Skip to main content
Springer Nature Link
Log in

Multispectral Image Denoising Based on Non-local Means and Bilateral Filtering

  • Conference paper
  • First Online:
Internet Multimedia Computing and Service (ICIMCS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 819))

Included in the following conference series:

  • 1431 Accesses

Abstract

Multispectral images are obtained by taking multiple images of the different wave bands of the same target, which provides a more comprehensive and clearer description of the scene. However, in practice, multispectral images are always degraded by various types of noise. In this paper, an image denoising method based on non-local means and bilateral filtering is proposed. The method uses the non-local means algorithm to denoise the image, and then uses the bilateral filter to enhance it. The proposed method is compared with the BM3D denoising algorithm, non-local means algorithm and bilateral filtering. The experimental results show that the proposed method not only improves the visual effect but also the value of structural similarity and feature similarity.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /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
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    http://www1.cs.columbia.edu/CAVE/databases/multispectral.

References

  1. Xie, Q., Zhao, Q., Meng, D., et al.: Multispectral images denoising by intrinsic tensor sparsity regularization. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1692–1700 (2016)

    Google Scholar 

  2. Peng, H., Rao, R., Dianat, S.A.: Multispectral image denoising with optimized vector bilateral filter. IEEE Trans. Image Process. 23(1), 264–273 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  3. Scheunders, P.: Denoising of multispectral images using wavelet thresholding, vol. 5238 (2003)

    Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  5. Buades, A., Coll, B., Morel, J.M.: A non-local algorithm for image denoising. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 60–65 (2005)

    Google Scholar 

  6. Xizheng, C.: Image denoising algorithm based on edge preservation. Xidian University (2014)

    Google Scholar 

  7. Zhang, Z., Wang, W.: An improved bilateral filtering algorithm. J. Image Graph. 14(3), 443–447 (2009)

    Google Scholar 

  8. Zhang, H., Tan, J.: Improved bilateral filtering algorithm. J. Hefei Univ. Technol. (Nat. Sci.) (9), 1059–1062 (2014)

    Google Scholar 

  9. He, J., Li, Y.: An image quality evaluation based on structural similarity. J. Changchun Univ. Sci. Technol. (Nat. Sci. Ed.) (3), 105–108 (2014)

    Google Scholar 

  10. Miao, Y., Yi, S., He, J., et al.: Feature similarity image quality evaluation based on gradient information. J. Image Graph. 20(6), 749–755 (2015)

    Google Scholar 

Download references

Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61370138, 61572077, 61271435, and U1301251) and Beijing Municipal Natural Science Foundation (Grant Nos. 4152017 and 4162027).

Author information

Authors and Affiliations

  1. Beijing Key Laboratory of Information Services Engineering, Beijing Union University, Beijing, 100101, China

    Xueyan Zhen & Yuqing Zhang

  2. College of Intellectualized City, Beijing Union University, Beijing, 100101, China

    Ning He & Xin Sun

Authors
  1. Xueyan Zhen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ning He
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xin Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuqing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ning He .

Editor information

Editors and Affiliations

  1. Multimedia Communications Department, EURECOM, Sophia Antipolis, France

    Benoit Huet

  2. Shandong University , Qingdao, China

    Liqiang Nie

  3. Hefei University of Technology , Hefei, China

    Richang Hong

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhen, X., He, N., Sun, X., Zhang, Y. (2018). Multispectral Image Denoising Based on Non-local Means and Bilateral Filtering. In: Huet, B., Nie, L., Hong, R. (eds) Internet Multimedia Computing and Service. ICIMCS 2017. Communications in Computer and Information Science, vol 819. Springer, Singapore. https://doi.org/10.1007/978-981-10-8530-7_37

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-8530-7_37

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8529-1

  • Online ISBN: 978-981-10-8530-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation