Table 1 The quantitative results of real-world denoising on AWLD dataset (PSNR/SSIM). Bolditalic number represents the best result, while bold number indicates the second-best result. F and P denote FLOPs and Parameters, respectively.

From: Wild horseshoe crab image denoising based on CNN-transformer architecture

Method

F(G)

P(M)

UI

UTI

TI

AVG

AP-BSN20

–

3.7

35.37/0.9443

30.46/0.8026

29.05/0.8723

31.63/0.8731

DDT21

86

18.4

38.16/0.9606

32.54/0.9013

33.21/0.9143

34.64/0.9254

MIRNetv222

785

31.8

34.19/0.9361

31.91/0.8992

30.27/0.8836

32.12/0.9063

MM-BSN23

–

5.3

34.94/0.9344

31.23/0.8937

30.07/0.8821

32.08/0.9034

MPRNet24

573

15. 7

37.93/0.9528

31.94/0.9011

31.27/0.8914

33.71/0.9151

SwinIR25

18

5.17

37.64/0.9516

30.89/0.8875

33.04/0.9105

33.86/0.9165

DDPG26

–

–

30.13/0.8012

30.02/0.8801

26.31/0.8529

28.82/0.8447

Restormer27

155

26.1

37.59/0.9516

31.68/0.8915

32.15/0.9027

33.81/0.9153

ours

196

28.3

38.12/0.9604

32.93/0.9026

33.59/0.9175

34.88/0.9273