stellar trajectory and the auxiliary ephemeris are used to obtain the corresponding object vector for correcting the associated calibration parameters iteratively. Experimental results evaluated on the data of a geostationary experiment satellite demonstrate that the positioning errors corrected by this proposed method can be within ±2.35 pixels. This approach is able to effectively calibrate the camera and improve the positioning accuracy, which avoids the influence of cloud cover and overcomes the great dependence on the number of the observed stars.

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Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images

Remote Sensing ◽

10.3390/rs13173535 ◽

2021 ◽

Vol 13 (17) ◽

pp. 3535

Author(s):

Zhongli Fan ◽

Li Zhang ◽

Yuxuan Liu ◽

Qingdong Wang ◽

Sisi Zlatanova

Keyword(s):

Satellite Imagery ◽

Image Matching ◽

Satellite Images ◽

Three Dimensional ◽

Phase Correlation ◽

Feature Descriptor ◽

Matching Method ◽

Reference Images ◽

Sar Data ◽

Optical Satellite Images

Accurate geopositioning of optical satellite imagery is a fundamental step for many photogrammetric applications. Considering the imaging principle and data processing manner, SAR satellites can achieve high geopositioning accuracy. Therefore, SAR data can be a reliable source for providing control information in the orientation of optical satellite images. This paper proposes a practical solution for an accurate orientation of optical satellite images using SAR reference images to take advantage of the merits of SAR data. Firstly, we propose an accurate and robust multimodal image matching method to match the SAR and optical satellite images. This approach includes the development of a new structural-based multimodal applicable feature descriptor that employs angle-weighted oriented gradients (AWOGs) and the utilization of a three-dimensional phase correlation similarity measure. Secondly, we put forward a general optical satellite imagery orientation framework based on multiple SAR reference images, which uses the matches of the SAR and optical satellite images as virtual control points. A large number of experiments not only demonstrate the superiority of the proposed matching method compared to the state-of-the-art methods but also prove the effectiveness of the proposed orientation framework. In particular, the matching performance is improved by about 17% compared with the latest multimodal image matching method, namely, CFOG, and the geopositioning accuracy of optical satellite images is improved, from more than 200 to around 8 m.

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A Subpixel Matching Method for Stereovision of Narrow Baseline Remotely Sensed Imagery

Mathematical Problems in Engineering ◽

10.1155/2017/7901692 ◽

2017 ◽

Vol 2017 ◽

pp. 1-14 ◽

Cited By ~ 6

Author(s):

Ning Ma ◽

Peng-fei Sun ◽

Yu-bo Men ◽

Chao-guang Men ◽

Xiang Li

Keyword(s):

Image Matching ◽

Remotely Sensed ◽

Phase Correlation ◽

Disparity Estimation ◽

Matching Method ◽

Remotely Sensed Imagery ◽

Novel Variant ◽

Remotely Sensed Images ◽

Relationship Of ◽

The Relationship

In this paper, an accurate and efficient image matching method based on phase correlation is proposed to estimate disparity with subpixel precision, which is used for the stereovision of narrow baseline remotely sensed images. The multistep strategy is adopted in our technical frame; thus the disparity estimation is divided into two steps: integer-pixel prematching and subpixel matching. Firstly, integer-pixel disparity is estimated by employing a cross-based local matching method. Then the relationship of corresponding points is established under the guidance of integer-pixel disparity. The subimages are extracted through selecting the corresponding points as the center. Finally, the subpixel disparity is obtained by matching the subimages utilizing a novel variant of phase correlation approach. The experiment results show that the proposed method can match different kinds of large-sized narrow baseline remotely sensed images and estimate disparity with subpixel precision automatically.

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GEOMETRIC CALIBRATION OF ZIYUAN-3 THREE-LINE CAMERAS COMBINING GROUND CONTROL POINTS AND LINES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b1-163-2016 ◽

2016 ◽

Vol XLI-B1 ◽

pp. 163-168

Author(s):

Jinshan Cao ◽

Xiuxiao Yuan ◽

Jianya Gong

Keyword(s):

Ground Control ◽

Calibration Model ◽

Control Points ◽

Charge Coupled Device ◽

Geometric Calibration ◽

Ground Control Points ◽

The Look ◽

Ccd Detectors ◽

True Values ◽

Better Than

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ILLUMINATION INVARIANT CHANGE DETECTION (IICD): FROM EARTH TO MARS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-1673-2018 ◽

2018 ◽

Vol XLII-3 ◽

pp. 1673-1680

Author(s):

X. Wan ◽

J. Liu ◽

M. Qin ◽

S. Y. Li

Keyword(s):

Change Detection ◽

Image Matching ◽

Large Scale ◽

Satellite Images ◽

Environmental Changes ◽

Phase Correlation ◽

Small Object ◽

Illumination Variation ◽

Illumination Invariant ◽

Multi Temporal

Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching.<br> The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.

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