NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising

• This repository is for NLH introduced in the following paper

Yingkun Hou, Jun Xu, Mingxia Liu, Guanghai Liu, Li Liu, Fan Zhu, and Ling Shao, "NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising", IEEE Transactions on Image Processing, vol. 29, pp. 5121-5135, 2020.

• Email: ykhou@tsu.edu.cn

• The code is built on Matlab 2018a for Windows 10 and macOS Catalina 10.15.4.

• The folder NLH_AWGN_Gray includes gray scale images Additive Gaussian White Noise denosing codes and some gray scale images.

• The folder NLH_CC includes CC dataset and denoising codes. The related information refers to "S. Nam, Y. Hwang, Y. Matsushita, and S. J. Kim. A holistic approach to cross-channel image noise modeling and its application to image denoising. In CVPR, pages 1683–1691, 2016."

• The folder NLH_DND only includes denoising codes for DND dataset, the dataset can be downloaded from the following website: https://noise.visinf.tu-darmstadt.de/. The related information refers to "T. Plo¨tz and S. Roth. Bench algorithms with real photographs. In CVPR, 2017."

Note: If one wants to conduct AWGN denoising on color images, please change "sigma_est_b = sigma_est*4.0" to "sigma_est_b = sigma_est*1.0" in NLH_CC.m line 47 and NLH_DND.m line 72 respectively.

Note: We have updated NLH code named NLH_v2.0.zip. We added some faster codes in this version.