A modified nonlocal-means for adaptive image denoising

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...

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Bibliographic Details
Published inProceedings of 2011 International Conference on Electronic & Mechanical Engineering and Information Technology Vol. 8; pp. 4224 - 4227
Main Authors Ming Yin, Shi-Quan Shao, Li Ma
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2011
Subjects
Algorithm design and analysis
edge information
Image denoising
image denosing
Image edge detection
Information filters
Noise
Noise reduction
nonlocal means
PSNR
Signal processing algorithms
texture collection
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Summary: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.
ISBN:9781612840871
1612840876
DOI:10.1109/EMEIT.2011.6023978