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http://dx.doi.org/10.6109/jkiice.2017.21.7.1342

A Study on Noise Removal using Modified Edge Detection in AWGN Environments  

Kwon, Se-Ik (Dept. of Control and Instrumentation Eng., Pukyong National University)
Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyong National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.21, no.7, 2017 , pp. 1342-1348 More about this Journal
Abstract
In an era where digital data takes on great importance, images are essential to various media. Noise is generated during the acquisition and transmission of such images, caused by a number of external factors. The removal of noise is an essential step in image processing. There are various methods used to remove noise, in accordance with the cause or form of the noise. AWGN is one of the leading methods. As such, this paper applies the edge detection method using the mean of each pixel after categorizing in detail the partial masks into nine areas as part of the preliminary process, in order to minimize noise that had been added to the image. In addition, the paper suggests an algorithm that applies different filters to the partial masks by using the critical mass value of the transfigured edge detection. To verify the competence of the suggested algorithm, it was compared with existing methods by using magnified images and PSNR(peak signal to noise ratio).
Keywords
AWGN; Corrupted image; Edge detection; PSNR;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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