Adaptive Enhancement of Underwater Images

  • Jharna Majumdar
  • Aparna Manikonda
  • G. M. Venkatesh
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 221)


Underwater images usually suffer from low contrast and non-uniform lightning. To overcome this histogram equalization is the basic technique for enhancement due to its simple function and effectiveness. This method tends to change the brightness of an image and therefore, not suitable for consumer electronic products, where preserving the original brightness is essential to avoid annoying artifacts. A number of techniques have been developed over a period of time to overcome these undesirable effects. But none of the technique is found suitable for enhancement of image under poor illumination conditions, which preserve the brightness of the original image. In this article we present a survey of different techniques that are based on histogram equalization, and also applied those techniques on underwater images. We also made a comparison of the processed images by a set of ten quality metrics.


Adaptive enhancement Histogram equalization Quality metrics 


  1. 1.
    Kolar R, Odstrcilik J, Jan J, Harabis V (2011) Illumination correction and contrast equalization in colour fundus images. In: 19th European signal processing conference (EUSIPCO 2011) Barcelona, Spain, August 29–September 2 2011Google Scholar
  2. 2.
    Bazeille S, Quidu I, Jaulin L, Malkasse J (2006) Automatic underwater image pre-processing CMM’06—caracterisation du milieu marin, 16 –19 Octobre 2006. Empirical mode decomposition based visual enhancement of underwater images, Aysun Taşyapı Çelebi and Sarp ErtürkGoogle Scholar
  3. 3.
    Schettini R, Corchs S (2010) Underwater image processing: state of the art of restoration and image enhancement methods. EURASIP J Adv Sig Process 2010, Article id 746052 (Hindawi Publishing Corporation)Google Scholar
  4. 4.
    Iqbal K, Abdul Salam R, Osman A, Zawawi Talib A (2007) Underwater Image Enhancement Using an Integrated Colour Model. IAENG Int J Comput Sci 34:2 IJCS_34_2_12Google Scholar
  5. 5.
    Gonzalez RC, Woods RE (2002) Digital image processing, 2nd edn. Prentice-Hall, New JerseyGoogle Scholar
  6. 6.
    Kim YT (1997) Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Trans Consum Electron 43(1):1–8CrossRefGoogle Scholar
  7. 7.
    Chen S, Ramli AR (2003) Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation. IEEE Trans Consum Electron 49(4):1301–1309CrossRefGoogle Scholar
  8. 8.
    Xu Z, Liu X (2010) Bilinear interpolation dynamic histogram equalization for fog-degraded image enhancement. J Inf Comput Sci 7(8):1727–1732Google Scholar
  9. 9.
    Ibrahim H, Kong NSP (2007) Brightness preserving dynamic histogram equalization for image contrast enhancement. IEEE Trans Consum Electron 53(4):1752–1758CrossRefGoogle Scholar
  10. 10.
    Wongsritong K, Kittayaruasiriwat K, Cheevasuvit F, Dejhan K, Somboonkaew A (1998) Contrast enhancement using multipeak histogram equalization with brightness preserving. IEEE Asia Pac Conf circuits syst 452–458Google Scholar
  11. 11.
    Wang Y, Chen Q, Zhang B (1999) Image enhancement based on equal area dualistic sub-image histogram equalization method. IEEE Trans Consum Electron 45(1):68–75CrossRefGoogle Scholar
  12. 12.
    Chen S, Ramli AR (2003) Minimum mean brightness error bi-histogram equalization in contrast enhancement. IEEE Trans Consum Electron 49(4):1310–1319CrossRefGoogle Scholar
  13. 13.
    Chang LW, Lie W-N, Chiang R (eds) (2006) PSIVT 2006, LNCS 4319. © Springer, Berlin Heidelberg, pp 1150–1158Google Scholar
  14. 14.
    Wang Q, Ward R (2007) Fast Image/Video Contrast Enhancement Based on WTHE. In: Proceedings of IEEE on MSP 2007. pp 339–342Google Scholar
  15. 15.
    Tai SC, Chang YY, Li KM, Tsai TC (2009) Contrast enhancement method based on average luminance with weighted histogram equalization. In: Proceedings of IEEE on IAS 2009. pp 555–558Google Scholar
  16. 16.
    Ye Z (2009) Objective assessment of nonlinear segmentation approaches to gray level underwater images. ICGST-GVIP J 9(2) ISSN 1687-398XGoogle Scholar
  17. 17.
    Lizuo J, Shin’ichi S, Masao S (2004) A novel adaptive image enhancement algorithm for face detection. In: Proceedings of the 17th international conference on pattern recognition (ICPR’04)Google Scholar
  18. 18.
    Grgi S, Grgic M, Mrak M (2004) Reliability of objective picture quality measures. J Electr Eng 55(1, 2):3–10Google Scholar
  19. 19.
    Leu JG (1992) Image contrast enhancement based on the intensities of edge pixels. CVGIP: Graph Models Image Process 54(6):497–506Google Scholar
  20. 20.
    Jafar I, Ying H (2007) A new method for image contrast enhancement based on automatic specification of local histograms. IJCSNS Int J Comput Sci Netw Secur 7(7):1–10Google Scholar

Copyright information

© Springer India 2013

Authors and Affiliations

  • Jharna Majumdar
    • 1
  • Aparna Manikonda
    • 1
  • G. M. Venkatesh
    • 1
  1. 1.Nitte Meenakshi Institute of TechnologyBangaloreIndia

Personalised recommendations