Full text: Proceedings, XXth congress (Part 5)

  
  
  
DODGING IN PHOTOGRAMMETRY AND REMOTE SENSING 
Zh.J. Li', Z.X. Zhang, J.Q. Zhang 
College of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan, China, 430079, 
zhijiang_lee(@yahoo.com.cn, zxzhang@supresoft.com.cn, jqzhang(@supresoft.com.cn 
KEY WORDS: Remote Sensing, Close Range, Photography, Color, Image, Modelling, Rendering 
ABSTRACT: 
The images in photogrammetry and remote sensing applications are always degraded images. The degradation lies in two aspects: 
geometry degradation and radiometry degradation. Aimed at the images captured in various scales, the causes of uneven illumination 
and uneven color are analyzed. Then, the definition of dodging is extended as a process removes uneven illumination and uneven 
color, eliminates obvious color cast, and improves the realistic representation and geometry quality effectively. However, the main 
approaches for dodging currently are all merely perform the task of balancing illumination without take into account other factors. 
After compared and analyzed such approaches, introduced multi-scale retinex for color rendition, and made an assumption of grey 
world, a framework for color image dodging only based on image information in photogrammetry and remote sensing is proposed 
and tested. The experiment indicates that such framework can process uneven lightness, uneven color, obvious color cast effectively 
and restore geometry degradation in a certain degree. 
1. INTRODUCTION 
In the applications of photogrammetry and remote sensing, the 
photos arc obtained in various carriers at various scales. The 
images can be classified into remote sensing image, aero-borne 
photo and close range image based on imaging scale. The 
carrier of remote sensing image usually is satellite or space 
shuttle. The carrier of aero-borne photo is usually the aeroplane 
or other crafts. The close range image 1s captured by camera in 
hand or vehicle-borne sensor, camera or video camera. In the 
process of imaging, each relevant element will affect the final 
image. According to the path of light propagation and 
perception, such affections can be arranged as following: 
(1) Mluminant. In photogrammetry and remote sensing, the 
illuminant of imaging is always the sun (close range image may 
be captured indoor). As to the sun, the difference of imaging 
time indicates the change of light direction and the color 
temperature of the illuminant. The direct affection. of the 
change of light direction is that the intensity of the illumination 
in the scene and the incident angle are changed. The direct 
affection of changing the color temperature of the illuminant 1s 
that the spectra distribution of the illuminant is changed. Thus, 
the reflectance spectra of the same surface in the same scene 
will be changed, which will make the image different. 
(2) Propagation medium. The primary medium in 
photogrammetry and remote sensing is the atmosphere. The 
affections of the atmosphere on image are different in different 
scales. Generally, the weather variation between multi imaging 
times, the variation of the clouds and the atmosphere turbulence 
etc. are primary factors, which will change the illumination 
spectra on the surface in the scene. 
(3) Surface characteristic in the scene. Different physical 
characteristic will obtain different selective absorption of the 
illumination spectra. While different geometry characteristic 
will cause the interaction of multi surfaces. 
(4) Imaging device. The optical system diffraction, the non- 
linearity of sensors or films, the aberration of the optical system, 
the relative movement of the imaging device and object in the 
  
* zhijiang_lee@vahoo.com.cn, Tel: 86-27-87654319 
scene all will cause the change of illuminant spectra and the 
lightness distribution in the image. 
Such affections will cause the degradation of the imaging result, 
which lies in two aspects, geometry degradation and radiometry 
degradation. The presentation of the former is mostly edge 
blurring, noise and geometry distortion. While the presentation 
of the latter is mostly uneven lightness, uneven color, and 
obvious color cast. 
The most intuitive approach is to build a degradation model. 
However, the building of the model is various. Wu and Danaher 
[Wu, 2001; Danaher, 2001] built a physical model based on the 
ground reflectance. Guo [Guo, 2000] built a model based on the 
radiometry characteristic of the image and imaging geometry 
relation. More literatures [Tian, 1999; Wang, 2000; Chehdi, 
1993; James, 1983; Zhou, 1999: Hu, 2004; Zhang, 2003a] 
proposed some approaches in the view of image restoration and 
image enhancement based on the image feature. However, they 
can't solve all the problems simultaneously. The definition of 
the dodging in such literatures is limited in dodging lightness 
and color, without the realistic of color rendition. But presently, 
with the development of the device and technology in image 
capturing, display, and output, the request of realistic image 
reproduction in the task such as image interpretation. and 
analysis is enhanced at the same time. Color as an attribution is 
more and more important in photogrammetry and remote 
sensing, computer vision, machine vision and other areas. 
Therefore, develop an approach to solve the problems above is 
very important and meaningful. 
Aimed at such problem, in this proposal, section II describes 
the two primary directions on such topic in detail and indicates 
the new definition of dodging in photogrammetry and remote 
sensing. Section III relates the approach based on physical 
model briefly and points out its availability. Section IV 
introduces primary approaches about dodging based on the 
characteristic of the image itself currently, analyzes their 
function, and points out their availability. Section V proposes a 
new framework about such topic. Section VI is concerned with 
its application to real data and the analysis on the result. 
   
  
  
  
  
    
   
  
     
   
  
    
   
   
   
   
   
  
    
   
    
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