Full text: Proceedings, XXth congress (Part 1)

   
   
   
   
   
   
   
   
   
    
  
  
  
  
  
  
  
   
  
   
  
    
   
    
  
   
   
   
   
   
   
    
   
   
    
     
    
   
     
     
  
   
   
  
   
   
   
  
   
  
   
   
   
     
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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B1. Istanbul 2004 
3. MATERIALS AND METHODS 
3.1 Materials 
The investigation was made in close co-operation with three 
Finnish image producers, Ministry of Agriculture and Forestry 
(MAF), two Forestry Centres and the Forestry Development 
Centre Tapio. In the following, the image producers are named 
Company A, Company B and Company C. 
The study of histograms was based on 41 scanned CIR images 
from Company A and 2818 histograms collected with 
HISTOQC-program from image servers of Company A and 
Company B. The scanning process was done using either 10 or 
12 bits per channel and images were transformed to 8 bits per 
channel afterwards. Summary of the histogram material used is 
presented in table 1. Scanners used are presented in table 2. 
  
  
  
  
  
  
  
  
  
  
  
  
can be used either interactively or from the command line. 
HISTOQC calculates the statistics described on chapter 2.2. 
The black borders of images, resulted from surrounding film 
clear base, were excluded from the calculations of histograms. 
Statistic-files were imported to Excel and several charts and 
diagrams were created and analysed. 
Experimental image enhancement was made with Adobe 
PhotoShop 7.0 —software. Effects of these enhancements to 
image histograms were followed using HISTOQC. 
4. RESULTS 
4.1 Histograms 
Different types of films produced clearly distinguishable image 
histograms. In all images investigated, RGB-histograms were 
typically unimodal, i.e. they had a single peak. In colour films 
  
   
  
  
  
  
  
  
  
  
  
  
  
Table 1. Histograms used. 
  
Scanner [Model Bits [Owner 
SI Zeiss SCAI 10 | Company A 
S3 Leica Geosystems DSW600 12 | Company A 
S3a  |Leica Geosystems DSW600 10 | Company B 
S3b  |Leica Geosystems DSW600 12. | Company B 
  
  
  
  
  
  
  
  
  
  
Table 2. Scanners. 
For the study of the tone tuning procedures and their influence 
on radiometric quality, 20 tuned CIR ortho images were 
received from three Finnish image producers and two Forestry 
Centres. Company A, Company B and Company C delivered 
three types of images: the original orthophoto, one tuned to be 
used in forest interpretation and one tuned to be used in land 
parcel interpretation. Forestry Centres delivered images tuned 
to be used in forest interpretation. Company A also delivered 
41 scanned CIR images (Kodak 1443 CIR-negative film, Leica 
Geosystems DSW600 12bit scanner). 40 of the images were 
taken in different parts of Finland (10 from Central Finland, 10 
from Northern Karelia, 10 from Northern Ostrobothnia, 10 
from Lapland) and in different seasons (from each area: 5 in 
the beginning of summer 2002 and 5 in the middle or end of 
the summer 2002). In addition, one image from southern 
Finland taken on the summer 2003 was delivered. 
3.2 Methods 
Preliminary studies of histograms were made with Matlab 6.5 
and Erdas Imagine 8.5 —softwares. Based on these results, a 
program named HISTOQC was coded with C++ -language for 
collecting histograms and statistics of scanned aeria! images. It 
runs in Windows-based operating systems in DOS-prompt and 
Source Amount [Country [Film Scanner {Resolution 
Company A 5 SWE [Agfa X-100 (colour-neg.) > 14pm 
Company A 48 FIN {Avi Chr 200 (colour-pos.) SI 14 pm Copurpositivefim Colour-negative-film 
Company A 18 FIN [Avi Chr 200 (colour-pos.) S2 14 um i 
CompanyA | 277 FIN [Kodak 1443 (CIR-neg.) SI 14 jm iu se 
Company À 557 FIN | [Kodak 1443 (CIR-neg.) S2 14 pum ET genre 
Company À 6 LTU |Kodak 1443 (CIR-neg.) SI l4 um op i |^ 20000 k [^ 
Company A 131 LTU [Kodak 1443 (CIR-neg.) S2 14 pm 3000000 1 3000000 3 [3 
Company A 2 SWE [Kodak 2444 (colour-neg.) SI 14 um 2000000 H 2000000 | E 
Company A 92 SWE [Kodak 2444 (colour-neg.) S2. 14 um ol | 1000000 { / 
Company B 96 FIN Kodak 1443 (CIR-pos.) S3a 20um ol | o 
Company B 911 FIN Kodak 1443 (CIR-pos.) S3b 20 pm | ut run |[- s i 
Company B 608 FIN Kodak 1443 (CIR-pos.) S3b 14um CIR-positive -film CIR-negative-film 
6000000 6000000 
  
  
  
  
5000000 4 
5000000 
4000000 j| | 4000000 1—— 
3000000 —8 3000000 
2000000 4-:——— 2000000 
1000000 1000000 
  
04 
  
   
  
  
  
  
Figure 2. Histograms of different types of films. 
this peak was often situated on the darker half and in CIR- 
films on the brighter half of histograms. The latter could be 
explained by the strong near-infrared and green reflectance of 
vegetation. In CIR-films bimodal histograms may appear if 
there are large water areas on the image. Example histograms 
of different types of films are presented in figure 2. 
4.0 QC of Scanned images 
Data from the Company A image server were calculated with 
the first version of HISTOQC-program, so only R, G and B — 
histograms and their statistics were gathered. Data from the 
Company B image server included also the L-histograms. 
In the analysis the histogram material was classified to image- 
detailed (Figure 3), flight-detailed (Figure 5) and film- and 
scanner-type-detailed data (Figure 4). According to studies of 
these histograms, the most important statistics for the QC were 
efficiency, saturation (0% & 255%) and 99%-efficiency. In the 
ideal situation, efficiency of all histograms in 8-bit data would 
be 256 and there would be only a small amount of 0 and 255 
DNs. Because the scanning process is such that several images 
are scanned using the same parameters, some compromises 
have to be accepted, and full utilization of histogram cannot be 
obtained. Also the averages and standard deviations of 
        
	        
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