Manuscript received April 1, 2024; revised July 4, 2024; accepted July 16, 2024; published October 8, 2024

Abstract—This research aims to enhance the performance of image-denoising algorithms, particularly in the context of Block Matching 3D (BM3D) usage, focusing on improving image quality and retaining important information in noisy images. The novelty of this research lies in developing more effective and efficient image-denoising techniques by considering the characteristics of image blocks to improve denoising results. The method employed in this research involves the development of a new approach enabling the application of adaptive 2D and 3D transformations depending on the characteristics of the image block being processed. The research develops a new approach enabling the application of adaptive 2D and 3D transformations depending on the characteristics of the image block being processed. The results of this research indicate that the proposed adaptive approach in the BM3D image denoising algorithm can significantly improve denoising performance. Experimental results show that performing 2D transformations on blocks that do not have sufficiently similar blocks can yield better denoising results, especially at high noise levels.

Keywords—image denoising, adaptive transformation, image processing, Block Matching 3D (BM3D) algorithm

Cite: Ayyub Hamdanu Budi Nurmana, Mars Caroline Wibowo, and Sarwo Nugroho, "Enhancing Image Denoising Efficiency: Dynamic Transformations in BM3D Algorithm," Journal of Image and Graphics, Vol. 12, No. 4, pp. 332-344, 2024.

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.