The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
Updated High 
resolution RS 
image 
Outdated map 
road feature 
Ï 
Change detection and 
revision road feature 
T 
Updated road 
feature result 
Figure 2 The flowchart of current map road feature updating 
method 
Searching for the changed road by current means is manually, 
the automatic level is low, and tends to omit changed road. 
In this paper, the “revision based on change detection” road 
feature updating method is discussed in detail, and the current 
road feature updating method is present only for comparing. 
2.1 Change detection 
In map road updating course, the change detection method is 
the key technique. In the process of change detection, image 
understanding technique of filtering, registration and 
multi-scale template matching are three main steps. 
2.1.1 The detection to partial changed or diminished 
road 
2.1.1.1 Filtering 
4) whether the road is partial changed or diminished. 
The templates this paper designed are a series of ridge-like 
templates with multi-scale in width (Figure 3), they are 
one-dimensional templates. g m axis represents template gray 
scale, y axis represents the template width, the middle part with 
even g m value represents the width of road. The difference of 
the width of template and the width of road is a constant. A 
series of templates were designed, they are differ in width of 
road, the width are respectively 3, 5, 7,..., 25(pixel)..., etc. In 
figure 3a, the width of template is 13, the width of road is 3; in 
figure 3b, the width of template is 15, the width of road is 
5.The template with 3 pixel of road width will get max 
matching result with a narrow road in image, and the template 
with 25 pixel of road width will get max matching result with a 
broad road in image. While the width of a road in image is 
unknown, it can be obtained by multi-scale template matching 
method. 
The road in image may be either bright or dark strip comparing 
to the background, two series of templates are designed: the 
first series of multi-scale templates are bright ridge-like 
(figure.3), and the second series of multi-scale templates are 
dark ridge-like (Figure 4). The former match bright road more 
efficient, and the latter match dark road more efficient. Whether 
the road is bright or dark could be judged by this means. 
A g m \ 
Filter the RS image to enhance the fuzzy texture using Wallis 
filter. Wallis filter •'] can increase the contrast and suppress 
noise of original RS image, thus it can raise the quality and 
accuracy of image feature in template matching. 
2.1.1.2 Registration 
The registration to the remote sensing image and the outdated 
map road feature. After choosing several control points equably 
on image and corresponding map, using polynomials rectify 
model to do the registration, the accuracy of registration should 
reach 1 pixel. 
a b 
Figure 3 Bright ridge-like multi-scale template 
Figure 4 Dark ridge-like multi-scale template 
2.1.1.3 Multi-scale template matching 
The character of the road in remote sensing image can be 
concluded as gray scale, geometry, topology, function and 
conjunction or context obligation etc. Among the characters, 
gray scale is the most important one, the gray scale of road can 
be expressed as linear feature with gray difference between the 
sides and the middle, so the ribbon-like (for ideal road) or 
ridge-like (for general road) template can be applied to match 
the road. This paper takes the outdated road vector as initial 
place, to match the updated RS image by multi-scale template 
matching method. The results are: 1 2 3 
1) The maximum template matching point; 
2) the width of the road in image; 
3) whether the road in image is bright or dark compare with 
the background; 
Figure 5 is the overlap of outdated road vector and updated 
RS image, the white line represents road vector, the line 
between two vector vertexes is a vector segment, and a road 
vector is make up of several vector segments. The broken line 
represents the direction of template matching, the crosses 
represent the max matching point produced by multi-scale 
template matching method. 
Figure 5 Multi-scale template matching 
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