Wavelet-Based Denoising Of Images

Alauldeen Yaseen, Applied Sciences Department, University of Technology, Baghdad - IraqFollow
Rafid Zamel, Applied Sciences Department, University of Technology, Baghdad - IraqFollow
Jabbar Khlaief, Applied Sciences Department, University of Technology, Baghdad - IraqFollow

Keywords

Image Processing, wavelet-analysis, Noise, Root-Mean-Square error

Document Type

Research Paper

Abstract

Wavelet-analysis has become a powerful tool for denoising images. It represents a new way to achieve better noise reduction and increased contrast. Here, experimentally demonstrate abilities of discrete wavelet transform with Daubechies basis functions for improving the quality of noisy images.in this research two methods has been compaired for modify the coefficients using soft and hard threshold to improv the visual fineness of noisy image depend on Root-Mean-Square error (RMS). The low RMS value and better noise reduction find in soft threshold method which is based on Daubechies wavelet (db8) for first example image RMS=0.101 and second example RMS=0.109

Recommended Citation

Yaseen, Alauldeen; Zamel, Rafid; and Khlaief, Jabbar (2026) "Wavelet-Based Denoising Of Images," Engineering and Technology Journal: Vol. 37: Iss. 2, Article 9.
DOI: https://doi.org/10.30684/etj.37.2B.4

DOI

10.30684/etj.37.2B.4

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