A novel iterative thresholding algorithm based on plug-and-play priors for compressive sampling

作者：Liu, Lingjun; Xie, Zhonghua^*; Yang, Cui

来源：Future Internet, 2017, 9(3): 24.

DOI：10.3390/fi9030024

• Block matching and 3d filtering
• BM3D
• Compressive sampling
• Constraint problems
• Iterative thresholding
• Plug and play
• Self-similarities
• Splitting techniques

We propose a novel fast iterative thresholding algorithm for image compressive sampling(CS) recovery using three existing denoisers-i.e., TV (total variation), wavelet, and BM3D(block-matching and 3D filtering) denoisers. Through the use of the recently introduced plug-and-playprior approach, we turn these denoisers into CS solvers. Thus, our method can jointly utilize theglobal and nonlocal sparsity of images. The former is captured by TV and wavelet denoisers formaintaining the entire consistency;while the latter is characterized by the BM3D denoiser to preservedetails by exploiting image self-similarity. This composite constraint problem is then solved withthe fast composite splitting technique. Experimental results show that our algorithm outperformsseveral excellent CS techniques.

• 出版日期2017-6-24
• 单位华南理工大学