Call for Paper

CAE solicits original research papers for the May 2023 Edition. Last date of manuscript submission is April 30, 2023.

Read More

Image Enhancement of Underwater Digital Images by Utilizing L*A*B* Color Space on Gradient and CLAHE based Smoothing

Ramandeep Kaur, Dipen Saini. Published in Image Processing.

Communications on Applied Electronics
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Ramandeep Kaur, Dipen Saini

Ramandeep Kaur and Dipen Saini. Article: Image Enhancement of Underwater Digital Images by Utilizing L*A*B* Color Space on Gradient and CLAHE based Smoothing. Communications on Applied Electronics 4(9):22-30, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {Ramandeep Kaur and Dipen Saini},
	title = {Article: Image Enhancement of Underwater Digital Images by Utilizing L*A*B* Color Space on Gradient and CLAHE based Smoothing},
	journal = {Communications on Applied Electronics},
	year = {2016},
	volume = {4},
	number = {9},
	pages = {22-30},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


The underwater digital images generally suffer from blur, low contrast, non-uniform lighting, and diminished color. This research paper proposed a preprocessing technique based on image to improve the quality of underwater digital images. The mixed Contrast Limited Adaptive Histogram Equilization (CLAHE) has actually neglected the utilization of L*A*B color image space to improve the image in an effective way. Also the uneven illumination problem is also ignored by many researchers. To conquer the problems of on hand technique a brand new L*A*B color image space as well as CLAHE based digital image enhancement technique is proposed in this paper. To conquer the problem of uneven illumination in the resultant image of the CLAHE image output has been further removed by utilizing the smoothing process of image gradient. The main objective of the planned algorithm is to enhance the accuracy of the underwater digital image enhancement methods/techniques. Various types of digital images will be considered for experimental point of view to estimate the efficacy of the image enhancement methods or techniques. Also, various types of image top-quality metrics have been utilized in order to check the significant improvement of the recommended technique over the offered techniques. The significant improvements have shown in the comparative analysis of the proposed algorithm over the available mixed CLAHE.


  1. Joung-Youn K., Lee-Sup K., and Seung-Ho H April 2001. An Advanced Contrast Enhancement Using Partially Overlapped Sub-Block Histogram Equalization. IEEE transactions on circuits and systems for video technology, vol. 11. No. 4.
  2. Chao W. and Zhongfu Y. November 2005. Brightness Preserving Histogram Equalization with Maximum Entropy: A Variational Perspective. IEEE Transactions on Consumer Electronics. Vol. 51. No. 4.
  3. Mary K. and Min C. August 2008. Recursively Separated and Weighted Histogram Equalization for Brightness Preservation and Contrast Enhancement. IEEE Transactions on Consumer Electronics. Vol. 54.
  4. Yisu Z., Nicolas G., Emil M. P. May 3-6 2010. Applying Contrast-limited Adaptive Histogram Equalization and Integral Projection for Facial Feature Enhancement and Detection. IEEE International Conference on Instrumentation and Measurement Technology.
  5. Zhen J., Hongcheng W., Rodrigo C., Ziyou X., Jianwei Z. and Alan F. March 14-19 2010. Real-Time Content Adaptive Contrast Enhancement for See-Through Fog And Rain. IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP).
  6. Chen H. O. and Nor Mat I. November 2010. Adaptive Contrast Enhancement Methods with Brightness Preserving. IEEE Transactions on Consumer Electronics. Vol. 56. No. 4.
  7. Nyamlkhagva S., Altansukh S., and Heung-Kook C. November 2010. Image Contrast Enhancement using Bi- Histogram Equalization with Neighborhood Metrics. IEEE Transactions on Consumer Electronics. Vol. 56. No. 4.
  8. Zohaib H. and Chunyan W. May 15-18 2011. Edge Detection Using Histogram Equalization And Multi-Filtering Process. IEEE International Symposium on Circuits and Systems (ISCAS).
  9. Yeong-Kang L., Yu-Fan L. January 9-12. Content-Based LCD Backlight Power Reduction with Image Contrast Enhancement Using Histogram Analysis. IEEE Journal of Display Technology.
  10. Seung-Won J. April 2014. Image Contrast Enhancement Using Color and Depth Histograms. IEEE Signal Processing Letters. Vol. 21, No. 4.
  11. Gurvir S., Mandeep S. December 2013. Histogram Eualization Techniques for Image Enhancement using Fuzzy Logic. Vol. 3, No. 6.
  12. Eunsung L., Sangjin K., Wonseok K., Doochun S., and Joonki P. January 2014. Contrast Enhancement Using Dominant Brightness Level Analysis and Adaptive Intensity Transformation for Remote Sensing Images IEEE Geoscience and Remote Sensing Letters. Vol.10, No.1.
  13. Muhammad Suzuri H., Wan Nural Hj Wan Y., Ezmahamrul Afreen A. and Zainuddin B. January 20-22 2013. Mixture Contrast Limited Adaptive Histogram Equalization for Underwater Image Enhancement. International Conference on Computer Applications Technology (ICCAT). pp. 1-5.
  14. John Y. C. and Ying-Ching C. April 2012. Underwater Image Enhancement by Wavelength Compensation and Dehazing. IEEE Transactions on Image Processing. Vol. 21, No. 4.
  15. Prabakar and Praveen K. 2011. An Image Based Technique for Enhancement Of Underwater Images. International Journal of Machine Intelligence. Vol. 3, No. 4.
  16. Shiwam S. T., Amit S. April 2014. Comparative Analysis of Various Underwater Image Enhancement Techniques. International Journal of Current Engineering and Technology, Vol. 3. No. 4.
  17. Pooja S. ,Neelesh G. and Neetu S. February 2014. A Survey on Underwater Image Enhancement Techniques. International Journal of Computer Applications. Vol. 87. No.13.
  18. Balvant S., Ravi Shankar M. and Puran G. 2011. Analysis of Contrast enhancement Techniques for Underwater Image. International Journal of Computer Technology and Electronics Engineering. Vol. 1, No.2.
  19. Dr. G. P., Dr. P. S., Muthu K. and Suresh T. 2010. Comparison of filters used for underwater image pre-processing. International Journal of Computer Science and Network Security. Vol. 10, No. 1.
  20. Pulung N. 2013. Underwater image enhancement using adaptive filtering for enhanced sift-based image matching. Journal of Theoretical and Applied Information Technology. Vol. 51, No. 3.
  21. Iqbal, K.; Odetayo, M.; James, A.; Salam, R.A.; Talib, A.Z.H. October 10-13 2010. Enhancing the low quality images using Unsupervised Colour Correction Method. IEEE International Conference on Systems Man and Cybernetics (SMC), pp.1703-1709.
  22. Jinbo C.; Zhenbang G.; Hengyu L.; Shaorong X. July 15-17 2011. A detection method based on sonar image for underwater pipeline tracker. Second International Conference on Mechanic Automation and Control Engineering (MACE), pp. 3766-3769.
  23. Hung-Yu Y.; Pei-Yin C.; Chien-Chuan H.; Ya-Zhu Z.; Yeu-Horng S. December 16-18 2011. Low Complexity Underwater Image Enhancement Based on Dark Channel Prior. Second International Conference on Innovations in Bio-inspired Computing and Applications (IBICA), pp. 17-20.
  24. Shamsuddin, N.; Wan Ahmad, W.F.; Baharudin, B.B.; Kushairi, M.; Rajuddin, M.; and. Mohd, F. June 12-14 2012. Significance level of image enhancement techniques for underwater images. International Conference on Computer & Information Science (ICCIS), Vol.1, pp. 490-494.
  25. Hitam, M.S.; Yussof, W.N.J.H.W.; Awalludin, E.A.; and Bachok, Z. January 20-22 2013. Mixture contrast limited adaptive histogram equalization for underwater image enhancement. International Conference on Computer Applications Technology (ICCAT), pp. 1-5.
  26. Muhammad Suzuri H. and Ezmahamrul Afreen A. 2013. Mixture Contrast Limited Adaptive HistogramEqualization for Underwater Image Enhancement. International Conference on Computer Applications Technology (ICCAT).


Preprocessing Underwater Image, CLAHE, L*A*B* Color Image Space, Image Gradient, Image Enhancement, Image Smoothing