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Research on Image Denoising in edge detection Based on Wavelet Transform
Version 1
: Received: 23 December 2022 / Approved: 26 December 2022 / Online: 26 December 2022 (13:29:13 CET)
A peer-reviewed article of this Preprint also exists.
You, N.; Han, L.; Zhu, D.; Song, W. Research on Image Denoising in Edge Detection Based on Wavelet Transform. Appl. Sci. 2023, 13, 1837. You, N.; Han, L.; Zhu, D.; Song, W. Research on Image Denoising in Edge Detection Based on Wavelet Transform. Appl. Sci. 2023, 13, 1837.
Abstract
In the process of image feature extraction, noise in the image will greatly affect the accuracy of edge detection. In this paper, the image is filtered to remove noise before edge detection by using the algorithm of wavelet transformation. Different wavelet functions are used to decompose image. Based on the experimental results, the best denoising wavelet function is selected. Canny algorithm is used to detect the edge of the denoised image, and the result of edge detection is evaluated according to the Pratt quality factor. It is proved that wavelet transform can improve the edge detection results.
Keywords
edge detection; wavelet transform; wavelet basis function; canny; Pratt quality factor
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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