When physics meets signal processing: Image and video denoising based on Ising theory
作者：
Highlights：
• We present a detailed analogy between image processing and statistical physics.
• We use a novel Ising-like model for denoising of damaged colored images and videos.
• The algorithm chooses automatically the denoising parameters.
• A novel simulated annealing code, based on the L1 norm is then run.
• We denoise images and videos damaged by additive impulse or Gaussian noise.
• The restoration results are better compared to other well-known filters.
摘要
•We present a detailed analogy between image processing and statistical physics.•We use a novel Ising-like model for denoising of damaged colored images and videos.•The algorithm chooses automatically the denoising parameters.•A novel simulated annealing code, based on the L1 norm is then run.•We denoise images and videos damaged by additive impulse or Gaussian noise.•The restoration results are better compared to other well-known filters.
论文关键词：Image denoising,Ising model,Monte-Carlo methods,Metropolis algorithm,Simulated annealing,Statistical physics.
论文评审过程：Received 4 May 2014, Revised 5 February 2015, Accepted 26 February 2015, Available online 10 March 2015.
论文官网地址：https://doi.org/10.1016/j.image.2015.02.007
