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Proceedings Paper

Optimization of wavelet threshold denoising based on edge detection
Author(s): Ning Li; Jinyuan Zhang; Zhongliang Deng
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Paper Abstract

Traditional wavelet threshold denoising algorithm is insufficient for the preservation of edge detail information and the separation of noise. In this paper, proposed the optimization of wavelet threshold denoising method based on edge detection, which to process the edge image obtained by the wavelet edge detection algorithm, and fuse the smoothing image produced by the improved threshold function model. Experimental results show that compared with the traditional wavelet threshold denoising method, this algorithm effectively preserves the edge information of the image and remove the noise, also improved signal to noise ratio obviously

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104200O (21 July 2017); doi: 10.1117/12.2282081
Show Author Affiliations
Ning Li, Beijing Univ. of Posts and Telecommunications (China)
Jinyuan Zhang, Beijing Univ. of Posts and Telecommunications (China)
Zhongliang Deng, Beijing Univ. of Posts and Telecommunications (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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