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An effective and flexible image enhancement algorithm in compressed domain

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Abstract

Images with JPEG format using discrete cosine transform (DCT) is selected for most popular compression standards. Enhancement in the compressed domain offers two major advantages, including low computational complexity and storage space. However, the compression is achieved by block-based transform; therefore, it is hard to enhance image globally. In this paper, the main issue is to develop a global enhancement method that effectively reduces the introduced blocking artifacts and achieves excellent visual quality of enhancement. We propose a combined DCT matrix representation, which consists of 8n × 8n pixel arrays, to enhance the global information on images for removing block artifacts in compressed-domain. In addition, we propose the multi-enhancement factors based on spatial frequency for image enhancement in compressed domain. From the simulation results, the proposed method achieves not only excellent improvement for image enhancement but also reducing the blocking artifacts significantly.

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References

  1. Amore M, Mitra SK, Carli M, McElvain JS (2007) Image enhancement in the compressed domain. Int Symp Signals, Circ Syst 2(13–14):1–4

    Google Scholar 

  2. Atta R, Ghanbari M (2013) “Low-contrast satellite images enhancement using discrete cosine transform pyramid and singular value decomposition”. IET Image Process 7(5):472–483

    Article  Google Scholar 

  3. Ghimire D, Lee J (2011) Nonlinear transfer function-based local approach for color image enhancement. IEEE Trans Consum Electron 57(2):858–865

    Article  Google Scholar 

  4. Jen TC, Wang SJ (2012) Bayesian structure-preserving image contrast enhancement and its simplification. IEEE Trans on Circ Syst Vi Technol 22(6):831–843

    Article  Google Scholar 

  5. Jobson DJ, Rahman Z, Woodell GA (2002) “Statistics of visual representation,” Proc. SPIE Conf. on Visual Information Processing XI, Orlando, FL, USA, 25–35

  6. Kim T, Paik J (2008) Adaptive contrast enhancement using gain-controllable clipped histogram equalization. IEEE Trans Consum Electron 54(4):1803–1810

    Article  Google Scholar 

  7. Kogan R, Agaian SS, Panetta K (1998) “Visualization using rational morphology and zonal magnitude-reduction,”. Proc SPIE 3304:153–163

    Article  Google Scholar 

  8. Konstantinides K, Bhaskaran V, Beretta G (1999) Image sharpening in the JPEG domain. IEEE Trans Image Process 8(6):874–878

    Article  Google Scholar 

  9. Kumar A, Bhandari AK, Padhy P (2012) “Improved normalised difference vegetation index method based on discrete cosine transform and singular value decomposition for satellite image processing”. IET Signal Process 6(7):617–625

    Article  MathSciNet  Google Scholar 

  10. Lee S (2007) An efficient content-based image enhancement in the compressed domain using retinex theory. IEEE Trans Circ Syst Vi Technol 17(2):199–213

    Article  Google Scholar 

  11. Lee S (2006) Content-based image enhancement in the compressed domain based on multi-scale alpha-rooting algorithm. Pattern Recogn Lett 27(10):1054–1066

    Article  Google Scholar 

  12. Lee JH, Lee JM, Park KT, Moon YS (2012) “Magnification by modifying DCT coefficients”, 2012 I.E. Int Conf Consum Electron, pp120-121

  13. Mukherjee J, Mitra SK (2008) “Enhancement of color images by scaling the DCT coefficients,”. IEEE Trans Image Process 17(10):1783–1794

    Article  MathSciNet  Google Scholar 

  14. Ooi CH, Mat Isa NA (2010) “Quadrants dynamic histogram equalization for contrast enhancement,”. IEEE Trans Consum Electron 56(4):2552–2559

    Article  Google Scholar 

  15. Panetta K, Xia J, Agaian S (2012) Color image enhancement based on the discrete cosine transform coefficient histogram”. J Elec Imaging 21(2):1–11

    Article  Google Scholar 

  16. Peli E (1990) Contrast in complex images. J Opt Soc Am A 7:2032–2040

    Article  Google Scholar 

  17. Rahmany ZU, Jobsonz DJ, Woodell GA (2004) Retinex processing for automatic image enhancement. J Elec Imaging 13(1):100–110

    Article  Google Scholar 

  18. Rizzi A, Gatta C, Marini D (2003) A new algorithm for unsupervised global and local color correction. Pattern Recogn Lett 24:1663–1677

    Article  Google Scholar 

  19. Sengar PS, Rawat TK, Parthasarathy H (2013), “Color image enhancement by scaling the discrete wavelet transform coefficients”, Int Conf Microelectron Commun Renew Energy, pp.1-6

  20. Singh TR, Roy S, Singh KM (2013) “Global DCT domain power law transformations in image enhancement technique”, 2013 I.E. Int Symp Comput Bus Intell (ISCBI), pp. 269–273

  21. Tang J, Kim J, Peli E (2004) Image enhancement in the JPEG domain for people with vision impairment. IEEE Trans Biomed Eng 51(11):2013–2023

    Article  Google Scholar 

  22. Tang J, Peli E, Acton S (2003) Image enhancement using a contrast measure in the compressed domain. IEEE Signal Proc Lett 10(10):289–292

    Article  Google Scholar 

  23. Tsai CY (2012) A fast dynamic range compression with local contrast preservation algorithm and its application to real-time video enhancement. IEEE Trans Multimedia 14(4):1140–1152

    Article  Google Scholar 

  24. Vale EE, Alcaim A (2008) “Image enhancement in the 2D DCT domain using a band-adaptive contrast modification,” 3rd Int Symp Commun, Control Signal Process (ISCCSP), pp. 1516–1519

  25. Wallace GK (1991) The JPEG still picture compression standard. Commun ACM 34(4):30–44

    Article  Google Scholar 

  26. Xia J, Panetta K, Agaian S (2011) “Color image enhancement algorithms based on the DCT domain” 2011. IEEE Int Conf Syst, Man Cybern (SMC), pp. 1496–1501

  27. Xie X, Lam KM (2005) Face recognition under varying illumination based on 2D face shape model. Pattern Recogn 38:221–230

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Science Counsel Granted NSC 102-2221-E-214 -034 -MY2

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Authors and Affiliations

  1. Department of Information Engineering, I-Shou University, Tahsu, 840, Kaohsiung, Taiwan, Republic of China

    Chung-Ming Kuo, Nai-Chung Yang, Chih-Shan Liu, Pi-Yun Tseng & Chi-Kao Chang

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  1. Chung-Ming Kuo
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  2. Nai-Chung Yang
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  3. Chih-Shan Liu
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  4. Pi-Yun Tseng
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  5. Chi-Kao Chang
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Correspondence to Chung-Ming Kuo.

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Kuo, CM., Yang, NC., Liu, CS. et al. An effective and flexible image enhancement algorithm in compressed domain. Multimed Tools Appl 75, 1177–1200 (2016). https://doi.org/10.1007/s11042-014-2363-x

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  • DOI: https://doi.org/10.1007/s11042-014-2363-x

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