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http://dx.doi.org/10.6109/jkiice.2017.21.8.1540

Noise Removal using Canny 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.8, 2017 , pp. 1540-1546 More about this Journal
Abstract
Digital image processing is widely used in various fields including the military, medical, image recognition system, robot and commercial sectors. But in the process of acquiring and transmitting digital images, noise is generated by various external causes. There are various types of general noise depending on the cause and form, but AWGN and impulse noise is one of the leading methods. Removing noise during image processing is essential to the pre-treatment process such as segmentation, image recognition and characteristic extraction. As such, this paper suggests an algorithm that distinguishes the non-edge area and edge area using the Canny edge to apply different filters to different areas in order to effectively remove noise from the image. To verify the effectiveness of the suggested algorithm, it was compared against existing methods using zoom images, edge images and PSNR(peak signal to noise ratio).
Keywords
AWGN; Corrupted image; Canny edge; PSNR;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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