A Comprehensive Review of Image Denoising Techniques: From Traditional Filters to Deep Learning

Author(s)	Mr. Avinash Kumar, Rajeev Ranjan Kumar
Country	India
Abstract	Image denoising is a fundamental preprocessing step in digital image processing aimed at removing unwanted noise while preserving important image details and structures. Noise can degrade the visual quality and affect the performance of subsequent image analysis tasks. This study explores various image denoising techniques, ranging from traditional filtering methods to advanced machine learning and deep learning approaches. The effectiveness of these methods is evaluated based on their ability to reduce noise without compromising image sharpness and detail. Experimental results demonstrate that modern denoising algorithms significantly outperform classical techniques, providing enhanced visual quality and better preservation of image features. This work highlights the importance of choosing appropriate denoising strategies for different noise types and application scenarios, paving the way for improved image restoration and analysis.
Keywords	Image denoising, Noise, Visual Quality, Machine Learning, , Deep Learning
Field	Computer
Published In	Volume 7, Issue 4, July-August 2025
Published On	2025-07-07
DOI	https://doi.org/10.36948/ijfmr.2025.v07i04.46673
Short DOI	https://doi.org/g9s89h

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International Journal For Multidisciplinary Research