• W. Fathima Farsana
• Dr. N. Kowsalya

Recent advancements in image denoising algorithms utilizing Convolutional Neural Networks (CNN) have demonstrated significant success, surpassing traditional methods in both performance and efficiency. CNN-based approaches offer powerful learning capabilities, enabling them to effectively handle complex noise patterns. This paper provides an overview of both traditional image denoising techniques and CNN-based methods, with a detailed explanation of the fundamentals of image denoising. This serves as a valuable resource for those new to the field of image denoising. Additionally, the paper highlights commonly used datasets in image processing, facilitating better access to resources for image denoising tasks. Finally, the paper offers recommendations for enhancing the performance of CNN-based image denoising techniques and discusses potential future research directions in this area.

Convolutional Neu ral Network, Denoising Algorithms, Image Processing, Deep Learning

"A Comprehensive Review of CNN-Based Image Denoising Algorithms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 2, page no.c15-c21, February-2025, Available :http://www.jetir.org/papers/JETIR2502203.pdf

"A Comprehensive Review of CNN-Based Image Denoising Algorithms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 2, page no. ppc15-c21, February-2025, Available at : http://www.jetir.org/papers/JETIR2502203.pdf