JOURNAL ARTICLE

Image Denoising Using Discrete Wavelet Transform : A Theoretical Framework

Abstract

Noise is a random variation in brightness and color in image or simply we can say that unwanted signals are called noise. The noise is mixed with original signal and cause may troubles. Due to the presence of noise, quality of image is reduced and other features like edge sharpness and pattern recognition are badly affected. In image denoising methods to improve the results a hybrid filter is used for better visualization. The hybrid filter is composed with the combination of three filters connected in series. The hybridization has performed much better in case of salt and pepper type of noise and for most of the medical image type, either MRI, CT, SPECT, Ultra Sound. PSNR values show major improvement in comparison of other existing methods. Future, the results obtained from the presented denoising experiments would be tried to be improved further by using this method with other transform domain methods. Finally, the results are concluded that the proposed approach in terms of PSNR, MSE improvement is outperformed.

Keywords:
Artificial intelligence Noise reduction Computer science Salt-and-pepper noise Pattern recognition (psychology) Noise (video) Video denoising Filter (signal processing) Wavelet Non-local means Peak signal-to-noise ratio Computer vision Wavelet transform Median filter Image (mathematics) Mathematics Image denoising Image processing Video processing

Metrics

3
Cited By
0.29
FWCI (Field Weighted Citation Impact)
26
Refs
0.53
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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