Skip to main content

Image Denoising Using Various Image Enhancement Techniques

  • 898 Accesses

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1172)

Abstract

The main aim of the image enhancement technique is to process any image given as input and to obtain the resultant outcome more accurately than the existing image. The level of accuracy of an image can be restored in different forms using image enhancement techniques. The choices of choosing different image enhancement techniques may vary depending upon the quality of the picture, task, and atmospheric conditions. The different algorithms used for enhancement and the concepts are discussed in this paper. The frequency and spatial domain of the image can be enhanced by using these processes.

Keywords

  • Image enhancement
  • Spatial domain enhancement
  • Frequency domain-based enhancement
  • Histogram equalization

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. R. Maini, H. Aggarwal, A Comprehensive Review of Image Enhancement Techniques

    Google Scholar 

  2. A.K. Jain, Fundamentals of Digital Image Processing (Prentice Hall, Englewood Cliffs, NJ, 1989)

    MATH  Google Scholar 

  3. S.M. Pizer et al., Adaptive histogram equalization and its variations. Comput. Vis. Graph. Image Process. 39, 355–368 (1987)

    CrossRef  Google Scholar 

  4. R.C. Gonzalez, R.E. Woods, Digital Image Processing (Prentice Hall, Upper Saddle River, New Jersey, 2002)

    Google Scholar 

  5. R. Jain, R. Kasturi, B.G. Schunck, Machine Vision (McGraw-Hill International Edition, 1995)

    Google Scholar 

  6. H. Lidong, Z. Wei, W. Jun, S. Zebin, Combination of Contrast Limited Adaptive Histogram Equalisation and Discrete Wavelet Transform for Image Enhancement (2014)

    Google Scholar 

  7. H.C. Andrews, Digital image restoration: a survey. Computer 7(5), 36–45 (1974)

    CrossRef  Google Scholar 

  8. Y. Yao, B. Abidi, M. Abidi, Digital Imaging with extreme Zoom: System Design and Image Restoration

    Google Scholar 

  9. R. Hummel, Histogram modification techniques. Comput. Graph. Image Process. 4, 209–224 (1975)

    CrossRef  MathSciNet  Google Scholar 

  10. G.L. Anderson, A.N. Netravah, Image restoration based on a subjective criterion. IEEE Trans. Syst. Man Cybern. SMC-6, 845 (1976)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. P. Premnath .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2021 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Premnath, S.P., Arokia Renjith, J. (2021). Image Denoising Using Various Image Enhancement Techniques. In: Dash, S.S., Das, S., Panigrahi, B.K. (eds) Intelligent Computing and Applications. Advances in Intelligent Systems and Computing, vol 1172. Springer, Singapore. https://doi.org/10.1007/978-981-15-5566-4_16

Download citation