International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B3, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
can then be connected correctly in a procedure for connecting
all matched points.
Moreover, another advantage of the AFTP on the top level of
image pyramid is that AFTP automatically provides
approximate image overlap information in a block. In other
word, this study proposes the new method for SIFT supported
dense point cloud matching and aero triangulation without the
need on the known image overlap information which is often
given by the input strip and block parameters.
Figure 5. AFTP provides approximate image overlap
information automatically
The afore-mentioned method for dense point cloud matching
can be done by the only input of aerial images. After the
transformation from image coordinates (r, c) to photo
coordinates (x, y), a bundle block adjustment with data
snooping (Baarda, 1968) procedure is used for preliminary error
detection (Kruck, 1984), and quality validation is done by
means of ground check points.
Figure 6. Overlap of all 108 test images, and locations of 6
ground control points and 65 check points
3. TESTS
3.1 Efficiency Analysis
Test data includes in total 108 aerial images taken with the
RMK DX camera with the focal length /-9.2cm in Chang-Hua,
Taiwan, inclusive of four strips and two cross strips. Figure 6
shows the overlap of these 108 aerial images and the locations
of 6 ground control points and 65 check points uniformly
distributed in the test block of about 4km x 4km. The average
flight height is about 1100m. The pixel size of these large
format aerial images is 7.2um, and the image size is 12096 rows
x 11200 columns. In other word, the average groundel size is
about 8.6cm. All tests are done on a PC with the CPU of Intel
Corel 15-750 at 2.67 GHz, and the RAM of 3GB, as well as the
OS of Microsoft Windows XP Professional SP3, where all
programs are written in MATLAB.
First, a block of 11 images is selected for testing the
computational efficiency of key point extraction, AFTP and QF,
as shown in Table 1. Key point extraction for 11 images spent
6575 seconds. When distance ratio of AFTP is 0.2, there are 28
image matching pairs available, i.e. loop number is reduced
from 55 to 28. The “distance ratio of AFTP” means the distance
ratio of SIFT set to a stricter smaller threshold in order to select
less number of best keypoints as input points to the AFTP.
AFTP for these image pairs spent 116 seconds. QF for all key
points on all 11 images spent 567 seconds. Figure 7 illustrates
the image coverage determined automatically by the AFTP for
these 11 images. It demonstrates an advantage of the proposed
new method for dense point cloud matching and aero
triangulation, namely without the need on image overlap
information.
rocess object Calculation time (seconds)
Key point 11 images 6575
extraction
AFTP 55 image pairs 116
QF 11 images 567
Table 1. Calculation time
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Figure 7. Image overlap determined by AFTP for the 11 test
images
Summarily, Table 2 shows the key point density for these 108
test images on different level of image pyramid, where a stricter
threshold 0.2 for the distance ratio of SIFT is adopted to extract
less number of best key points. Figure 8 illustrates the key point
density on each pyramid level. Apparently, a higher level of
image, namely a smaller scale of image, owns a denser cloud of
key points. Generally speaking, the density of key points
depends not only on the distance ratio threshold of SIFT but
also on the amount of image information as well as image
quality. For example, Figure 9 illustrates the locations of key
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