Title :
Partial Differential Equation Model Method Based on Image Feature for Denoising
Author :
Zhang, Xiaohua ; Wang, Ran ; Jiao, L.C.
Author_Institution :
Key Lab. of Intell. Perception & Image Understanding of the Minist. of Educ. of China, Xidian Univ., Xi´´an, China
Abstract :
For the special different nature images, we could hardly find particularly desirable approach, and there always exist Gibbs-type artifacts in the results of most methods. A novel Partial Differential Equation (PDE) model is proposed based on image feature for images denoising. The PDE model is adaptive within each region according to the details of the image feature to adjust the size of the diffusion coefficient. So it can be disposed the high gradient noise at the same time better to retain the edge information. We also analyze the performance of the PDE model method. Numerical results show that our algorithm competes favorably with state of the-art TV projection methods to eliminate noise and reduce Gibbs-type artifacts.
Keywords :
diffusion; image denoising; partial differential equations; Gibbs type artifacts; Gibbs-type artifacts; PDE model; diffusion coefficient; gradient noise; image denoising; image feature; nature images; partial differential equation model;
Conference_Titel :
Multi-Platform/Multi-Sensor Remote Sensing and Mapping (M2RSM), 2011 International Workshop on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-9402-6
DOI :
10.1109/M2RSM.2011.5697408