Skip to main content

Contrast Stretching Techniques for Enhancement of Mammograms

  • Chapter
  • First Online:
Non-Linear Filters for Mammogram Enhancement

Part of the book series: Studies in Computational Intelligence ((SCI,volume 861))

Abstract

Contrast stretching techniques deal with manipulation of grey-levels of an image that do not properly incur utilization of the dynamic range of the display system. These are spatial processing techniques which modify or enhance the contrast of the image to yield a visually better image for specific application.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

Institutional subscriptions

References

  • S.A. Ahmad, M.N. Taib, N.E.A. Khalid, H. Taib, An analysis of image enhancement techniques for dental X-ray image interpretation. Int. J. Mach. Learn. Comput. 2(3), 292–297 (2012)

    Google Scholar 

  • S. Anand, S. Gayathri, Mammogram image enhancement by two-stage adaptive histogram equalization. Optik—Int. J. Light. Electron Opt. 126(21), 3150–3152 (2015)

    Article  Google Scholar 

  • V. Bhateja, M. Misra, S. Urooj, Unsharp masking approaches for hvs based enhancement of mammograms: a comparative evaluation. Futur. Gener. Comput. Syst. 82 176–189 (2018)

    Google Scholar 

  • A.C. Bovik, Handbook of Image and Video Processing, 2nd edn. (Elsevier Academic Press, Amsterdam, 2010)

    Google Scholar 

  • S. Chiandussi, G. Ramponi, Nonlinear unsharp masking for the enhancement of document images, in Proceedings of IEEE 8th European Signal Processing Conference (EUSIPCO-1996) (Trieste, Italy, 1996), pp. 1–4

    Google Scholar 

  • A.P. Dhawan, G. Buelloni, R. Gordon, Enhancement of mammographic features by optimal adaptive neighborhood image processing. IEEE Trans. Med. Imaging 5(1), 8–15 (1986)

    Article  Google Scholar 

  • T.L. Economopoulos, P.A. Asvestas, G.K. Matsopoulos, Contrast enhancement of images using partitioned iterated function systems. Image Vis. Comput. 28(1), 45–54 (2010)

    Article  Google Scholar 

  • R.C. Gonzalez, R.E. Woods, Digital Image Processing, 3rd edn. (Prentice Hall, USA, 2007)

    Google Scholar 

  • R. Gordon, R.M. Rangayyan, Feature enhancement of film mammograms using fixed and adaptive neighborhoods. Appl. Opt. 23(4), 560–564 (1984)

    Article  Google Scholar 

  • S. Jenifer, S. Parasuraman, A. Kadirvelu, Contrast enhancement and brightness preserving of digital mammograms using fuzzy clipped contrast-limited adaptive histogram equalization algorithm. Appl. Soft Comput. 42, 167–177 (2016)

    Article  Google Scholar 

  • L. Kanelovitch, Y. Itzchak, A. Rundstein, M. Sklair, H. Spitzer, Biologically derived companding algorithm for high dynamic range mammography images. IEEE Trans. Biomed. Eng. 60(8), 2253–2261 (2013)

    Article  Google Scholar 

  • J.K. Kim, J.M. Park, K.S. Song, H.W. Park, Adaptive mammographic image enhancement using first derivative and local statistics. IEEE Trans. Med. Imaging 16(5), 495–502 (1997)

    Article  Google Scholar 

  • G. Kom, A. Tiedeu, M. Kom, Automated detection of masses in mammograms by local adaptive thresholding. Comput. Biol. Med. 37(1), 37–48 (2007)

    Article  Google Scholar 

  • P. KuÅŸ, Ä°. Karagöz, Detection of micro-calcification clusters in digitized X-ray mammograms using unsharp masking and image statistics. Turk. J. Electr. Eng. & Comput. Sci. 21(1), 2048–2061 (2013)

    Google Scholar 

  • Y.H. Lee, S.Y. Park, A study of convex/concave edges and edge-enhancing operators based on the laplacian. IEEE Trans. Circuits Syst. 37(7), 940–946 (1990)

    Article  MathSciNet  Google Scholar 

  • S.K. Mitra, H. Li, I. Li, T-H. Yu, A new class of non-linear filters for image enhancement, in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, (ICASSP-1991) (Toronto, Canada, 1991), pp. 2525–2528

    Google Scholar 

  • K.A. Panetta, Z. Yicong, S.S. Agaian, H. Jia, Non-linear unsharp masking for mammogram enhancement. IEEE Trans. Inf. Technol. Biomed. 15(6), 918–928, (2011)

    Article  Google Scholar 

  • F. Pellegrino, W. Vanzella, V. Torre, Edge detection revisited. IEEE Trans. Syst., Man, Cybernetics—Part B: Cybern., 34(3), 1500–1518 (2004)

    Article  Google Scholar 

  • N. Petrick, H.-P. Chan, B. Sahiner, D. Wei, An adaptive density-weighted contrast enhancement filter for mammographic breast mass detection. IEEE Trans. Med. Imaging 15(1), 59–67 (1996)

    Article  Google Scholar 

  • E.D. Pisano, S. Zong, B.M. Hemminger, M. Deluca, R.E. Johnston, K. Muller, M.P. Braeuning, S.M. Pizer, Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms. J. Digit. Imaging 11(4), 193–200 (1998)

    Article  Google Scholar 

  • A. Polesel, G. Ramponi, V.J. Mathews, Image enhancement via adaptive unsharp masking. IEEE Trans. Image Process. 9(3), 505–510 (2000)

    Article  Google Scholar 

  • W.K. Pratt, Image enhancement, in Digital Image Processing, 4th edn. (PIKS Scientific Inside, 2001), pp. 247–305

    Google Scholar 

  • G. Ramponi, A cubic unsharp masking technique for contrast enhancement. Signal Process. 67(2), 211–222 (1998)

    Article  Google Scholar 

  • G. Ramponi, A. Polesel, Rational unsharp masking technique. J. Electron. Imaging 7(2), pp. 333–338 (1998)

    Article  Google Scholar 

  • G. Ramponi, G.L. Sicuranza, Image sharpening using a polynomial operator, in Proceedings of IEEE European Conference on Circuit Theory and Design (ECCTD-1993) (Davos, Switzerland, 1993), pp. 1431–1436

    Google Scholar 

  • R.M. Rangayyan, L. Shen, Y. Shen, J.E.L. Desautels, H. Bryant, T.J. Terry, N. Horeczko, M.S. Rose, Improvement of sensitivity of breast cancer diagnosis with adaptive neighborhood contrast enhancement of mammograms. IEEE Trans. Inf. Technol. Biomed. 1(3), 161–170 (1997)

    Article  Google Scholar 

  • J. Rogowska, K. Preston and D. Sashin, Evaluation of digital unsharp masking and local contrast stretching as applied to chest radiology. IEEE Trans. Biomed. Eng. 35(10), 817–827 (1988).

    Article  Google Scholar 

  • J.A. Stark, Adaptive image contrast enhancement using generalizations of histogram equalization. IEEE Trans. Image Process. 9(5), 889–896 (2000)

    Article  Google Scholar 

  • M. Sundaram, K. Ramar, N. Arumugam, G. Prabin, Histogram modified local contrast enhancement for mammogram images. Appl. Soft Comput. 11(8), 5809–5816 (2011)

    Article  Google Scholar 

  • Z. Wu, J. Yuan, B. Lv, X. Zheng, Digital mammography image enhancement using improved unsharp masking approach, in Proceedings of IEEE 3rd International Congress on Image and Signal Processing (Yantai, China, 2010), pp. 668–671

    Google Scholar 

  • J.B. Zimmerman, S.M. Pizer, E.V. Staab, J.R. Perry, W. Mccartney, B.C. Brenton, An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement. IEEE Trans. Med. Imaging 7(4), 304–312 (1988)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vikrant Bhateja .

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Bhateja, V., Misra, M., Urooj, S. (2020). Contrast Stretching Techniques for Enhancement of Mammograms. In: Non-Linear Filters for Mammogram Enhancement. Studies in Computational Intelligence, vol 861. Springer, Singapore. https://doi.org/10.1007/978-981-15-0442-6_5

Download citation

Publish with us

Policies and ethics