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Random Walker Segmentation based Contrast Enhancement of Dark Images with Canny Detection

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 122 - Number 22
Year of Publication: 2015
Authors:
Harshit Khare
Sanjay Sharma
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.

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