The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008
172
d e f
Figure 2. (a,d) Aerial image (20 cm), (b,e) reduced resolution
(40 cm) ,(c, f) further reduced resolution (80 cm)
a Rollei AlC-modular -L-S digital metric camera with 4080 x
5440 pixels per image.
The RGB images are transformed to a gray scale images and
used as input to the SIFT algorithm. The LiDAR data have been
interpolated to a regular raster of 0.5 m grid size. Thus four
images, two for the last and two for the first returns of LiDAR
scanner are produced which in the following are called “Last
Range, First Range, Last Intensity and First Intensity". Each
LiDAR image covers 2000 x 2000 grid points.
3.2 SIFT Algorithm applied to the LiDAR Data
In a first experiment, keypoint extraction related to LiDAR
range and intensity is investigated by using all four LiDAR
images. Table 3.1 shows a significant difference with respect to
the number of extracted keypoints. LiDAR intensity images
have 7 to 8 times more SIFT key point features than LiDAR
range images which manifests a comparatively low range
variation in the range images. The reflected signal
Original image
500*500 pixels
original
aerial image
reduced
image
reduced
image
(20 cm)
(40 cm)
(80 cm)
Number of
3980
1326
378
SIFT features
Table 3.1. Key points in different LiDAR images
strength, which leads to the intensities in the range images,
leads to texturing which is comparable to the greyscale aerial
image. The spatial distribution of the keypoints is therefore
sparse in the LiDAR range images and dense in the LiDAR
intensity images. First return data tend to result in more
keypoints than last return data, which was expected in advance.
3.3 SIFT Keypoints extracted from the Aerial Image
While LiDAR images have a resolution of 50 cm, the aerial
image resolution is much higher with around 20 cm on the
ground. To see the impact on the number of extracted keypoints
the resolution of the aerial image is reduced to 40 cm and 80 cm
ground pixel size by Gaussian filtering and resampling. Figure
2 shows the extracted keypoints. The reduction of the
resolution by a factor of 2 (linearly), i.e. 2 by 2 pixels are
combined to 1 pixel, leads to a similar reduction of the number
of extracted keypoints (Table 3.2).
LiDAR
Last
Range
First
Range
Last
Intensity
First
Intensity
Number of
Key Points
1601
1828
11993
13393
Spatial
distribution
poor
poor
good
good
Table 3.2. Dependency of SIFT keypoints from image
resolution
3.4 Impact of Base Level Smoothing of the Datasets on
SIFT Keypoint Extraction
While in the previous section smoothing and reduction of the
resolution of aerial image was carried out, the base level
smoothing is a filtering of the input image with the Gaussian
kernel to define the base level of the scale space image
according to Eqn. (2-1). Figure 3 shows the dependency of the
number of extracted keypoints on base level smoothing for an
aerial image, and for LiDAR First Range, Last Intensity and
First Intensity. All image data sets are regions of 500 by 500
pixels. Figure 3 also shows that the curves for the aerial image
and both LiDAR intensity images are close to each other at a
base level smoothing with a cr of 1 and above. With a lower
sigma value for base level filtering more keypoints are
extracted from the aerial image than from the LiDAR intensities.
A value of 1 for the base level a was used for all further
experiments. The red line indicates the very small number of
extracted keypoints in the range data.
16000
Figure 3. Impact of base level filtering on keypoint
extraction
3.5 Impact of Octave Selection on Keypoint Extraction
Figure 4 shows that with an increasing the number of octaves an
increasing number keypoints is extracted. However with more
than 5 octaves the number of extracted keypoints is almost
constant. Thus, 5 octaves are used for the further experiments.
The size of the image was again 500 by 500 pixels. The number
of extracted keypoints varies with less than 10% between aerial
image and the LiDAR intensity images.