2008 
1005 
A METHOD OF HIGH-RESOLUTION REMOTE SENSING IMAGES BUILDING ON 
EDGE EXTRACTION 
WANG DAN *, SONG WEI-dong 
School of Geomatics, Liaoning Technical University, Fuxin, 123000 ,Liaoning, China — 
wangdan youxiang@163.com,song wd@163.net 
Commission VII, WG VII/5 
KEY WORDS: Aerial Images; Building Contour; Building Recognition; Edge Extraction; Edge Extraction; Semi-Automatic 
ABSTRACT: 
This paper proposes a method of high-resolution remote sensing image of buildings on semi-automatic edge extraction. The first, 
pre-process remote sensing image and detecting all the edge; the second, tracking the edge and extracting linear feature, extracting 
the main direction line of the buildings; then using the model to judge the relations of line, segmentation and regional growth; lastly, 
merge regions and extract the building contour. The paper use this method to experiment on high-resolution Quick Bird satellite 
images, the result shows that this method has a higher recognition level, a better accuracy of a certain practical value. 
1. INTRODUCTION 
As an important element of topographic map, Buildings, whose 
recognition and extraction directly affected the automatic level 
of terrain feature survey. Because the building has obvious 
characteristics of position, it’s recognition and precise 
positioning for feature extraction, the feature matching, the 
image understood, the mapping and regarded as reference body 
to other targets have the vital significance. From the point of 
view of practical application, the realization of remote sensing 
images to identify buildings need to satisfy the remote sensing 
image mapping, GIS data acquisition and automatic updates; 
From the point of view of research, because of the high 
diversity and complexity, the successful automatic identification 
system of buildings will provide a general understanding of 
guiding significance of the theory and methods. Therefore, how 
to identify and extract the buildings from remote sensing images 
is the one of the most important researching topics of objective 
recognition. 
The paper studied the computer vision, image understanding, as 
well as the method of information extraction, then put forward a 
semi-automatic extraction method of buildings and solved the 
problem of extraction of flattened rectangular buildings. 
2. METHODS OF REALIZING 
Rectangular buildings or that combinations, whose obvious 
characteristics in the images, is mutual orthogonal of neighbour 
edges. Based on this structural characteristics of buildings, 
carried out statistics to the edge of lines, obtained the main 
direction of buildings, according to main line direction to get rid 
of some interference, processed the main direction and its 
vertical line with model, divided the image to different regional 
blocks with the extension of line, chose the blocks of buildings, 
merged them with adjacent regions in accordance with certain 
criteria, then extracted the outside edge of combination region 
and implemented linear approximation, the final outcome was 
got. 
2.1 Preprocessing of remote sensing image 
There are a variety of influencing factors present on accessing 
the remote sensing images, due to the image including 
quantization noise, channel transmission noise, thermal noise 
and other types of noise, and influencing the following work of 
information extraction. In order to solve this problem, we need 
to carry out the smoothing filter to remove the noise, however, 
during the process of smoothing, the filter which requires good 
ability of smoothing, at the same time , should keep the details 
of images, and maintains the accuracy of marginal position. In 
this paper, use adaptive smoothing method to pre-proceed the 
image. 
2.2 Edge detection and linear feature extraction 
Building recognition and extraction on the high-resolution 
remote sensing images, building top edge information is a most 
important means of judge. Therefore, how to extract the top 
edge of building is one of the important factors influencing the 
result of extraction. In image processing, generally considered 
grey changed dramatically which is the edge points. In the 
frequency domain shows high-frequency component, the 
process of edge detection is to locate the grey dramatic changes 
in image, which is also a high-frequency enhanced process. 
Compared to other classic edge detection operatorfRobert, 
Sobel), Canny edge detection has good continuity and integrity, 
moreover has obvious effect, after the detection, it’s necessary 
to process threshold segmentation and refinement to get BW 
images, easily process followed. 
* Corresponding author. Wang Dan, (1983-), female, Liaoyan, Liaoning province, graduate student. 
E-mail:wangdan_youxiang@163.com