Tahle 1. Statistical data of Spatial Domain 
std. max (range) 
filter mean dev 
original 12.51 6.08 40 
LP 3x3 12.51 602 39 
LP 5x5 12.50 601 38 
LP 7x7 12.50 599: 37 
LP 9x9 12.50 597. 3% 
MED 3x3 12.59 6.03 39 
MED 5x5 12.59 6.02. 38 
MED 7x7 13.50 601" 33 
MED 9x9 12.58 $99. 37 
MODE 3x3 12.60 6.04 40 
MODE 5x5 12.61 6.04 40 
MODE 7x7 12.60 6.04 40 
MODE 9x9 12.60 6.03 40 
Table 2. Statistical data of frequency Domain 
FFT filter mean std. dev max (range) 
original 12.51 6.08 40 
0.25 inch 106.80 43.35 254 
0.5 inch 93.59 39.62 254 
0.75 inch 89.16 38.11 253 
1.0 inch 88.25 37.51 253 
1.25 inch 89.22 37.07 255 
1.5 inch 90.00 37.21 255 
1.75 inch 91.26 36.82 255 
2.75 inch 90.37 36.30 254 
Conclusion 
As a result of applying low-pass filters to digital images 
using Imager software, the gray level histogram data is 
generated. The results of applying low-pass filters to an X- 
ray image to remove noise, show that the calculated 
statistics do not vary significantly from filter to filter within 
the spatial or the frequency domain. Also, within the 
spatial domain, the statistics do not vary significantly from 
kernel to kernel, and within the frequency domain, the 
statistics do not vary significantly from cut-off distance to 
another. Filtering in the frequency domain appears to 
maintain image integrity better than that of the spatial 
domain. In conclusion, the conventional noise removal 
techniques both in the spatial and frequency domains may 
not be an effective mean for noise removal in a rejected low 
contrast and noisy X-ray images. However, the final result 
depends mainly on the noise level in the image. Local 
adaptive box filter might be more effective in these case, 
since it tends to remove the noise locally rather than using 
the entire image. 
    
  
  
    
  
  
   
  
  
   
  
   
  
   
   
  
   
  
  
   
   
   
  
   
   
  
  
   
  
   
   
    
   
  
  
   
   
    
   
   
   
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
    
  
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