International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 7, No. 5, 8 Apr. 2015
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Performance Evaluation of Modified DBLA Using Dark Channel Prior & CLAHE
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Author(s)
Kirandeep Kaur
1,*
Neetu Gupta
1
Index Terms
Image Enhancement, Human Visual Perception, DBLA, CLAHE, RGB
Abstract
This paper has focused on the different image enhancement techniques. Image enhancement has found to be one of the most important vision applications because it has ability to enhance the visibility of images. It enhances the quality of poor pictures. Distinctive procedures have been proposed so far for improving the quality of the digital images. To enhance picture quality image enhancement can specifically improve and limit some data presented in the input picture. It is a kind of vision system which reductions picture commotion, kill antiquities, and keep up the informative parts. Its object is to open up certain picture characteristics for investigation, conclusion and further use. The main objective of this paper is to modify the DBLA using the dark channel prior and CLAHE to enhance the results further. The comparative analysis has shown the significant improvement over the CLAHE and the DBLA.
Cite This Paper
Kirandeep Kaur, Neetu Gupta, "Performance Evaluation of Modified DBLA Using Dark Channel Prior & CLAHE", International Journal of Intelligent Systems and Applications(IJISA), vol.7, no.5, pp.48-56, 2015. DOI:10.5815/ijisa.2015.05.07
Reference
[1]Eunsung lee, Sangjin Kim, Wonseok Kang, Doochun Seo, Joonki Paik "Contrast Enhancement Using Dominant Brightness Level Analysis and Adaptive Intensity Transformation for Remote Sensing Images.” pp.62-66, 2013.
[2]Ullah, E., R. Nawaz, and J. Iqbal. "Single image haze removal using improved dark channel prior." Modelling, Identification & Control (ICMIC), 2013 Proceedings of International Conference on. IEEE, 2013.
[3]Setiawan, Agung W., et al. "Color Retinal Image Enhancement using CLAHE." 2013 International Conference on ICT for Smart Society (ICISS).
[4]Agaian, Sos, and Mehdi Roopaei. "New haze removal scheme and novel measure of enhancement." Cybernetics (CYBCONF), 2013 IEEE International Conference on. IEEE, 2013.
[5]Hitam, M. S., et al. "Mixture contrast limited adaptive histogram equalization for underwater image enhancement." Computer Applications Technology (ICCAT), 2013 International Conference on. IEEE, 2013.
[6]Im, Jaehyun, et al. "Dark channel prior-based spatially adaptive contrast enhancement for back lighting compensation." Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on. IEEE, 2013.
[7]Kil, Tae Ho, Sang Hwa Lee, and Nam Ik Cho. "A dehazing algorithm using dark channel prior and contrast enhancement." Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on. IEEE, 2013.
[8]Zhu, Qingsong, et al. "An adaptive and effective single image dehazing algorithm based on dark channel prior." Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on. IEEE, 2013.
[9]Saleem, Amina, Azeddine Beghdadi, and Boualem Boashash. "Image fusion-based contrast enhancement." EURASIP Journal on Image and Video Processing 2012: pp.1-17, 2012.
[10]Khan, Mohd Farhan, Ekram Khan, and Z. A. Abbasi. "Weighted average multi segment histogram equalization for brightness preserving contrast enhancement." Signal Processing, Computing and Control (ISPCC), 2012 IEEE International Conference on. IEEE, 2012.
[11]Peng,Li,Chuangbai Xiao, and Jing Yu. "single image fog removal based on dark channel prior and localextrema." american journal of engineering and Technology Research Vol 12.2 (2012).
[12]Tripathi, A. K., and S. Mukhopadhyay. "Single image fog removal using anisotropic diffusion." Image Processing, IET 6.7 (2012): 966-975.
[13]Rajesh Garg, Bhawna Mittal, Sheetal Garg “Histogram Equalization Techniques For Image Enhancement” IJECT vol2, issue1, March 2011.
[14]Demirel, Hasan, Cagri Ozcinar, and Gholamreza Anbarjafari. "Satellite image contrast enhancement using discrete wavelet transform and singular value decomposition." Geoscience and Remote Sensing Letters, IEEE 7.2: pp.333-337, 2010.
[15]Guo, Fan, et al. "Automatic Image Haze Removal Based on Luminance Component." Wireless Communications Networking and Mobile Computing (WiCOM), 2010 6th International Conference on. IEEE, 2010.
[16]Yisu Zhao, Nicolas D. Georgans, Emil M. Petriu “Applying Contrast-Limited Adaptive Histogram Equalization and Integral Projection For Facial Feature Enhancement and Detection” 2010, IEEE.
[17]Chen, Mengyang, et al. "Single image defogging." Network Infrastructure and Digital Content, 2009. IC-NIDC 2009. IEEE International Conference on. IEEE, 2009.