Denoising multi-view images by soft thresholding: A short-time DFT approach
作者：
Highlights：
• We address the problem of denoising multi-view images.
• ST-DFT coefficients of multi-view images are modeled as Laplacian random variables.
• Multi-view images are denoised by soft thresholding in the ST-DFT domain.
• Threshold values are optimized based on Stein’s unbiased risk estimate.
• The effectiveness of our method is discussed in terms of restoration quality.
摘要
•We address the problem of denoising multi-view images.•ST-DFT coefficients of multi-view images are modeled as Laplacian random variables.•Multi-view images are denoised by soft thresholding in the ST-DFT domain.•Threshold values are optimized based on Stein’s unbiased risk estimate.•The effectiveness of our method is discussed in terms of restoration quality.
论文关键词：Multi-view images,Denoising,Short-time DFT,Soft thresholding,Model selection
论文评审过程：Received 27 September 2021, Revised 3 March 2022, Accepted 7 April 2022, Available online 14 April 2022, Version of Record 23 April 2022.
论文官网地址：https://doi.org/10.1016/j.image.2022.116710
