Full text: Proceedings, XXth congress (Part 3)

   
  
  
  
   
  
  
   
EXTERIOR ORIENTATION FOR REMOTE SENSING IMAGE WITH HIGH 
RESOLUTION BY LINEAR FEATURE 
Jianqing Zhang Hongwei Zhang Zuxun Zhang 
College of Remote Sensing and Information Engineering, Wuhan University 
#129 Loyu Road, Wuhan, Hubei, P.R.China 430070 
jazhang@supresoft.com.en, zZhwIx_wuhan(àsina.com, zxzhang@supresoft.com.en 
KEY WORDS: Remote Sensing, Photogrammetry, Updating, High Resolution, Image, Feature, Vector, Orientation 
ABSTRACT: 
An automatic approach to the exterior orientation by using linear primitives such as rivers and roads, which are extracted from the 
image and match to the existing vector data, is presented in this paper. Because the automatic identifying line features is much easier 
than point features, so that the observations are increased significantly and the exterior orientation can be improved. Proposed 
approach creates the possibilities for automatic exterior orientation in special data updating and the registration of multi-resolution 
remote sensing images. The exterior orientation is based on automatic linear object extraction and generalized point photogrammetry, 
so called generalized point it means that collinearity equation is still used for linear primitives, which is divided into three phases. In 
the first phase, by using three coarse conjugate point pairs defined manually a global affine transformation between remote sensing 
image and vector map is determined, which provide initial corresponding relation between image and map for automatic linear 
feature extraction. Based on the high accuracy extraction algorithm, the linear objects are optimized automatically in the second 
phase. In the third phase, the exterior parameters of remote sensing image with high resolution are computed based on the linear 
object segments by the generalized point photogrammetry. Proposed method can used for both affine transformation and second 
order polynomial for remote sensing image. Within the study, some experiments are carried out for a number of images with high 
resolution. All of the results of the experiments show that the approach mentioned above is feasible and very efficient. 
1. INTRODUCTION 
It is now widely accepted that photogrammetry has reached the 
digital age and that many processes can be carried out more 
efficiently using digital data than with hard copy images. It is 
by no means yet accepted that digital methods can offer savings 
in time and cost across the board and it is likely that the 
development of more robust automatic techniques will be 
needed before this can happen. The automatic exterior 
orientation of remote sensing imagery is a promising task in 
photogrammetry and remote sense, which is usually completely 
performed by a human operator in the Digital Photogrammetric 
Systems existing today. 
The need of making map revision arises due to the addition or 
removal of terrain features. The rapid changes in the map 
contents and the need for up-to-date maps have compelled 
surveyors to focus their attention to the development of faster 
and more economical map revision processes. Photogrammetric 
techniques and satellite techniques are main means for the map 
revision, in which remote sensing imagery are effective and 
economical data source. In the processing the captured image, 
the first step is calculating the parameters of image position and 
orientation. 
Exterior orientation for remote sensing image is a prerequisite 
for its geo-reference, which was solved using a number of well- 
defined ground control points (GCPs) traditionally. It is a time 
consuming operation because the GCPs were measured 
manually and the recognition of control points was very 
difficult. Generations of researchers have worked hard to 
improve this process. 
  
It is essential that the same feature is identified from the image 
and the reference data. In view of these issues, other researchers 
have investigated the use of higher-level geometric features 
such as lines or curves as observed geometric entities to 
improve the automation for estimating exterior parameters, 
which also improve robustness and accuracy. With the recent 
trend towards automatic extraction and recognition of features 
from digital imagery, it is becoming advantageous to utilize 
features in photogrammetric applications. Those features can be 
used to increase the redundancy and improve the geometric 
strength of photogrammetric adjustments. In addition, it is 
easier to automatically extract features than distinct points from 
imagery. In the literature many advantages of using line 
observations instead of points can be found. The most 
prominent advantage is the better automation potential for 
extraction and measurement of lines in digital imagery (Burns, 
1986). From the geometrical point of view lines have the 
advantage that they only have to be partly visible in the image, 
and this does not have to be the same part for image and 
corresponding map. 
An automatic approach to the exterior orientation by using 
linear primitives such as rivers and roads, which are extracted 
from the image and match to the existing vector data, is 
presented in this paper. Because the automatic identifying line 
features is much easier than point features, so that the 
observations are increased significantly and the exterior 
orientation can be improved. Proposed approach creates the 
possibilities for automatic exterior orientation in special data 
updating and the registration of multi-resolution remote sensing 
images. 
“jgzhang@supresoft.com.cn, Tel: 86-27-87561116; Fax: 86-27-87561011 
   
  
   
  
  
  
  
  
  
   
  
  
   
  
  
   
  
   
  
  
  
  
  
  
  
   
  
  
   
   
  
   
   
   
   
  
    
  
   
   
    
  
   
  
   
  
  
   
   
   
    
   
  
   
   
   
   
   
International Archi 
UPC EI NN 
This paper is o 
summarizes the aut 
vector river map by 
and its solution « 
presented in Sectio 
above, some tests c 
method is manipula 
2. AUT( 
Extraction of curvi 
been one of pop! 
photogrammetry, 
Automation of suc 
although full and 
Various methods p 
grouping, (Trinder 
scale-space approa 
network and classif 
energy minimizatit 
matching (Vosselm: 
et al., 2000). Thos 
extraction from ae 
which were not al 
sensing imagery. 
[n this paper, a new 
with two steps, whi 
orientation in the 
transformation betw 
determined by using 
manually, which pre 
image and map for 
second steps, pro 
extraction of river 
characteristic of riv 
initial position prop 
  
Figure 1: river fea 
the red | 
road ma 
extractioi 
  
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.