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Table 1 The PSNR results of the denoised images by different denoising schemes

From: A wavelet denoising approach based on unsupervised learning model

Image Method σ=10 σ=25 σ=50 σ=70 σ=100
Barbara Wavelet thresholding 31.24 25.60 22.50 21.73 20.23
  TV 30.56 25.31 22.81 22.31 21.72
  K-SVD 34.11 29.57 25.42 23.30 21.87
  BM3D 34.75 30.36 26.95 25.17 23.24
  Proposed approach 34.34 29.80 27.03 25.85 23.63
House Wavelet thresholding 32.25 27.60 24.57 23.15 21.58
  TV 34.28 30.43 27.21 25.92 24.41
  K-SVD 35.23 31.20 28.08 25.77 23.82
  BM3D 36.36 32.48 29.32 27.52 25.47
  Proposed approach 35.62 31.60 28.40 27.05 25.84
Flinstones Wavelet thresholding 30.09 24.66 20.72 19.08 17.70
  TV 30.95 25.86 21.63 20.40 18.80
  K-SVD 31.97 27.87 24.33 22.20 19.64
  BM3D 32.27 28.25 24.98 23.20 21.26
  Proposed approach 32.08 28.36 25.35 24.31 22.50
Bridge Wavelet thresholding 29.81 24.54 21.74 20.80 19.90
  TV 29.55 25.64 22.85 22.05 21.17
  K-SVD 30.87 26.04 23.10 22.10 21.09
  BM3D 31.03 26.15 23.56 22.56 21.57
  Proposed approach 31.25 26.57 23.98 22.87 21.70
Fingerprint Wavelet thresholding 30.55 25.11 20.86 19.52 17.72
  TV 29.88 25.40 22.90 21.31 18.03
  K-SVD 32.20 27.28 23.28 20.60 18.40
  BM3D 32.19 27.38 24.32 22.84 21.23
  Proposed approach 32.21 27.80 25.18 23.20 21.83
  1. For each test setting, five results are provided: Wavelet thresholding, TV, K-SVD, BM3D, and our proposed model. The highest PSNR values (best denoising results) are given in bold