/Image-Denoising-Benchmark

Collection of image denosing tools in an unification Matlab code

Primary LanguageMATLAB

Image Denoising Benchmark

This is collection of matlab tool for image denoising benchmark. Current supported tools are

  • ACPT "Detail-Preserving Image Denoising via Adaptive Clustering and Progressive PCA Thresholding," in IEEE Access,2018
  • ACVA "Texture variation adaptive image denoising with nonlocal PCA", TIP 2018.
  • AST-NLS Image Denoising via Adaptive Soft-Thresholding Based on Non-Local Samples, CVPR 2015
  • BM3D Image restoration by sparse 3D transform-domain collaborative filtering (SPIE Electronic Imaging 2008), Dabov et al.
  • DnCNN Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising, TIP 2018.
  • GGMM-EPLL Image denoising with generalized Gaussian mixture model patch priors, SIAM JIS 2018.
  • GSRC ICIP 2016.
  • KSVD TIP 2016.
  • MultiScaleEPLL Multi-Scale Patch-Based Image Restoration, TIP 2016.
  • NCSR TIP 2012.
  • NLH: "NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising", TIP 2020 (github.com/njusthyk1972/NLH). Only Gray denoising is used with given sigma.
  • PGDP Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising, ICCV 2015
  • SSC_GSRM Image Restoration via Simultaneous Sparse Coding: Where Structured Sparsity Meets Gaussian Scale Mixture, IJVC 2015
  • TWSC A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising, ECCV 2018
  • WNNN Weighted Nuclear Norm Minimization with Application to Image Denoising (CVPR2014), Gu et al.