JOURNAL ARTICLE

Comparing Wavelet and Wavelet Packet Image Denoising Using Thresholding Techniques

Abstract

Image denoising has remained a fundamental problem in the field of image processing.With Wavelet transforms, various algorithms for denoising in wavelet domain were introduced.Wavelets gave a superior performance in image de-noising because here multi-resolution analysis is possible.Wavelet thresholding is a signal estimation technique that exploits the capabilities of wavelet transform for signal denoising.The aim of this project was to study various denoising techniques using wavelet and wavelet packets and compare them to determine the better one for image denoising.Performance of denoising algorithm is measured using quantitative performance measures such as Signal-to-Noise Ratio (SNR) and Mean Square Error (MSE).

Keywords:
Wavelet Thresholding Wavelet packet decomposition Artificial intelligence Pattern recognition (psychology) Noise reduction Computer science Image denoising Wavelet transform Image (mathematics) Computer vision

Metrics

6
Cited By
0.84
FWCI (Field Weighted Citation Impact)
10
Refs
0.83
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
Brain Tumor Detection and Classification
Life Sciences →  Neuroscience →  Neurology

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