HJ-1A/B CCD IMAGERY Geometric Distortions and

Precise Geometric Correction Accuracy Analysis

Changmiao Hu, Ping Tang Email: akaishi@163.com, tangping@irsa.ac.cn

Institute of Remote Sensing ApplicationsChinese Academy of Sciences

Chao Yang, Beijing 100101

Content

1. Brief Introduction of HJ-1 A /B satellites

2. Geometric distortion analysis of HJ-1 CCD data

3. Comparison of different geometric correction models for HJ-1 CCD data

4. Conclusion

HJ-1 A and HJ-1 B satellites were launched on Sept. 5, 2008 by a Long March-2C in Taiyuan Satellite Launch Center, Shanxi Province, China.

HJ-1 A and HJ-1 B satellites together provide observation revisit cycle in 48 hours. The overall objective is to establish an operational earth observing system for environmental protection and disaster monitoring.

1. Brief Introduction of HJ-1 A /B satellites

Note: HJ is the abbreviation for Chinese pinyin “Huan Jing” - means “environment”. HJ-1 (Huan Jing-1: Environmental Protection & Disaster Monitoring Constellation)

HJ-1A is an optical satellite with two CCD cameras and an infrared camera; HJ-1B is also an optical satellite with two CCD cameras and a hyperspectral camera. The two pushbroom CCD cameras form a WVC ( Wide View CCD Cameras)

HJ-1 A/B WVC Landsat TM

CCD 1

31°31°

30° 30°

CCD 2

360km360km

TM185km

11°

HJ-1 A/B CCD Landsat TM

Spatial resolution 30m (in nadir) 30m

Swath width 360km (CCD*2≥700km) 185km

Aspect angle 31° 5°

Revisit period 2 days 16 days

Spectral resolution Band 1:(0.43-0.52µm)Band 2:(0.52-0.60µm)Band 3:(0.63-0.69µm)Band 4:(0.76-0.90µm)

Band 1:(0.45-0.52µm)Band 2:(0.52-0.60µm)Band 3:(0.63-0.69µm)Band 4:(0.76-0.90µm)Band 5:(1.55-1.75µm)Band 7:(2.08-2.35µm)

Technical parameters for multispectral CCD sensors of HJ and Landsat TM

2. Geometric distortion analysis of HJ-1 CCD data

Test data Eight images from different satellites and CCD, which are after

systematic geometric correction processing and have map projection information. The details of systematic geometric correction are unknown.

No. Satellite Sensor Path Row Date ID

No.1 HJ-1A CCD1 3 72 2009-12-22 0000225232

No.2 HJ-1A CCD1 4 72 2009-10-17 0000186716

No.3 HJ-1A CCD2 1 72 2009-12-25 0000226660

No.4 HJ-1A CCD2 1 72 2009-12-25 0000226699

No.5 HJ-1B CCD1 4 69 2009-10-15 0000186267

No.6 HJ-1B CCD1 3 72 2009-11-19 0000204443

No.7 HJ-1B CCD2 1 72 2009-11-22 0000205299

No.8 HJ-1B CCD2 2 72 2009-10-22 0000189452

These images are from Satellite Environment Center (Ministry of Environmental Protection).

Eight images are displayed as a false-color composite (RGB-B432) after applying an identical linear stretch.

No.1 No.2 No.3 No.4

No.5 No.6 No.7 No.8

Methods for distortion analysis

The automatic image matching method is adopted to obtain image control points, where HJ data as the original images, the Landsat TM GLCF images as reference images.

Drawing the displacement vectors of control points;

Calculate root mean squared error (RMSE) and analysis.

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Image control points selection

About 1000 image control points evenly distributed are extracted by image matching in each test image. All the image control points are checked and the error matched points are deleted. Then 50, 200, and 1000 nearly even distributed control points are selected out, and some points are used as check points.

Over 1000 points 200 points 50 points

Displacement vectors for eight images, 50 points

There are both global system distortions of oriented shift and local distortions exist within the eight images. These distortions are quite different and not regular.

RMSE No.1 No.2 No.3 No.4 No.5 No.6 No.7 No.8

x 257.0 379.7 356.1 365.7 348.7 643.1 448.8 800.6

y 1004.5 981.16 741.9 760.9 888.9 300.2 246.4 559.3

total 1037.1 1052.0 822.9 844.3 954.9 709.7 512.0 976.6

RMSE of eight images, geographical coordinates (meters), 50 points

The geometric precision of eight images are low. The total RMSE is from 500 to 1000 meters.

After systematic geometric correction processing, the HJ-1 A/B CCD images are still with low geometric precision and need to be geo-corrected in high precision.

3. Comparison of different geometric correction models for HJ-1 CCD data

Three mathematical models are tested :

1) Polynomial model (Global method)

2) Thin plate splines (Global method with local characteristics)

3) Finite element method (Local method)

Polynomial model

: the image coordinates. : the ground coordinates. : the coefficients, which always determined

by least squares regression analysis.

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Polynomial model is a global method. It always be used in small size image.

Degrees/points No.1 No.2 No.3 No.4 No.5 No.6 No.7 No.8

3 Degrees/40 control 7.179 8.245 8.876 9.338 11.22 9.205 7.197 11.27

3 Degrees/10 check 12.03 6.137 5.890 15.95 9.275 8.721 10.26 12.22

3 Degrees/180 control 7.551 9.213 8.161 10.06 9.761 8.517 8.330 12.57

3 Degrees/20 check 6.413 7.731 6.450 9.388 11.43 7.232 10.79 12.85

5 Degrees/40 control 5.238 6.072 6.229 7.571 9.479 6.854 6.023 7.197

5 Degrees/10 check 13.55 5.392 6.544 15.51 9.163 12.12 10.77 14.67

5 Degrees/180 control 6.721 8.568 7.454 9.708 9.089 7.753 7.704 11.63

5 Degrees/20 check 6.519 6.978 6.291 9.668 10.36 8.171 9.845 12.36

RMSE in pixels. The control points are used for solving model. Both control points and check points are used for accuracy analysis.

Polynomial model

The polynomial model is difficult to be used in correcting the eight images. The errors always larger than five pixels.

Thin plate splines (TPS)

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TPS is a global method, and also with local characteristics. It interpolates the control point rigorously, hence there are no residuals for the control points.

RMSE in pixels, for check points.

Points: Check/Control

No.1 No.2 No.3 No.4 No.5 No.6 No.7 No.8

10/40 13.80 11.13 8.342 19.12 9.800 10.06 11.70 13.95

20/180 5.816 4.128 5.850 6.011 9.572 9.621 8.437 18.17

100/1000 2.465 12.15 94.54 5.241 7.668 7.334 118.8 6.994

120/1000 1.779 6.948 137.3 4.949 2.300 1.500 40.39 24.48

Thin plate splines (TPS)

When the number of control points is 40 or 180, the errors in check points are always larger than 5 pixels.

When the number of control points is over 1000, the calculation results of TPS are not stable.

Finite element method

Firstly construct Delaunay tessellation using the control points; Then calculate the transformation parameters. In a Delaunay

triangulation, use a 1st-order polynomial algorithm to do precise geometric correction.

Finally, interpolates the intensity of each pixel in the transformed file.

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References: Jonathan Richard Shewchuk. “Triangle” A Two-Dimensional Quality Mesh Generator and Delaunay Triangulator. http://www.cs.cmu.edu/~quake/triangle.html

Finite element method is a local method, local variations do not directly affect the registration of the entire image.

Finite element method RMSE in pixels, for check points.

Points:Check/Control

No.1 No.2 No.3 No.4 No.5 No.6 No.7 No.8

10/40 13.28 4.636 7.513 19.12 9.897 9.340 10.19 13.09

20/180 5.900 9.453 5.369 10.74 9.638 9.510 7.915 20.12

100/1000 1.565 1.852 2.410 2.069 1.226 1.236 1.772 1.587

120/1000 1.461 2.817 2.121 2.243 1.493 1.338 1.726 1.814

Finite element method can meet the requirement of precise geometric correction for HJ-1A/B CCD imagery if the number of evenly distributed control points are over 1000.

4.Conclusion

Both global system distortions and complex local distortions exist within the HJ-1A/B CCD images;

Polynomial model gets the worst accuracy;

Thin plate splines significantly improve accuracy, but with the

increase in the number of control points, the calculation is not stable.

Finite element method is recommended to be used of precise geometric correction for HJ-1A/B CCD imagery if the control points are enough and evenly distributed. Besides it is a local method, and possesses the advantages of rapidity and stability.

Changmiao Hu, Ping Tang Email: akaishi@163.com, tangping@irsa.ac.cn