Open AccessA Variational Model for Staircase Reduction in Image Denoising
Author(s) -
Tang Liming,
Fang Zhuang,
Xiang Changcheng,
Chen Shiqiang,
Huang Darong
Publication year - 2017
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2017.01.015
Subject(s) - noise reduction , image denoising , reduction (mathematics) , image (mathematics) , artificial intelligence , computer science , computer vision , mathematics , algorithm , geometry
We propose a new variational model to reduce the staircase that often appears in Total variation (TV) based models in image denoising. The model uses BV ‐seminorm and Besov‐seminorm to measure the piecewise constant component and piecewise smooth component of the image, respectively. We discuss the nontrivial property of the proposed model and introduce an alternating iteration algorithm that combines the dual projection algorithm with Wavelet soft thresholding (WST) algorithm to solve the model numerically. The experimental results show that the proposed model is effective for noise removal and staircase reduction, while the contour can be preserved in the denoised images. Furthermore, compared with two classical staircase reduction models, CEP2 and TGV, the proposed model is much faster than these two models.