An unified interface for benchmarking HSI denoising algorithms on various datasets under different noise settings.

• Download the library of HSI denoising algorithms from OneDrive and put the lib directory in the matlab folder.

• Type addpath(genpath('lib')); in matlab command line; now you can use any algorithms with an unified interface defined in demo_fun.m. For instance, you can use BM4D to denoise a hyperspectral image via demo_fun(noisy_hsi, sigma_ratio, 'BM4D')

• Benchmark your selected algorithm on the whole dataset by Main_Gauss/Complex/Real.m; Get the quantitative results via Result_Gauss/Complex.m

The bibtex of the collected algorithms can be found in benchmarks.bib

• The code of different HSI denoising algorithms is collected online.
• Special thanks to these authors for making their source code publicly available.

Adding your own algorithms is very easy: Simply put your source code in lib directory, then write your algorithm interface in demo_fun.m.