Random Walker Segmentation based Contrast Enhancement of Dark Images with Canny Detection
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10.5120/21856-5177 |
Harshit Khare and Sanjay Sharma. Article: Random Walker Segmentation based Contrast Enhancement of Dark Images with Canny Detection. International Journal of Computer Applications 122(22):13-15, July 2015. Full text available. BibTeX
@article{key:article,
author = {Harshit Khare and Sanjay Sharma},
title = {Article: Random Walker Segmentation based Contrast Enhancement of Dark Images with Canny Detection},
journal = {International Journal of Computer Applications},
year = {2015},
volume = {122},
number = {22},
pages = {13-15},
month = {July},
note = {Full text available}
}
Abstract
Contrast enhancement is a technique which enables images to improve the contrast level of images. Contrast enhancement of images requires filtering of regions where contrast level is high or where noise level is more. The techniques such as non-dynamic based stochastic resonance are implemented but the technique provides less accuracy of contrast improvement. Hence an efficient technique is implemented here by segmented the low contrast region of the image and then filtering is performed on the segmented region using transformation. The proposed methodology greatly improves the contrast enhancement of the images.
References
- Adin Ramirez Rivera, Byungyong Ryu, and Oksam Chae "Content-Aware Dark Image Enhancement Through Channel Division", IEEE Transactions on Image Processing, Vol. 21, No. 9, pp. 3967 – 3980, September 2012.
- Panetta, K. A. , Wharton, E. J. and Agaian, S. S. "Human Visual System-Based Image Enhancement and Logarithmic Contrast Measure", IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. - 38, Issue 1, pp. 174 – 188, 2008.
- Wolf, S. ; Ginosar, R. ; Zeevi, Y. : Spatio-chromatic image enhancement based on a model of humal visual information system. J. Vis. Commun. Image Represention 9(1) (1998), 25—37.
- Farbman, Z. ; Fattal, R. ; Lischinski, D. ; Szeliski, R. : Edge-preserving decompositions for multi-scale tone and detail manipulation. ACM Trans. Graph. 27(3) (2008), 1–10
- Rallabandi, V. P. S. : Enhancement of ultrasound images using stochastic resonance based wavelet transform. Comput. Med. Imaging Graph. 32 (2008), 316–320.
- Rallabandi, V. P. S. ; Roy, P. K. : Magnetic resonance image enhancement using stochastic resonance in Fourier domain. Comput. Med. Imaging Graph. 28 (2010), 1361–1373.
- Rajib Kumar Jha, Raj laxmi Chouhan, P. K. Biswas, "Noise-induced Contrast Enhancement of Dark Images using Non-dynamic Stochastic Resonance" 978-1-4673-0816, 2012.
- Erkan Bostanci, NadiaKanwal, Adrian F. Clark, "Spatial Statistics of Image Features for Performance Comparison" IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 23, NO. 1, JANUARY 2014.
- R. Priyakanth, Santhi Malladi, and Radha Abburi "Dark Image Enhancement through Intensity Channel Division and Region Channels using Savitzky-Golay Filter", International Journal of Scientific and Research Publications, ISSN 2250-3153, Volume 3, Issue 8, August 2013.
- Hasanul Kabir, Abdullah Al-Wadud, and Oksam Chae "Brightness Preserving Image Contrast Enhancement Using Weighted Mixture of Global and Local Transformation Functions", The International Arab Journal of Information Technology, Vol. 7, No. 4, pp. 403 - 410 ,October 2010.
- Adin Ramirez Rivera, Byungyong Ryu, and Oksam Chae "Content-Aware Dark Image Enhancement Through Channel Division", IEEE Transactions on Image Processing, Vol. 21, No. 9, pp. 3967 – 3980, September 2012.