Mixed Noise Removal Algorithm Combining Adaptive Directional Weighted Mean Filter and Improved Adaptive Anisotropic Diffusion Model

Hongjin Ma and Yufeng Nie

Mathematical Problems in Engineering, 2018, vol. 2018, 1-19

Abstract:

A mixed noise removal algorithm combining adaptive directional weighted mean filter and improved adaptive anisotropic diffusion model is proposed. Firstly, a noise classification method is introduced to divide all pixels into two types as the pixels corrupted by impulse noise and the pixels corrupted by Gaussian noise. Then an adaptive directional weighted mean filter is developed to remove impulse noise, which can adaptively select the optimal direction template from twelve direction templates and replace the gray level of each impulse noise corrupted pixel by the weighted mean gray level of pixels on the optimal direction template. Finally, an improved adaptive anisotropic diffusion model is developed to remove Gaussian noise in the initial denoised image, which can finely classify image features as smooth regions, edges, corners, and isolated noises by characteristic parameters and variance parameter and conduct adaptive diffusion for different image features by designing reasonable eigenvalues of diffusion tensor. A large number of experimental results show that the proposed algorithm outperforms many existing main mixed noise removal methods in terms of image denoising and detail preservation.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2018/6492696.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2018/6492696.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6492696

DOI: 10.1155/2018/6492696

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().