THE STUDY OF SPACE INTERSECTION MODEL BASED ON DIFFERENT-SOURCE
HIGH RESOLUTION RS IMAGERY
Weixi Wang a,b *, Qing Zhu a
a State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079,
Hubei, China—measurer@163.com
b School of Geomatics, Liaoning Technical University, Fuxin 123000, Liaoning, China—zhuqing@lmars.whu.edu.cn
Commission VI, WG VI/4
KEYWORDS: Different-source imagery, High resolution, generalized stereopair, RFM, Space intersection, reliability
ABSTRACT:
According to the concept of “generalized stereopair”, this paper focuses on the different-source high resolution remotely sensed
imagery covering the same regions, and investigates the space intersection mathematics models based on RFM. Considering the
complexity of imagery orientation in generalized stereopairs, this paper expends the original space intersection model based on RFM,
and proposed homologous new models. And then the accuracy of different space intersection models are analyzed and compared
through experiments. The results prove the computing precision and feasibility of space intersection mathematics models
based on generalized stereopairs.
1. INTRODUCE
Along with the development of satellite remote sensing (ab. as
RS) technology, the high resolution RS imagery play a more
and more important role in military, economy and government
decision-making, etc. It becomes a hot researching point to
realize targets 3D reconstruction using RS imagery. For
example, in the military applications, it is a urgent need to
obtain the medium and small scale terrain data and 3D model
reconstruction of the whole world key military targets using the
satellite RS imagery; In the development of city navigation
system, it needs to complete the destination navigation and
localization, the optimal route selection after the the 3D
reconstruction of cities or regions; In the research of city
emergency system, it urgently needs to construct the 3D
reconstruction model, and provide the data support for
government decision-making in the forecast of disaster scope,
the disaster effect evaluation, and the crowd dispersal.
In photogrammtry and RS, the 3D reconstruction is familiarly
obtained by stereopairs, and we can get many types of RS images
for now. However, we still suffer from the following two critical
reasons,
1. Many regions may have no stereopairs;
2. Even have, but very expensive.
Investigating the reasons, there are some factors to cause them:
(l)Polity (information blockage to non-allies or regions); (2)
Price (the prince of stereo RS imagery is usually more
expensive than single image several times); (3)Data lacking
(many special regions or targets usually have no stereopairs of
same satellite); (4)Security (the high resolution stereopairs of
some special regions are not provided).
Fortunately, more and more imagery could cover the same area,
which are of different satellite sensors or aerial cameras, these
images therefore have different space resolutions, different
colors and different period.
Focusing on the above two problems, and according to the
concept of “Generalized Stereopair”, this paper proposes a
method to construct a generalized stereopairs taking the overlap
high resolution images from different sensors or cameras as the
left and right images, and establishes new rigorous space
intersection models based on Rational Function Model (ab. as
RFM), then searches for homologous image points, lines or
patches in corresponding images, and brings these image
coordinates into these new space intersection models,
constructs generalized stereopairs, calculates the 3D
coordinates of corresponding ground points and completes the
3D reconstruction of targets at last.
2. THE CONCEPT OF GENERALIZED STEREOPAIR
In the traditional photogrammetry and RS, the concept of
stereopair is:
A pair of imagery obtained from different stations and has
overlap sections
Aiming at the complexity of different-source imagery, this
paper proposed the concept of Generalized Stereopair:
The stereo points, lines or spots established from any two
single image having overlap sections.
If the two single image have the same sensor, same imaging
station, same conditions etc, the generalized stereopair will
equal to the traditional stereopair. Therefore, they have the
following differentiation and affiliation :
Traditional Stereopair
Generalized Stereopair
Basic Cell
whole image
whole or part of image
Select Condition
singleness, same sources
multeity, same or different sources
