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An Adaptive Edge Detection Algorithm for Images Corrupted with Impulse Noise

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 45 - Number 18
Year of Publication: 2012
Krishna Kant Singh
Akansha Mehrotra
M. J. Nigam
Kirat Pal

Krishna Kant Singh, Akansha Mehrotra, M J Nigam and Kirat Pal. Article: An Adaptive Edge Detection Algorithm for Images Corrupted with Impulse Noise. International Journal of Computer Applications 45(18):21-24, May 2012. Full text available. BibTeX

	author = {Krishna Kant Singh and Akansha Mehrotra and M. J. Nigam and Kirat Pal},
	title = {Article: An Adaptive Edge Detection Algorithm for Images Corrupted with Impulse Noise},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {45},
	number = {18},
	pages = {21-24},
	month = {May},
	note = {Full text available}


Edge detection is one of the most important tasks in the field of image processing. Detection of edges from noisy images is of greater importance as most images obtained are corrupted by impulse noise due to communication and transmission errors. In the proposed work a novel adaptive algorithm for finding edges of noisy images is proposed. One of the major problem with noisy images is that the noise pixels are also detected as edges, so in the proposed algorithm a threshold is used to distinguish between edge pixels and noise pixels. The value of threshold is inversely proportional to the level of details whose edges are detected and makes the algorithm adaptive. A sliding window is taken and the difference of the center pixel with all the pixels of the window whose value is not equal to zero or one is taken, But if the center pixel itself is zero or one then the difference from a noise free median is calculated. The average of the differences is checked against a threshold value. If the average value is above the threshold then it is a edge point otherwise it is noise based on this a binary image showing the edges is obtained


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