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Histogram image enhancement using a limited wavelet integer coefficient

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Abstract

Histogram equalization plays an important role in digital image preprocessing. However, traditional histogram equalization tends to have technical defects such as over-enhancement and artifacts. This can lead to a loss of detail and make the target image look unnatural. To resolve this issue, this paper presents an approach to image enhancement that uses a limited wavelet integer coefficient histogram to maintain high information entropy. First, a single-layer wavelet transform is performed on the input image to obtain a low-frequency sub-image and three high-frequency sub-images. Then, the low-frequency sub-image is subjected to a histogram-limitation technique to acquire the wavelet integer coefficients. After this, the processed low-frequency and three high-frequency sub-images are reconstructed to output a single high-information enhanced image. An experiment was conducted that shows that the proposed method performs very well in terms of the amount of detailed information captured when compared to an existing improved method based on histogram equalization. In addition, the method can handle the enhancement of images across different dynamic ranges, especially images with narrow a dynamic range, thus improving the amount of detailed information in the output image and maximizing the visual effect for human observers.

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References

  1. Celik T, Tjahjadi T (2012) Automatic image equalization and contrast enhancement using gaussian mixture modeling. IEEE Trans Image Process 21(1):145–156

    Article  MathSciNet  MATH  Google Scholar 

  2. Chen YB (2017) Local linear enhancement of luminance histogram of color remote sensing image. Opt Precis Eng 25(2):502–508

    Article  Google Scholar 

  3. Chen SD, Ramli R (2003) Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation. IEEE Trans Consum Electron 49(4):1301–1309

    Article  Google Scholar 

  4. Chen SD, Ramli AR (2003) Minimum mean brightness error bi-histogram equalization in contrast enhancement. IEEE Trans Consum Electron 49:1310–1319

    Article  Google Scholar 

  5. Cheng L (2011) A fast algorithm for foggy image contrast enhancement. In: Proceedings of conference on transportation, mechanical and electrical engineering, Changchun, China, pp 455–458

  6. Hassan VM, Ali A, Yasser B (2018) Optimized watermarking technique using self-adaptive differential evolution based on redundant discrete wavelet transform and singular value decomposition. Expert Syst Appl 114:296–312

    Article  Google Scholar 

  7. Hedayati KS (2018) Monitoring of wound rotor induction machines by means of discrete wavelet transform. Electr Power Compon Syst 46(19–20):2021–2035

    Google Scholar 

  8. Huang S, Cheng F, Chiu Y (2013) Efficient contrast enhancement using adaptive gamma correction with weighting distribution. IEEE Trans Image Process 22(3):1032–1041

    Article  MathSciNet  MATH  Google Scholar 

  9. Jiang BJ, Zhong MX (2014) Improved histogram equalization algorithm in the image enhancement. Laser Infrared 44(6):703–706

    Google Scholar 

  10. Kanmani M, Narsimhan V (2018) An image contrast enhancement algorithm for grayscale images using particle swarm optimization. Multimed Tools Appl 77:23371–23387

    Article  Google Scholar 

  11. Khan M, Khan F (2012) Weighted average multi segment histogram equalization for brightness preserving contrast enhancement. In: Proceedings of IEEE international conference on signal processing, computing and control, pp 1–6

  12. Kim YT (1997) Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Trans Consum Electron 4(3):1–8

    Google Scholar 

  13. Li GF, Li GJ, Han GL et al (2018) Illumination compensation using Retinex model based on bright channel prior. Opt Precis Eng 26(5):1191–1200

    Article  Google Scholar 

  14. Liu SL, Rahman MA, Lin CF, Wong CY, Jiang GN, Liu SC, Kwok N, Shi HY (2017) Image contrast enhancement based on intensity expansion-compression. J Vis Commun Image Represent 48:169–181

    Article  Google Scholar 

  15. Lu CH, Hsu HY, Wang L (2009) A new contrast enhancement technique by adaptively increasing the value of histogram. In: IST 2009 - international workshop on imaging systems and techniques, Shenzhen, China, May 11-12, pp 402–405

  16. Ooi CH, Mat Isa NA (2010) Adaptive contrast enhancement methods with brightness preserving. IEEE Trans Consum Electron 56:2543–2551

    Article  Google Scholar 

  17. Ooi CH, Mat Isa NA (2010) Quadrants dynamic histogram equalization for contrast enhancement. IEEE Trans Consum Electron 56:2552–2559

    Article  Google Scholar 

  18. Ooi CH, Kong NSP, Ibrahim H (2009) Bi-histogram equalization with a plateau limit for digital image enhancement. IEEE Trans Consum Electron 55:2072–2080

    Article  Google Scholar 

  19. Santhi K, Wahida Banu RSD (2015) Adaptive contrast enhancement using modified histogram equalization. Optik -Int J Light Electron Opt 126:1809–1814

    Article  Google Scholar 

  20. Sim KS, Tso CP, Tan YY (2007) Recursive sub-image histogram equalization applied to gray scale images. Pattern Recognit Lett 28:1209–1221

    Article  Google Scholar 

  21. Singh K, Kapoor R (2014) Image enhancement using exposure-based sub-image histogram equalization. Pattern Recogn Lett 36:10–14

    Article  Google Scholar 

  22. Tang JR, Mat Isa NA (2017) Bi-histogram equalization using modified histogram bins. Appl Soft Comput 55:31–43

    Article  Google Scholar 

  23. Thakkar FN, Srivastava VK (2017) A blind medical image watermarking: DWT-SVD based robust and secure approach for telemedicine applications. Multimed Tools Appl 76:3669–3697

    Article  Google Scholar 

  24. Wang XW, Chen LX (2017) An effective histogram modification scheme for image contrast enhancement. Signal Process Image Commun 58:187–198

    Article  Google Scholar 

  25. Wang Y, Pan ZB (2017) Image contrast enhancement using adjacent-blocks-based modification for local histogram equalization. Infrared Phys Technol 86:59–65

    Article  Google Scholar 

  26. Wang Y, Zhang B (1999) Image enhancement based on equal area dualistic sub image histogram equalization method. IEEE Trans Consum Electron 45(1):68–75

    Article  Google Scholar 

  27. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image qualifty assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612

    Article  Google Scholar 

  28. Xiao B, Tang H, Jiang YJ, Li WS, Wang GY (2018) Brightness and contrast controllable image enhancement based on histogram specification. Neurocomputing 275:2798–2809

    Article  Google Scholar 

  29. Xie XF, Zhou J, Wu QZ (2010) No-reference quality index for image blur. J Comput Appl 30(4):921–924

    Google Scholar 

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Acknowledgements

The authors would like to express their gratitude to EditSprings (https://www.editsprings.com/) for the expert linguistic services provided. This project is supported by the Natural Science Fund Project of Colleges in Jiangsu Province(grant number 18KJB520012).

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Authors and Affiliations

  1. Information Center, Jiangsu University of Technology, Changzhou, People’s Republic of China

    Haifeng Wang & Yi Zhang

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  1. Haifeng Wang
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  2. Yi Zhang
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Correspondence to Haifeng Wang.

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Wang, H., Zhang, Y. Histogram image enhancement using a limited wavelet integer coefficient. Multimed Tools Appl 82, 14879–14896 (2023). https://doi.org/10.1007/s11042-022-14060-y

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