Fractional‐integral‐operator‐based improved SVM for filtering salt‐and‐pepper noise-Reference-Cited by-同舟云学术

Fractional‐integral‐operator‐based improved SVM for filtering salt‐and‐pepper noise

Published:2019-09-18 Issue:12 Volume:13 Page:2346-2357
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET image process

Author:

Jia Xiaofen¹²,Guo Yongcun¹³,Zhao Baiting²^ORCID,Huang Yourui²

Affiliation:

1. State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and TechnologyHuainan232001People's Republic of China

2. School of Electrical and Information Engineering, Anhui University of Science and TechnologyHuainan232001People's Republic of China

3. School of Mechanical Engineering, Anhui University of Science and TechnologyHuainan232001People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2019.0624

Reference34 articles.

1. Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data

2. Fast adaptive and selective mean filter for the removal of high‐density salt and pepper noise

3. Learning deep CNNs for impulse noise removal in images

4. An adaptive decision based kriging interpolation algorithm for the removal of high density salt and pepper noise in images

5. Adaptive type‐2 fuzzy approach for filtering salt and pepper noise in greyscale images;Singh V.;IEEE Trans. Fuzzy Syst.,2018

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