Ephemeris 
+ recording To 
Imaging start time To * 53s 
Imaging end time 
     
    
8 seconds 
Figure 1. The illustration of ephemeris information recording 
frequency of HJ-1A/1B Example of a figure caption. 
3. CONSTRUCTION OF GCP IMAGE DATABASE 
The resolution of HJ-1A/1B multi-spectral CCD image is 
equivalent to LandSat-TM, and both are 30m. The historical 
TM images and DOM images can be obtained from website for 
free. There are TM images covering the whole China, and the 
plane precision is about 1 to 1.5 pixels, which can be utilized 
as the GCP data source for HJ-1A/1B. Although the change is 
certain due to the different imaging time evenly many years, 
there are many stabilized and character-distinct points or areas 
in the images. These stabilized points or areas can be used as 
GCP for rectification. Fig 2. shows the sample unchangeable 
image chip on TM(2007) and HJ-1A(2010) at the same area 
  
  
    
TM Multi-Spectral Image HJ Multi-Spectral Image 
(2007) (2010) 
Figure 2. The unchangeable image chip on TM 
DOM(2007)and HJ(2010). 
The GCP Image Database is constructed with many small GCP 
image chips, which consists of the image information and 
attribute information. The attribute information of GCP image 
chip describes the geographic information which contains the 
3-D coordinate of GCP point, the coordinate system and ellipse 
datum information, the auxiliary information such as the sensor 
name, spectral range, the resolution and width/height of the 
GCP image chip. After collection of GCP image chips, then 
save them using the same table attribution, the GCP Image 
Database can be applied as GCP data source for geo- 
rectification. 
4. SEARCHING AND AUTO-MATCHING THE 
REASONABLE GCPS FROM DATABASE 
One scene image of HJ-1A/1B covers 360km*360km, while 
the GCP Image database covers the whole China, so quickly 
searching and auto-matching the reasonable GCPs is a key 
problem for rectification. The geographic information of GCP 
image chips provides the direction, and then the searching area 
can be reduced and the initial position of coarse-matching 
    
    
     
   
  
    
     
  
    
   
    
     
   
   
   
    
  
  
  
    
   
    
     
    
   
  
    
  
  
  
    
     
    
    
   
   
   
    
   
   
   
   
    
    
    
    
points can be fixed, which can decrease the calculation and 
increase the matching accuracy. 
The steps of GCP image chips searching and matching are as 
follows: 
1) Indexing the GCP image chips from database based on the 
covering area of initial image and the geo-information of 
GCP image chips. 
2) Select the Columns icon from the MS Word Standard 
toolbar and then select “1 Column” from the selection 
palette. Searching for the reasonable GCP image chips by 
analyzing the imaging time and distance between GCP 
image chips. The latest GCP image chips to the imaging 
time will be preserved and distance between GCP image 
chips will be restricted as 30km, or there will be too many 
GCP image chips in the covering area. 
3) Clip the image chip from initial image according to the 
geo-information of GCP and the metadata information of 
initial image, the clipped chip from initial image should be 
bigger then GCP chip because of the possible error. 
4) Imaging matching between the clipped chip from initial 
image and GCP image chip by SIFT algorithm([7]. 
5) Eliminate the mis-matching points by Rough Fuzzy C-mean 
Method[8]. 
6) Precise image matching by LSM[5]. 
7) Output the matching result. 
  
Ea GCP image 
Initial image ; 
chips 
Yv Yv 
Extraction of Geometrical Extraction of Geometrical 
Invariant Feature Points Invariant Feature Points 
Image matching base on | 
SIFT algorithm 
No (Parameters self-adapted adjustment) 
Matching points number is 
bigger than 7 
Yes 
Yv 
Mismatching points elinimation using Rough 
Fuzzy C-Mean Method 
y 
Matching points number is 
N 
bigger than 7 9 
Yes 
Y 
SAC ; Y 
RANSAC algorithm 
Matching points 
number is bigger than-3^ 
v - 
LSM and eliminate the points 
; ; Yes 
which fit error bigger than 2*rms 
y 
Output the | No 
matching result 
Figure 3. The work-flow of auto-matching GCP image chip 
  
  
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