Image Dehazing Algorithm Based on Attention Mechanism and Markov Discriminant

Fig. 10. Comparison of algorithms in outdoor. (a) Foggy images; (b) CAP results; (c) DCP results; (d) Dehaze results; (e) MSCNN results; (f) results of proposed algorithm

Download full size

Fig. 11. Comparison of PSNR

Download full size

Fig. 12. Comparison of SSIM

Download full size

Table 0. [in Chinese]

View table

Table 0. [in Chinese]

algorithm 1 A&P-dehaze algorithm

input：Foggy image

output：Defogging image

1）Input foggy imageI；

2）Use formula（7） to extract shallow features and get feature map $F_{s}$ ；

3）First， $F_{s}$ is downsampled by residual network，and attention mechanism is used to allocate weight $F_{d} = H_{A M} [F_{s} + F (F_{s}, W_{l})]$ ， $H_{A M}$ is the whole function of attention mechanism， $F (F_{s}, W_{l})$ is the residual；

4）Then the deconvolution residual network is used for upsampling to get $F_{b}$ ， $F_{b} = F_{d} + F (F_{d}, W_{l})$ ；

5）The transmittance map is obtained by using the mapping function， $t = H_{M A P} (F_{b})$ ；

（6）Using Inception module，the atmospheric light value of foggy image is predicted $A = F_{I n c, n} [. . . F_{I n c, 1} (I)]$ ；

（7）The defogging image $J$ can be obtained by using the atmospheric scattering model，

$J (x) = \frac{I (x) - A [1 - t (x)]}{t (x)}$ ；

8）Using PantchGAN to judge whether it is true or false；

9）Further training the network，repeat formula（8） until the loss function of the network is optimal，and the training is completed；

10）Save the optimal model.

Table 1. Comparison results on SOTS dataset
View table
Table 1. Comparison results on SOTS dataset
Algorithm SSIM PSNR
CAP
0.8524
0.8705
0.8756
0.8069
0.8764
18.96
18.97
21.34
17.12
20.86
DCP
Dehaze
MCSNN
Proposed algorithm

Table 2. Comparison results on HSTS dataset
View table
Table 2. Comparison results on HSTS dataset
Algorithm SSIM PSNR
CAP
0.7859
0.8095
0.8886
0.8632
0.8938
18.24
15.99
22.94
19.61
22.36
DCP
Dehaze
MCSNN
Proposed algorithm

Table 3. Comparison of average running time of different algorithms
View table
Table 3. Comparison of average running time of different algorithms
Algorithm CAP DCP Dehaze MSCNN Proposed algorithm
Time /s 1.42 9.86 1.78 1.70 0.93

Tools

Get Citation

Copy Citation Text

Kezheng Lin, Jiahao Geng, Weiyue Cheng, Ao Li. Image Dehazing Algorithm Based on Attention Mechanism and Markov Discriminant[J]. Laser & Optoelectronics Progress, 2022, 59(16): 1610003

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites