This repository aggregates popular image denoising works that have publicly available code and demonstrate reproducible state-of-the-art results. It covers classical approaches (NLM, BM3D) and deep learning-based methods (DnCNN, FFDNet) for image denoising, organized by algorithm categories including filtering, sparse coding, and deep learning. The collection serves as a reference for researchers to compare approaches and access implementations.