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TWO STAGES NON-LOCAL MEANS ALGORITHM BASED ON WAVELET TRANSFORM

ABSTRACT
This paper presents an innovative wavelet transform-based two-stage non-local means algorithm that offers a new approach to image de-noising. It first decomposes the noisy image into four sub-images with different frequencies, which provides a more detailed analysis. Then, it fuses three high frequency sub-images into one high frequency sub-image, which enhances the image quality. The low-frequency sub-image and the fused high frequency sub-image are de-noised using the non-local means algorithm, which is a highly effective and robust de-noising technique. Furthermore, the de-noised low-frequency sub-image and the high frequency sub-image are merged to form the initial de-noised image. Finally, the initial de-noised image is de-noised again using the non-local means algorithm to produce the final de-noised image. The proposed algorithm is able to effectively remove noise while preserving edges and details.
KEYWORDS
PAPER SUBMITTED: 2024-05-08
PAPER REVISED: 2024-07-07
PAPER ACCEPTED: 2024-07-07
PUBLISHED ONLINE: 2025-07-06
DOI REFERENCE: https://doi.org/10.2298/TSCI2503015M
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2025, VOLUME 29, ISSUE Issue 3, PAGES [2015 - 2021]
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2025 Society of Thermal Engineers of Serbia. Published by the VinĨa Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence