ITHEA® International Journal
"Information Theories and Applications"
2025, Volune 32, Nimber 2
A Robust Approach to grayscale Image Denoising: Integrating Neighborhood-Based Filtering and Wavelet Thresholding
Byulent Idirizov
Copy Citation Text:
Byulent Idirizov, "A Robust Approach to grayscale Image Denoising: Integrating Neighborhood-Based Filtering and Wavelet Thresholding" IJ ITA, Vol. 32, Issue 2, pp. 177-199. (2025)
DOI: https://doi.org/10.54521/ijita32-02-p06
Abstract:
Thе paper proposes a novel image denoising algorithm in grayscale that integrates neighborhood filtering with adaptive wavelet-based denoising. The algorithm leverages both local and frequency-domain information to effectively remove noise while preserving image details, demonstrating superior performance in terms of PSNR and visual quality compared to existing algorithms. Thе approach is robust against various types of noise, including salt-and-pepper and Gaussian, making it suitable for applications in different fields requiring high-quality image restoration. The image denoising algorithm is built in Matlab.
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