Version 1
: Received: 18 October 2023 / Approved: 20 October 2023 / Online: 20 October 2023 (16:10:28 CEST)
How to cite:
Wu, M. Wavelet Analysis for Image Denoising: A Multiscale Approach for Enhancing Visual Clarity. Preprints2023, 2023101364. https://doi.org/10.20944/preprints202310.1364.v1
Wu, M. Wavelet Analysis for Image Denoising: A Multiscale Approach for Enhancing Visual Clarity. Preprints 2023, 2023101364. https://doi.org/10.20944/preprints202310.1364.v1
Wu, M. Wavelet Analysis for Image Denoising: A Multiscale Approach for Enhancing Visual Clarity. Preprints2023, 2023101364. https://doi.org/10.20944/preprints202310.1364.v1
APA Style
Wu, M. (2023). Wavelet Analysis for Image Denoising: A Multiscale Approach for Enhancing Visual Clarity. Preprints. https://doi.org/10.20944/preprints202310.1364.v1
Chicago/Turabian Style
Wu, M. 2023 "Wavelet Analysis for Image Denoising: A Multiscale Approach for Enhancing Visual Clarity" Preprints. https://doi.org/10.20944/preprints202310.1364.v1
Abstract
This paper explores the application of wavelet analysis, a multiscale approach for enhancing visual clarity, in the context of image denoising, which reduces the impact of noisy pixels, caused by various factors such as electronic sensor limitations, low-light conditions, or transmission errors in digital imaging systems. This paper introduces some common noise types like Gaussian noise and processes of image denoising, eliciting the strength of wavelet analysis. As a powerful image denoising technology, wavelet analysis needs five steps to process the image, and the key step is thresholding. There are many kinds of wavelet, and each wavelet has different advantages and functions, which makes it suitable for different applications. Hence, wavelet analysis also makes a contribution in various fields beyond signal processing and data analysis, such as Biomedical Imaging and Geophysics and Seismology, where preserving image quality is essential for accurate analysis and interpretation. In short, this research highlights the promise of wavelet analysis, emphasizing the use of high- quality image data.
Keywords
Wavelet Analysis; image denoising; signal processing; enhancing visual clarity
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
