Open AccessImage smoothing model based on the combination of the gradient and curvature
Author(s) -
Zhou Xian-Chun,
Meiling Wang,
Shi Lan-Fang,
Liang Zhou,
Wu Qin
Publication year - 2015
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.64.044201
Subject(s) - curvature , smoothing , image (mathematics) , computer science , noise (video) , enhanced data rates for gsm evolution , diffusion , image processing , anisotropic diffusion , edge detection , computer vision , mathematics , geometry , physics , thermodynamics
In image processing, in order to keep the detailed information about image edge, we propose a curvature smoothing model based on the nature of diffusion coefficient and curvature. Considering the fact that the curvature will change significantly when the image is affected by noise pollution, in this article we will continue to take the level set curvature as a detection factor and substitute it into the model, then we present a new model which combines gradient and curvature. Analysis and simulation indicate that the new model can keep more image information than the Perona-Malik model, and it can strengthen the sharp edge of the image efficiently, and well keep the straight lines of image, and edges, corners, slopes and small-scale features of curve at the same time, so this model is an ideal model.