Home > Archives > IJSRST184145 IJSRST-Library

LIME: Low-Light Image Enhancement Via Illumination Map Estimation

Authors(2) :-K Ganga Bhavani, T. Durga Rao

Enhancing the quality of low light Images is a critical problem .To overcome this problem efficient method introduced that is Low Light Image Enhancement Previously different algorithms used to enhance the quality of low light Images Among that one algorithm is multimedia algorithm .Through this algorithm we can process on only gray scale Images and the quality of Image is not properly enhance to that extent .The main drawback is that the quality of the image gets reduced because the processing can be done by considering the single pixel .In our method LIME first we are calculating the illumination map next gamma correction method used for denoising of the Image .After that block matching can be done using the method BM3D .Using this method processing can be done in RGB Images and also considering the neighboring pixels so that the quality of the Image gets enhanced and also the image gets denoised using non local means method and show its superiority over several state-of-the-arts in terms of Enhancement Quality and Efficiency .
K Ganga Bhavani, T. Durga Rao
Illumination Estimation, Illumination (Light) Transmission, Low-light Image Enhancement
  1. D. Oneata, J. Revaud, J. Verbeek, and C. Schmid, "Spatio"temporal object detection proposals," in ECCV, pp. 737 -752, 2014.
  2. K. Zhang, L. Zhang, and M. Yang, "Real"time compressive tracking," in ECCV, pp. 866 -879, 2014.
  3. E. Pisano, S. Zong, B. Hemminger, M. DeLuce, J. Maria, E. Johnston, K. Muller, P. Braeuning, and S. Pizer, "Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms," Journal of Digital Imaging, vol. 11, no. 4, pp. 193 -200, 1998.
  4. H. Cheng and X. Shi, "A simple and effective histogram equalization approach to image enhancement," Digital Signal Processing, vol. 14, no. 2, pp. 158 -170, 2004.
  5. M. Abdullah"Al"Wadud, M. Kabir, M. Dewan, and O. Chae, "A dynamic histograme equalization for image contrast enhancement," IEEE Trans. on Consumer Electronics, vol. 53, no. 2, pp. 593 -600, 2007.
  6. T. Celik and T. Tjahjadi, "Contextual and variational contrast enhancement,"TIP, vol. 20, no. 12, pp. 3431 -3441, 2011.
  7. C. Lee and C. Kim, "Contrast enhancement based on layered difference representation," TIP, vol. 22, no. 12, pp. 5372 -5384, 2013.
  8. E. Land, "The retinex theory of color vision," Scientific American, vol. 237, no. 6, pp. 108 -128, 1977.
  9. D. Jobson, Z. Rahman, and G. Woodell, "Properties and performance of a center/surround retinex," TIP, vol. 6, no. 3, pp. 451 -462, 1996.
  10. D. Jobson, Z. Rahman, and G. Woodell, "A multi"scale retinex for bridging the gap between color images and the human observation of scenes," TIP, vol. 6, no. 7, pp. 965 -976, 1997.
  11. S. Wang, J. Zheng, H. Hu, and B. Li, "Naturalness preserved enhancement algorithm for non"uniform illumination images," TIP, vol. 22, no. 9, pp. 3538 -3578, 2013.
  12. X. Fu, D. Zeng, Y. Huang, Y. Liao, X. Ding, and J. Paisley, "A fusion"based enhancing method for weakly illuminated images," Signal Processing, vol. 129, pp. 82 -96, 2016.
  13. X. Fu, D. Zeng, Y. Huang, X. Zhang, and X. Ding, "A weighted variational model for simultaneous reflectance and illumination estimation," in CVPR, pp. 2782 -2790, 2016.
  14. X. Dong, G. Wang, Y. Pang, W. Li, J. Wen, W. Meng, and Y. Lu, "Fast efficient algorithm for enhancement of low lighting video," in ICME, pp. 1 -6, 2011.
  15. L. Li, R. Wang, W. Wang, and W. Gao, "A low"light image enhancement method for both denoising and contrast enlarging," in ICIP, pp. 3730 - 3734, 2015.

Find everything about JavaScript and jQuery in the cheat sheets, read the JavaScript blog or use the free online tools.

Publication Details
  Published in : Volume 4 | Issue 2 | January-February 2018
  Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 213-218
Manuscript Number : IJSRST184145
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
K Ganga Bhavani, T. Durga Rao, "LIME: Low-Light Image Enhancement Via Illumination Map Estimation ", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 4, Issue 2, pp.213-218, January-February-2018.
Journal URL : http://ijsrst.com/IJSRST184145

Article Preview