SURVEY ON IMAGE DENOISING TECHNIQUES 论文

摘要

In the digital era of the world images are vital part of life and media. This survey explores a wide array of image denoising methods, spanning traditional and contemporary approaches. The review encompasses classical filters, statistical methods, and modern machine learning-based algorithms, with a focus on their principles, advantages and limitations. Through a systematic examination of the literature, we categorize the denoising techniques based on their underlying methodologies and applications. Insights are drawn from comparative analyses, highlighting the trade-offs and performance variations across different approaches. Additionally, emerging trends and future directions in image denoising research are discussed. This comprehensive survey serves as a valuable resource for researchers, practitioners, and enthusiasts in understanding of the different image denoising techniques. Keywords:- Wavelet Transformer, Image Denoising, Machine Learning.