A modified nonlocal-means for adaptive image denoising

Author

Ming Yin ; Shi-Quan Shao ; Li Ma

Author_Institution

Sch. of Electr. & Inf. Eng., Southwest Univ. for Nat. of China, Chengdu, China

Volume

8

fYear

2011

fDate

12-14 Aug. 2011

Firstpage

4224

Lastpage

4227

Abstract

Image denoising is an important problem and widely studied in image processing. Denoising is a crucial step to increase image conspicuity and to improve the performances of all the processing needed for quantitative imaging analysis. This work presents a modified nonlocal-mean denoising method based on the texture collection and edge information. At last, experiments result illustrate that the technique can be successfully used to the classical case of additive Gaussian noise. The proposed algorithm seems to improve on the state of the art performance.

Keywords

Gaussian noise; edge detection; image denoising; image texture; adaptive image denoising; additive Gaussian noise; edge information; image conspicuity; image processing; modified nonlocal-mean denoising method; texture collection; Algorithm design and analysis; Image denoising; Image edge detection; Information filters; Noise; Noise reduction; Signal processing algorithms; PSNR; edge information; image denosing; nonlocal means; texture collection;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on

Conference_Location

Harbin, Heilongjiang

Print_ISBN

978-1-61284-087-1

Type

conf

DOI

10.1109/EMEIT.2011.6023978

Filename

6023978