Table 4 Comparison of Key metrics with State-of-the-Art Techniques.

From: Deep learning steganography for big data security using squeeze and excitation with inception architectures

Dataset

Metric

Image

HiDDeN 32

SteganoGAN 33

HCISNet 34

AVG-GAN 35

Proposed

MRI Brain Dataset

PSNR

MRI-1

36.96

36.56

38.86

39.95

40.3

MRI-2

37.25

35.96

37.65

39.97

41.09

MRI-3

36.85

36.02

38.99

40.25

41.96

MSE

MRI-1

6.28

6.75

4.04

2.57

6.05

MRI-2

5.91

7.55

5.42

2.54

5.05

MRI-3

6.4

7.62

3.91

2.61

4.13

SSIM

MRI-1

0.96

0.96

0.97

0.98

0.98

MRI-2

0.97

0.96

0.97

0.98

0.99

MRI-3

0.96

0.96

0.97

0.98

0.98

OCT Glaucoma Dataset

PSNR

OCT-1

36.86

36.56

38.16

38.95

38.51

OCT-2

37.15

36.22

37.44

38.47

38.85

OCT-3

38.45

37.23

38.44

38.13

39.71

MSE

OCT-1

6.34

6.75

4.85

4.09

9.14

OCT-2

5.79

7.54

5.17

4.26

8.46

OCT-3

4.27

5.93

4.28

3.39

6.94

SSIM

OCT-1

0.96

0.96

0.97

0.98

0.98

OCT-2

0.96

0.95

0.97

0.98

0.96

OCT-3

0.97

0.96

0.97

0.98

0.98