Skip to main content

Table 3 Comparison results in SSIM for different levels of Gaussian noise

From: Hybrid regularizers-based adaptive anisotropic diffusion for image denoising

Method

Lena

Peppers

Barbara

Cameraman

House

\(\sigma =5\)

 Noise

0.85

0.85

0.89

0.84

0.80

 TV model

0.93

0.91

0.92

0.93

0.97

 LLT model

0.91

0.89

0.93

0.92

0.94

 NLM model

0.94

0.92

0.96

0.94

0.97

 BLS-GSM

0.94

0.92

0.96

0.96

0.98

 Hybrid model

0.94

0.93

0.96

0.96

0.98

 Proposed model

0.94

0.93

0.97

0.97

0.97

\(\sigma =10\)

 Noise

0.61

0.61

0.71

0.63

0.53

 TV model

0.89

0.88

0.87

0.86

0.90

 LLT model

0.87

0.86

0.85

0.86

0.89

 NLM model

0.90

0.89

0.90

0.90

0.92

 BLS-GSM

0.91

0.88

0.91

0.92

0.92

 Hybrid model

0.91

0.88

0.90

0.90

0.91

 Proposed model

0.91

0.89

0.91

0.91

0.90

\(\sigma =20\)

 Noise

0.34

0.43

0.48

0.41

0.35

 TV model

0.86

0.85

0.82

0.83

0.84

 LLT model

0.84

0.83

0.80

0.82

0.83

 NLM model

0.87

0.86

0.83

0.85

0.85

 BLS-GSM

0.86

0.84

0.83

0.84

0.87

 Hybrid model

0.87

0.85

0.82

0.83

0.85

 Proposed model

0.89

0.87

0.84

0.86

0.87

\(\sigma =40\)

 Noise

0.15

0.21

0.26

0.22

0.16

 TV model

0.79

0.77

0.75

0.77

0.80

 LLT model

0.75

0.74

0.73

0.74

0.76

 NLM model

0.82

0.80

0.76

0.76

0.82

 BLS-GSM

0.79

0.77

0.74

0.76

0.83

 Hybrid model

0.81

0.79

0.76

0.78

0.81

 Proposed model

0.82

0.79

0.75

0.79

0.83

\(\sigma =50\)

 Noise

0.11

0.17

0.15

0.18

0.13

 TV model

0.73

0.72

0.69

0.71

0.73

 LLT model

0.70

0.69

0.65

0.69

0.70

 NLM model

0.73

0.74

0.71

0.70

0.75

 BLS-GSM

0.74

0.73

0.69

0.72

0.75

Hybrid model

0.73

0.73

0.70

0.71

0.74

Proposed model

0.74

0.74

0.72

0.73

0.76