Full text: Mapping without the sun

153 
Table 4. Residue of tie points-comer 
The image coordinates of gravity center tie points are listed in 
table 5. These tie points are used to register the PAN image and 
the MS image. The residual is listed in table 6. The average 
residual is 1.1 m. 
No 
MS 
PAN 
Column 
Row 
Column 
Row 
1 
93 
506 
655 
738 
2 
99 
509 
681 
750 
3 
91 
497 
648 
702 
4 
96 
500 
669 
714 
5 
101 
503 
689 
726 
6 
94 
493 
659 
687 
7 
95 
490 
665 
672 
8 
101 
493 
687 
685 
9 
106 
496 
707 
696 
10 
1704 
815 
7088 
1978 
11 
1639 
830 
6827 
2037 
12 
1673 
843 
6965 
2088 
13 
1819 
387 
7545 
263 
14 
1819 
456 
7547 
539 
15 
2705 
553 
11084 
930 
16 
2730 
570 
11186 
999 
17 
2752 
1243 
11272 
3691 
18 
2561 
1690 
10509 
5477 
19 
1335 
1778 
5614 
5827 
20 
1134 
1771 
4812 
5800 
21 
1130 
1799 
4797 
5911 
22 
1091 
1747 
4639 
5706 
23 
106 
793 
707 
1886 
24 
98 
787 
676 
1859 
25 
152 
776 
892 
1817 
26 
135 
770 
822 
1796 
27 
239 
515 
1237 
772 
28 
651 
557 
2884 
943 
29 
632 
553 
2807 
926 
30 
1423 
460 
5966 
555 
31 
1414 
461 
5930 
562 
32 
1397 
454 
5861 
533 
33 
2903 
934 
11873 
2455 
34 
2905 
933 
11882 
2453 
Table 5. Tie points-gravity center 
No 
DX (m) 
DY (m) 
DH (m) 
Lon (°) 
Lain 
H (m) 
1 
0.614062 
0.099311 
0.000898 
66.5038 
45.84216 
12.23018 
2 
-1.23508 
0.065404 
-0.00722 
66.5036 
45.84209 
12.48353 
3 
-0.27595 
0.091463 
-0.00295 
66.5038 
' 45.84237 
11.75083 
4 
-1.21428 
0.07187 
-0.0067 
66.5037 
45.8423 
11.97572 
5 
-1.2488 
0.065249 
-0.0069 
66.5035 
45.84223 
12.20407 
6 
0.606496 
0.741034 
-0.01208 
66.5037 
45.84246 
11.59733 
7 
-1.20592 
-1.20093 
0.01889 
66.5037 
45.84253 
11.44491 
8 
0.559579 
-0.54401 
0.013131 
66.5035 
45.84246 
11.67833 
9 
0.525857 
-1.18904 
0.026498 
66.5033 
45.8424 
11.89462 
10 
-0.4202 
0.983144 
-0.00463 
66.4516 
45.83573 
28.89208 
11 
0.921315 
0.416142 
-0.00265 
66.4537 
45.83536 
29.39594 
12 
-1.11013 
-0.28598 
0.002354 
66.4526 
45.83508 
29.36405 
13 
1.399646 
-0.90938 
0.016064 
66.4478 
45.84565 
15.48529 
14 
-0.38934 
-0.94789 
0.010687 
66.4478 
45.84406 
17.661 
15 
-0.06905 
0.08487 
-0.00031 
66.4191 
45.84219 
27.80031 
16 
-2.02742 
0.676073 
0.001319 
66.4183 
45.84181 
27.84866 
17 
-0.11628 
0.443255 
-0.01782 
66.4177 
45.8263 
44.73466 
18 
0.43671 
-0.92311 
-0.01952 
66.4239 
45.81594 
58.05384 
19 
0.506976 
-1.0099 
0.000351 
66.4636 
45.81337 
29.73939 
20 
0.04247 
-0.17446 
-0.00049 
66.4701 
45.81344 
27.52945 
21 
-0.82709 
-0.84148 
-0.00469 
66.4702 
45.8128 
27.26041 
22 
1.228146 
1.179983 
0.006289 
66.4715 
45.81397 
27.44878 
23 
0.529867 
-0.0066 
0.007545 
66.5033 
45.83556 
22.20843 
24 
-0.32284 
-1.9317 
-0.00016 
66.5036 
45.8357 
21.77115 
25 
-0.6946 
-0.71485 
-0.00695 
66.5018 
45.83598 
24.42901 
26 
1.23475 
1.259045 
0.012387 
66.5024 
45.8361 
23.5107 
27 
1.417718 
-1.31574 
0.044876 
-66.499 
45.84203 
14.94287 
28 
-0.51233 
0.14652 
-0.00337 
66.4857 
45.84124 
20.88123 
29 
0.520512 
-0.45821 
0.012267 
66.4863 
45.84132 
20.69716 
30 
-0.39113 
-0.5687 
0.010798 
66.4606 
45.8438 
17.90377 
31 
-0.32515 
1.358252 
-0.0225 
66.4609 
45.84376 
18.05702 
32 
0.689816 
0.749536 
-0.01364 
66.4615 
45.84392 
17.88244 
33 
1.446471 
0.451103 
0.0109 
66.4128 
45.83348 
37.87234 
34 
0.536908 
1.712487 
-0.03244 
66.4127 
45.8335 
37.93841 
Mean error=l. 118235 m 
Table 6. Residue of tie points-gravity center 
4. ANALYSIS AND CONCLUSION 
Compare the average residual of comer and the average residual 
of gravity center, it is not difficult to draw a conclusion that the 
gravity center tie points are more suitable for registration of 
different resolution images. The problem is that, as analysis in 
the introduction, most of the automatic interest point extraction 
algorithms can not extract gravity center points. Therefore, how 
to extract gravity center points is our future work. 
REFERENCE 
Baker, S., Nayar, S.K., and Murase, H. 1998. Parametric feature 
detection. International Journal of Computer Vision, 27(1 ):27- 
50. 
Beaudet, P.R. 1978. Rotationally invariant image operators. In 
Proceedings of the 4th International Joint Conference on 
Pattern Recognition, Tokyo, pp. 579-583. 
Beus H.L. and Tiu S.S.H. 1987. An improved comer detection 
algorithm based on chain-coded plane curves. Pattern 
Recognition, 20:291-296. 
Chen C.H., Lee J.S. and Sun Y. N., 1995, Wavelet 
transformation for grey-level comer detection, 28(6), pp853- 
861, Pattern Recognition, 1995.
	        
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