JOURNAL ARTICLE

Image Denoising for Adaptive Threshold Function Based on the Dyadic Wavelet Transform

Abstract

Based on the characteristic of dyadic wavelet transform to image denoising, this paper presents that denoising precision can be improved by the way that adopting different thresholds according to the different scales of the wavelet coefficients of image and noise to establish adaptive layered threshold function which adapts to it and reconstruct the wavelet. The experiment shows that by the method above the effect of image denoising is obviously superior to that of fixed threshold function.

Keywords:
Wavelet Wavelet transform Noise reduction Image denoising Artificial intelligence Non-local means Video denoising Pattern recognition (psychology) Image (mathematics) Wavelet packet decomposition Computer science Noise (video) Stationary wavelet transform Second-generation wavelet transform Function (biology) Computer vision Mathematics

Metrics

3
Cited By
0.31
FWCI (Field Weighted Citation Impact)
6
Refs
0.68
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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