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An improved algorithm based on CLAHE for ultrasonic well logging image enhancement

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Abstract

This study presents a novel image enhancement method in consideration of low contrast and blurred details of ultrasonic well logging images by combining the contrast limited adaptive histogram equalization (CLAHE) with power-law transformation. The red, green, and blue (RGB) color image is first transformed into hue, saturation, and intensity (HSI) space and the CLAHE is applied only to the intensity (or luminance) component (I) of the image. This enhances local details and prevents excess brightness in flat areas and uniform regions while maintaining the chromaticity values of the degraded image. Limitation of the CLAHE technique is that it limits the amplification of contrast by clipping the histogram of every sub-region at a predefined clip-limit. The power-law transformation is then applied to the processed image following the CLAHE processing. This maps a wide range of dark input values into a narrower range of output values, whereas a narrow range of bright input values into a wider range of output values, which further improve the contrast and highlight the local details. Finally, the result is presented as an RGB image. The performance of the proposed technique is compared with histogram equalization and CLAHE methods based on image quality objective measurement tools such as the mean square error (MSE) involving peak signal-to-noise ratio (PSNR), information entropy (IE), and luminance contrast (LC). Experimental results show that the proposed algorithm produces better ultrasonic well logging images than the existing enhancement schemes. The underlying improvement is of great significance for further upgrading the accuracy of sonic imaging logging data interpretation.

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References

  1. Movahed, Z., Radzuan, J., Peter, J.: Evaluate the borehole condition to reduce drilling risk and avoid potential well bore damages by using image logs. Pet. Sci. Eng. 122, 318–330 (2014)

    Article  Google Scholar 

  2. Movahed, Z., et al.: Formation evaluation in Dezful embayment of Iran using oil-based-mud imaging techniques. Pet. Sci. Eng. 121, 23–37 (2014)

    Article  Google Scholar 

  3. Lee, C.W., et al.: Power-constrained contrast enhancement for emissive displays based on histogram equalization. IEEE Trans. Image Process. 21, 80–93 (2012)

    Article  MathSciNet  Google Scholar 

  4. Arici, T., Dikbas, S., Altunbasak, Y.: A histogram modification framework and its application for image contrast enhancement. IEEE Trans. Image Process. 18, 1921–1935 (2009)

    Article  MathSciNet  Google Scholar 

  5. Huang, S.C., Cheng, F.C., Chiu, Y.S.: Efficient contrast enhancement using adaptive gamma correction with weighting distribution. IEEE Trans. Image Process. 22, 1032–1041 (2013)

    Article  MathSciNet  Google Scholar 

  6. Chiu, C.-C., Ting, C.-C.: Contrast enhancement algorithm based on gap adjustment for histogram equalization. Sensors 16, 1–18 (2016)

    Article  Google Scholar 

  7. Yan, J.P., et al.: The method of image dynamic intensify and morphing in imaging log. Well Logging Technol. 30, 364–366 (2006)

    Google Scholar 

  8. Tu, J.H., Yu, H.Q., Li, C.W., Zou, W.: Study of histogram equalization for ultrasonic logging well image. Video Eng. 35, 113–114 (2011)

    Google Scholar 

  9. Kim, J.Y., Kim, L.S., Hwang, S.H.: An advanced contrast enhancement using partially overlapped sub-block histogram equalization. IEEE Trans. Syst. Video Technol. 11, 475–484 (2001)

    Article  Google Scholar 

  10. Wadud, M.A.A., Kabir, M.H., Dewan, M.A., Chae, O.: A dynamic histogram equalization for image contrast enhancement. IEEE Trans. Cons. Electron 53, 593–600 (2007)

    Article  Google Scholar 

  11. Ibrahim, H., Pik Kong, N.S.: Brightness preserving dynamic histogram equalization for image contrast enhancement. IEEE Trans. Cons. Electron. 53, 1752–1758 (2007)

    Article  Google Scholar 

  12. Wang, X.F., et al.: On the method of XRMI dynamic enhancement and full borehole imaging and its application. Well Logging Technol. 39, 432–437 (2015)

    Google Scholar 

  13. Ward, Du Shan, Rabab, K.: Adaptive region-based image enhancement method for robust face recognition under variable illumination conditions. IEEE Trans. Syst. Video Technol. 20, 1165–1175 (2010)

    Article  Google Scholar 

  14. Karel, Z.: Contrast Limited Adaptive Histogram Equalization, pp. 474–485. Press Professional, Inc., Randallstown (1994)

    Google Scholar 

  15. Reza, A.M.: Realization of the contrast limited adaptive histogram equalization (CLAHE) for real-time image enhancement. J. VLSI Sig. Proc. 38, 35–44 (2004)

    Article  Google Scholar 

  16. Zohair, A.A., et al.: An innovative technique for contrast enhancement of computed tomography images using normalized gamma-corrected contrast-limited adaptive histogram equalization”. EURASIP J. Adv. Signal Process. 1, 1–12 (2015)

    Google Scholar 

  17. Yang, Y., Li, B.: A method of document image enhancement based on the combination Of CLAHE and detail amplifying. J. Image Gr. 16, 522–527 (2011)

    Google Scholar 

  18. Huang, L.D., et al.: Combination of contrast limited adaptive histogram equalisation and discrete wavelet transform for image enhancement. IET Image Process 9, 908–915 (2015)

    Article  Google Scholar 

  19. Sheeba, J., Parasuraman, S., Kadirvelu, A.: 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 

  20. Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn, pp. 88–94. Publishing House of Electronics Industry, Beijing (2007)

    Google Scholar 

  21. Babu, P., Rajamani, V.: Contrast enhancement using real coded genetic algorithm based modified histogram equalization for gray scale images. Int. J. Imag. Syst. Technol. 25, 24–32 (2015)

    Article  Google Scholar 

  22. Song, W.Q., et al.: Segmentation algorithm for SAR images based on power transformation. Syst. Eng. Electr. 37, 1504–1511 (2015)

    Google Scholar 

  23. Zhang, D.F.: Matlab digital image processing, pp. 213–218. Publishing house of electronics industry, Beijing (2012)

    Google Scholar 

Download references

Acknowledgements

The authors wish to thank the reviewers for their valuable suggestions. This work was supported in part by The National Natural Science Foundation of China (Nos. 51604038, 51541408) and the Education Department of Hubei Province, China (D20141303).

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Authors and Affiliations

  1. School of Electronics and Information Engineering, Yangtze University, Jingzhou, 434023, China

    Qingqing Fu & Aiping Wu

  2. National Demonstration Center for Experimental Electrical & Electronical Education, Yangtze University, Jingzhou, China

    Qingqing Fu & Aiping Wu

  3. School of Electrical Engineering and Computer Science, Ohio University, Athens, OH, 45701, USA

    Mehmet Celenk

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  1. Qingqing Fu
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  2. Mehmet Celenk
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  3. Aiping Wu
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Correspondence to Aiping Wu.

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Fu, Q., Celenk, M. & Wu, A. An improved algorithm based on CLAHE for ultrasonic well logging image enhancement. Cluster Comput 22 (Suppl 5), 12609–12618 (2019). https://doi.org/10.1007/s10586-017-1692-8

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  • DOI: https://doi.org/10.1007/s10586-017-1692-8

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