Open AccessAn Improved WNNM Algorithm for Image Denoising
Author(s) -
Jiawei Wu,
XiDa Lee
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/2/022037
Subject(s) - salt and pepper noise , median filter , gaussian noise , noise reduction , noise (video) , algorithm , computer science , image noise , gradient noise , value noise , noise measurement , mathematics , artificial intelligence , image (mathematics) , noise floor , image processing
The traditional weighted nuclear norm minimization (WNNM) has excellent performance for the removal of non-sparse noise such as Gaussian noise, but attains bad performance for the removing of salt&pepper noise and mixed noise of Gaussian noise and salt&pepper noise. This paper proposes an improved WNNM image denoising algorithm. WNNM can effectively remove non-sparse noise such as Gaussian noise and adaptive median filtering algorithm can effectively remove sparse noise such as salt and pepper noise; the improved algorithm combines the characteristics of WNNM and adaptive median filtering. The experimental data demonstrate that the improved WNNM algorithm has better denoising effect than WNNM algorithm.