JOURNAL ARTICLE

An Improved Non-local Means Filter for Image Denoising

Abstract

This paper proposes a improved non-local means (NLM) filter for image denoising. Due to the drawback that the similarity is computed based on the noisy image, the traditional NLM method easily generates the artifacts in case of high-level noise. The proposed method first preprocesses the noisy image by Gaussian filter. Then, a moving window at each pixel of the noisy image is chosen as the search window, and meanwhile, a improved calculation method of spatial distance based on the preprocessed image is used for computing the similarity. Finally, combining the improved distance with search window based on the noisy image, the intensity of each pixel is restored as the traditional NLM method. The standard images are used to evaluate restoration performance of the proposed method. Additionally, the application on medical image denoising also demonstrates that our method is practical.

Keywords:
Non-local means Artificial intelligence Computer vision Noise reduction Computer science Bilateral filter Pixel Filter (signal processing) Similarity (geometry) Image restoration Noise (video) Image (mathematics) Pattern recognition (psychology) Window (computing) Gaussian filter Image denoising Image processing

Metrics

10
Cited By
0.00
FWCI (Field Weighted Citation Impact)
21
Refs
0.34
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology

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