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ProcediaEngineering
Procedia Engineering 00 (2010) 000–000
www.elsevier.com/locate/procedia
2010 Symposium on Security Detection and Information Processing
Image noise reduction based on superposition algorithm used in X-
ray imager
Liang Wang , Xiaofeng Jin, Yunjian Fei
Beijing Heweiyongtai Sci & Tech Co.Ltd, Shijingshan District,BeiJing,100043,China
Abstract
Now, the X-ray detection technique is used popularly in security inspection. using this technique, shadows of guns or knives are
showed clearly to the inspector. Besides, this technique can be controlled easily, and it is safe to people generally. Because of
these, the X-ray technique is more and more important in security inspection[1]. When the X-ray penetrates several objects with
different thickness and different density, we will get a gray image from imager. The nonuniformity and discontinuity of X-ray
will bring noise, this noise seems to be grain, it will damage image and make inspector uncomfortable. The paper mainly
introduces two superposition algorithms to process this noise but do not damage the original image, and the inclusions tell us the
process is very effective.
Keywords: X-ray, Superposition algorithm, Image process, Noise
1. The theory of X-ray image system
X-ray can be used in nondestructive inspection because of its penetrability[4], besides, it has any other
characteristics, such as fluorescence and photography[2]. The different object has different density and different
absorbing capacity of X-ray, and transmission energy is also different, so we can get images with different gray[5].
Fig 1. X-ray imager elements frame
Corresponding author. Tel.: 010-51712630; fax: 010-51712717.
E-mail address: king@heweigroup.com
c⃝ 2010 Published by Elsevier Ltd.
Procedia Engineering 7 (2010) 286–289
www.elsevier.com/locate/procedia
1877-7058 c⃝ 2010 Published by Elsevier Ltd.doi:10.1016/j.proeng.2010.11.046
Liang Wang, Xiaofeng Jin, Yunjian Fei / Procedia Engineering 00 (2010) 000–000
2. Introduce the noise and ways of noise reduction
There are several reasons for noise generation. The first one, X-ray is nonuniform; the second one, screen’s
luminous reflectance and its smoothness are nonuniform; the last one, data transmission may bring image noise. In
the paper, we mainly process the noise generated because light intensity is not enough. The noise is random, the
image will be fuzzy if we use median filter algorithm[3] to reduce the noise, so we choose superposition algorithm
to reduce the noise. The fig 2 shows the X-ray image with noise to you.
Fig 2. Take a picture by X-ray technique
3. Algorithm implementation inVC
3.1 Three points’ superposition
This algorithm superposes three points in corresponding three images, images’ names are image1.bmp,
image2.bmp and image3.bmp, the image processed is saved as image4.bmp. The variable image(data) points to the
image’s pixel, so the calculation is:
image4(data)=image1(data)/3+image2(data)/3+image3(data)/3.
The corresponding code in VC is:
First , find three images you want to process, and define the path of image4.bmp.
CString strSavePath=strPath+"temp1.bmp";
CString strSavePath1=strPath+"temp2.bmp";
CString strSavePath2=strPath+"temp3.bmp";
CString strSavePath3=strPath+"temp4.bmp";
Second, read these images, and save their pixels in variable imgdata1 imgdata2 and imgdata3.
Img1.Read(strSavePath1);
Imgdata1=Img1.m_pImgData;
Img2.Read(strSavePath2);
Imgdata2=Img2.m_pImgData;
Img3.Read(strSavePath3);
Imgdata3=Img3.m_pImgData;
In the end, begin to calculate, get the pixel of a image, and save it in array m[] generate image4.bmp file.
L. Wang et al. / Procedia Engineering 7 (2010) 286–289 287
Liang Wang, Xiaofeng Jin, Yunjian Fei / Procedia Engineering 00 (2010) 000–000
for(i=0;i<921600;i++)
{
m[i]=(imgdata1[i]/3)+(imgdata2[i]/3)+(imgdata3[i]/3);
}
Img4.Write(strSavePath4);
Fig 3. An original picture and the picture processed
3.2 twenty-seven points’ superposition
This algorithm superposes twenty-seven points in corresponding three images, these points include current point
and other 8 points around it in the same image and corresponding points in other two images. The fig 4 shows you
position of 27 points.
Fig 4. Position of the twenty-seven points
This algorithm uses more points to calculate, it is more effective than the first algorithm, and it can be used in
processing video, only video with moveless objects. The paper introduces a equation to enhance contrast:
)(xMky (1)
The variable x is the gray value of current point, is the average of a image’s gray, is the variance of current
point neighboring area, the neighborhood size is 33 . K is a coefficient. This equation is a common one, if the
contrast value is low( is low), the gray value after calculation will be improved, oppositely the gray value will be
reduced. This method would aggravate noise, so it is not suitable for us. We need to change the equation as:
Mkxky 21 )(
(2)
288 L. Wang et al. / Procedia Engineering 7 (2010) 286–289
Liang Wang, Xiaofeng Jin, Yunjian Fei / Procedia Engineering 00 (2010) 000–000
Fig 5. An original picture and the picture processed with 27 points’ superposition
4. Conclusions
The paper introduces two superposition algorithm used in image noise processing, the algorithm improves
images’ definition, and reduce noise which raises in dark section, then it supplies a technique for deeper research on
image noise. Now, this algorithm has been used in X-ray imager, in future, we need to do deeper research on video
noise processing.
References
[1] Wang T.W., Evans J.P.O. Sterescopic dual-energy x-ray imaging for target materials identification. IEEProc Vis Image Signal Process 2003;150(2):122-130.
[2] Shi XinHua. Improving Object Classification in X-ray Luggage Inspection[D], Doctor Dissertation, 2000:27-28.
[3] Kenneth R.Castleman. Digital Image Process. Electronic Industry publish; 2003.
[4] S.Cadeddu, D.Caredda, and M.Caria. Pharos. A Spectrometer -on-a-chip for digital radiology systems with
spectral detection. Nuclear Instruments and Methods in Physics Research A 2002; 478:367-371.
[5] Richard D.R. Macdonald. Design and Implementation of a Dual-Energy X-ray imaging system for Organic
Material Detection in an Airport Security Application. Machine Vision Application in Industrial Inspection 2001;
43(1):31-41.
L. Wang et al. / Procedia Engineering 7 (2010) 286–289 289
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