Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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X-Ray Image Enhancement Using a Boundary Division Wiener Filter and Wavelet-Based Image Fusion Approach

  • Khan, Sajid Ullah (Dept. of Computer Science, CECOS University of IT and Emerging Sciences) ;
  • Chai, Wang Yin (Dept. of Computing and Software Engineering, University of Malaysia Sarawak (UNIMAS)) ;
  • See, Chai Soo (Dept. of Computing and Software Engineering, University of Malaysia Sarawak (UNIMAS)) ;
  • Khan, Amjad (Dept. of Statistical and Computer Science, Faculty of Science, University of Peradeniya)
  • Received : 2015.01.16
  • Accepted : 2015.05.28
  • Published : 2016.03.31
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Abstract

To resolve the problems of Poisson/impulse noise, blurriness, and sharpness in degraded X-ray images, a novel and efficient enhancement algorithm based on X-ray image fusion using a discrete wavelet transform is proposed in this paper. The proposed algorithm consists of two basics. First, it applies the techniques of boundary division to detect Poisson and impulse noise corrupted pixels and then uses the Wiener filter approach to restore those corrupted pixels. Second, it applies the sharpening technique to the same degraded X-ray image. Thus, it has two source X-ray images, which individually preserve the enhancement effects. The details and approximations of these sources X-ray images are fused via different fusion rules in the wavelet domain. The results of the experiment show that the proposed algorithm successfully combines the merits of the Wiener filter and sharpening and achieves a significant proficiency in the enhancement of degraded X-ray images exhibiting Poisson noise, blurriness, and edge details.

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References

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