Removing the Blurring from X-Ray Image Using BM3D Technique

  • Conference paper
  • First Online:
Proceedings of the 6th International Conference on Fundamental and Applied Sciences

Abstract

The x-ray image quality of normal patient is needed to enhance to diagnose accurately. For this reason, block-matching 3D (BM3D) technique is chosen for denoising the x-ray images. The currently the best BM3D denoising system utilizes a white Gaussian noise (WGN) design. The similar 2D x-ray image is converted to 3D data arrays by grou** to improve the sparsity and it is called grou**. Collaborative filtering is a unique method for dealing with these three-dimensional groups. The collaborative filtering reduces noise, demonstrating even the details of image shared by grouped blocks while preserving the crucial unique characteristics from every individual block. After that, the shifted blocks are replaced with new positions. As these blocks coincide, we get a variety of special predictions with each pixel, which we have to combine. The Wiener filtering process is implemented in the transform coefficients to a post-thresholding signal in the present BM3D algorithm for improved noise removal. Wiener filtering of transform domain co-efficient is used based on the properties of x-ray images in terms of PSNR and SNR value. The hard thresholding system is used in previous step to denoise the x-ray image in the utter lack of a ground-truth signal. The performance of BM3D technique is compared with wavelet transform to evaluate image quality.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (Germany)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 93.08
Price includes VAT (Germany)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 117.69
Price includes VAT (Germany)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
EUR 160.49
Price includes VAT (Germany)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Brenner, D.J.: Radiation risks potentially associated with low-dose CT screening of adult smokers for lung cancer. Radiology 231(2), 440–445 (2004)

    Article  Google Scholar 

  2. Brenner, D.J., Hall, E.J.: Computed tomography-an increasing source of radiation exposure. N. Engl. J. Med. 357(22), 2277–2284 (2007)

    Article  Google Scholar 

  3. Mayo, J.R., Kim, K.I., MacDonald, S.L., Johkoh, T., Kavanagh, P., Coxson, H.O., Vedal, S.: Reduced Radiation Dose Helical Chest CT: Effect on Reader Evaluation of Structures and Lung Findings. Radiology 232(3), 749–756 (2004)

    Google Scholar 

  4. Yuan, R., Mayo, J.R., Hogg, J.C., Pare, P.D., McWilliams, A.M., Lam, S., Coxson, H.O.: The effects of radiation dose and CT manufacturer on measurements of lung densitometry. Chest J. 132(2), 617–623 (2007)

    Article  Google Scholar 

  5. Choo, J.Y., Goo, J.M., Lee, C.H., Park, C.M., Park, S.J., Shim, M.S.: Quantitative analysis of emphysema and airway measurements according to iterative reconstruction algorithms: Comparison of filtered back projection, adaptive statistical iterative reconstruction and model-based iterative reconstruction. Eur. Radiol. 24(4), 799–806 (2014)

    Google Scholar 

  6. Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Trans. Image Process. 16(8), 2080–2095 (2007)

    Google Scholar 

  7. Lebrun, M.: An analysis and implementation of the BM3D image denoising method. Image Process. On Line 2, 175–213 (2012)

    Google Scholar 

  8. Gao, J., Chen, Q., Blasch, E.: Image denoising in the presence of non-Gaussian, power-law noise. In: 2012 IEEE National Aerospace and Electronics Conference (NAECON), pp.103–108 (2012)

    Google Scholar 

  9. Matrecano, M., Poggi, G., Verdoliva, L.: Improved BM3D for correlated noise removal. VISAPP 1, 129–134 (2012)

    Google Scholar 

  10. Hoffman, J., Young, S., Noo, F., McNitt-Gray, M.: Technical note: FreeCT wFBP: A robust, efficient, open-source implementation of weighted filtered backprojection for helical, fan-beam CT. Med. Phys. 43(3), 1411–1420 (2016)

    Article  Google Scholar 

  11. Young, S., Kim, H.G., Ko, M.M., Ko, W.W., Flores, C., McNitt-Gray, M.: Variability in CT lung-nodule volumetry: Effects of dose reduction and reconstruction methods. Med. Phys. 42(5), 2679–2689 (2015)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Islam, A., Zainuddin, N., Karim, S.A.B.A. (2021). Removing the Blurring from X-Ray Image Using BM3D Technique. In: Abdul Karim, S.A., Abd Shukur, M.F., Fai Kait, C., Soleimani, H., Sakidin, H. (eds) Proceedings of the 6th International Conference on Fundamental and Applied Sciences. Springer Proceedings in Complexity. Springer, Singapore. https://doi.org/10.1007/978-981-16-4513-6_62

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-4513-6_62

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-4512-9

  • Online ISBN: 978-981-16-4513-6

  • eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)

Publish with us

Policies and ethics

Navigation