KEY TECHNIQUE OF ACCU
RATE RECTIFICATION
FOR REMOTE SENSING IMAGE WITH HIGH RESOLUTION
Jianging Zhang, Yong Zhang*, Shunyi Zheng, Hongwei Zhang, Zhijiang Li
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China, 430079 -
e
(jqzhang,yongzhang)@supresoft.com.cn, syzheng(@263.net, Zhwlx_wuhan(@sina.com, zhijiang lee(yahoo.com.cn
Commission III, WG 111/72
KEY WORDS: Remote Sensing Image, High Resolution, Parameter Calculation, Image Matching, Accurate Rectification
ABSTRACT:
The geo-referenced image with one-meter resolution (GRIOMR)
sensing image with |
is one of the most basic information in the digital earth. The remote
righ resolution (RSIHR) is the best resource for acquiring the GRIOMR in low costing and sort period. The key
technique producing GRIOMR from RSIHR is introduced in this paper, including parameter computation of RSIHR, image
matching to creating DTM and fast orthogonal rectifica
tion of RSIHR. After the Rational Polynomial Coefficient (RPC) used by
IKONOS and QUICKBIRD images and the block adjustment based on RPC parameters are presented, the new, simple and strict
geometric model based on affine transformation is destribed. When there are control points less th
an 5 in each image, the block
adjustment based on RPC parameters could be used. If there are control points more than 4 in each image, the new, simple and strict
geometric model based on affine transfor
relative registration, remains quite large y-para
from RSIHR. Based on DTM and image parameters acquired by block adjustment b
Igorithm. The experimental results with real RSIHR show the strategy
affine transformation, the RSIHR can be rectified by fast a
mation should be applied. For some of RSIHR, the approximate epipolar image pair, after
lax. Therefore, the 2 D relaxation matching should be used in the DTM modelling
ased on RPC parameters or the model based on
introduced in this paper is feasible. Corresponding conclusion and future work are summarized in the final.
1. INTRODUCTION
The geo-referenced image with one-meter resolution (GRIOMR)
is one of the most basic information in the digital earth. The
remote sensing image with high resolution (RSIHR) is the best
resource for acquiring the GRIOMR in low costing and sort
period. The key technique producing GRIOMR from RSIHR is
introduced in this paper, including parameter computation of
RSIHR, image matching to creating DTM and fast orthogonal
rectification of RSIHR.
Because of very strong relativity of traditional parameters of the
RSIHR, traditional image parameters can't be acquired
sometimes. The algorithm of fitting based on reasonable
polynomials, proposed by Kratky (Kratky, 1989a and Kratky,
1989b), is used. For example, the IKONOS and QUICKBIRD
images are supported by RPC (Rational Polynomial Coefficient)
(Z hang et al., 2001). But, the coordinate accuracy computed by
them is quite lower in many cases, and some control points are
still needed for improving the accuracy. Furthermore RPC/RPB
model is too complex. After the block adjustment based on RPC
parameters 15 presented, the new, simple and strict geometric
model based on affine transformation is described (Zhang et al.,
2002). Only 8 affine coefficients and one slantwise angle need
to be determined by control points. Then, the image coordinates
can be calculated using ground coordinates and 9 parameters.
When there are control points less than 5 in each image, the
block adjustment based on RPC parameters, where an affine
transform of image coordinates are computed by measured
coordinates of control points and their coordinates calculated by
RPC/RPB parameters, could be used. If there are control points
KL
* Corresponding author.
more than 4 in each image, the new, simple and strict geometric
model based on affine transformation should be applied.
For some of RSIHR, the approximate epipolar image pair(Zhang
et al., 1989), after relative registration, remains quite large y-
parallax. Therefore, the usual 1-D image matching method is
not suitable for the approximate epipolar image pair of the
RSIHR, including the very efficient relaxation matching
(Baltsavias, 1991; Zhang et al, 1992). Instead of the ! D
relaxation matching, 2 D relaxation matching should be used in
the DTM modeling from RSIHR. The procedure includes
Feature point extraction, approximate value estimation,
matching and refining and filter.
Based on DTM and image parameters acquired by block
adjustment based on RPC parameters or the model based on
affine transformation, the image coordinates can be calculated
for the orthogonal rectification of RSIHR. After re-sampling on
original RSIHR, the orthogonal image is obtained. The fast
algorithm for orthogonal rectification of RSIHR should be
applied. The experimental results with real RSIHR show the
strategy introduced in this paper is feasible.
2. PARAMETER COMPUTATION OF RSIHR
If there are control points less than 5 in each image, the block
adjustment based on RPC parameters could be used. Otherwise
the new strict geometric model based on affine transformation
could be applied for any RSIHR.
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