International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B4, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
ACCURACY IMPROVEMENT OF DEM FOR GENERATING ORTHOPHOTO BY
REVERSE PROJECTION METHOD
F.Sugiyama®, H.Chikatsu®
* System Development & Research Center, AERO ASAHI CORPORATION,
3-1-1 Minami-dai, Kawagoe, Saitama, 350-1165, Japan - fuminori-sugiyama@aeroasahi.co.jp
? Dept. of Civil and Environmental Engineering, Tokyo Denki University,
Ishizaka, Hatoyama, Saitama, 350-0394, Japan - chikatsu@g.dendai.ac.jp
Commission V, WG V/4
KEYWORDS: Matching, Image, Orthoimage, DEM/DTM, Accuracy, Three-dimensional
ABSTRACT:
The generation of orthophotos using digital aerial photography is performed for the maintenance of spatial information data for wide
areas at the mid-scale.For orthophoto generation, a digital elevation model (DEM) based on stereo matching methods is widely used,
the accuracy of which should be effectively improved by removing mismatched points created during the stereo matching process for
efficient orthophoto generation. With this motive in mind, a new method called the “Reverse-Projection Method” is proposed to
remove mismatched points from DEM generation. The most remarkable points of this method are its ability to detect mismatched
points and improve the accuracy of a DEM using only stereo models on the previous and following strips and restricting the higher-
resolution stage in the coarse-to-fine approach using the Digital Terrain Model as a reference. The effectiveness of the method is
discussed in this paper.
1. INTRODUCTION
Digital orthophotos are widely generated using digital
photogrammetry, for the preparation of geospatial information
over wide areas. Digital orthophotos are created by projecting
aerial photo images orthometrically using a digital elevation
model (DEM). A DEM is an intermediate product of digital
photogrametry and is extracted through a matching process.
When a mismatch occurs during the matching process, a DEM
with erroneous altitude information is extracted and a
degradation of the accuracy of the orthophoto occurs. Checking
and modifying a digital orthophoto requires a lot of manpower.
Thus, the reduction of mismatches during DEM extraction
directly affects the efficiency of digital orthophoto generation.
There are two approaches for a reduction of mismatches during
DEM extraction: a restriction of the search range and an
improvement in the similarity of the texture pattern. A
restriction of the search range has been adopted for epipolar
image creation (Schenk 1999), the vertical line locus method
(Bethel 1986), and the coarse-to-fine method (Shecnk 1999),
while an improvement in the similarity of the texture patterns
has been adopted for least square matching (Foerstner 1982;
Ackermann 1984; Gruen 1985, ct.al). However, even with these
approaches, a perfect prevention of mismatches has yet to be
achieved(Bethmann et al. 2010).
While the following three methods have been proposed to judge
and remove mismatched points, a problem remains in each
method: Foerstner's method (Foerstner 1984) also incorrectly
removes matched points in steep areas. The Back-Matching
method (Zhang et al. 2006) may not remove mismatched points
in areas with a continuously similar texture pattern. Finally, the
multi-lay stereo model method (Zhang et al. 2005) requires
additional time during the processing by creating stereo models
between the base images and neighboring images (Takeda et al,
2008).
In traditional aerial photogrammetry, sterco models for each
image along the direction of every strip are created. Therefore,
it is examined that the reliability of DEM points from multiple
directions has been positively evaluated, and the accuracy of the
DEM has been improved using the stereo models described
above along and across the strip, without the need to create new
stereo models.
In this research, a Reverse Projection Method (RPM), which
uses neighbor stereo models for evaluating the reliability of the
DEM points, is proposed. Next, the propriety of this method for
an improvement in the accuracy of the DEM is discussed.
Furthermore, the best way to apply the RPM for optimizing the
creation of the DEM is investigated.
2. THEORY AND ALGORITHM
The RPM proposed in this research is performed as follows. (1)
Project DEM points to a neighbor stereo model after the
matching process. (2) Evaluate the reliability of the DEM points
using the similarity of texture patterns from the neighbor stereo
model. (3) Finally, DEM points with low reliability are
removed.
AerialPhoto Interior Exterior
Image Orientation Orientation
(L*R) Parameter Parameter
[
Coarse-to-Fine Approach
y
Matching
RPM
Figure 1 The flow for DEM extraction using the RPM
Using these steps, the RPM prevents any mismatches, which are
a problem for the efficiency of digital orthophoto generation,
and maintains or improves the accuracy of the DEM. The flow
of DEM extraction using the RPM is shown in Figure 1, and
further details on this process are given in the following section.
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