JOURNAL ARTICLE

Improved adaptive wavelet threshold for image denoising

Abstract

Adaptive wavelet threshold for Bayes shrink (Bayes threshold) is a simple and effective method for image denoising. Multiple wavelet representations have excellent performance in image denoising. In this paper, combining the multiple wavelet representations with the Bayes threshold and using their advantages in image denoising, proposes a new image denoising algorithm which called M-Bayes threshold. It is simple and effective. Simulation results show that the proposed M-Bayes threshold can achieve the state-of-the-art image denoising performance at the low computational complexity.

Keywords:
Noise reduction Wavelet Artificial intelligence Bayes' theorem Pattern recognition (psychology) Non-local means Image (mathematics) Computer science Video denoising Noise (video) Wavelet transform Image denoising Reduction (mathematics) Mathematics Algorithm Computer vision Bayesian probability

Metrics

23
Cited By
1.24
FWCI (Field Weighted Citation Impact)
25
Refs
0.85
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
Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology

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