Optimization of wavelet threshold denoising based on edge detection

Ning Li; Jinyuan Zhang; Zhongliang Deng

doi:10.1117/12.2282081

21 July 2017 Optimization of wavelet threshold denoising based on edge detection

Ning Li, Jinyuan Zhang, Zhongliang Deng

Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 104200O (2017) https://doi.org/10.1117/12.2282081
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China

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

Citation Download Citation

Ning Li, Jinyuan Zhang, and Zhongliang Deng "Optimization of wavelet threshold denoising based on edge detection ", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104200O (21 July 2017); https://doi.org/10.1117/12.2282081

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