Table 1 The average PSNR28, SSIM29, UCIQE30, and UIQM31 of different methods on TEST-485 and TEST-90. The best performances are marked in bold, respectively.
From: Mamba-convolution hybrid network for underwater image enhancement
Methods | TEST-485 | TEST-90 | ||||||
|---|---|---|---|---|---|---|---|---|
PSNR\(\uparrow\) | SSIM\(\uparrow\) | UCIQE\(\uparrow\) | UIQM\(\uparrow\) | PSNR\(\uparrow\) | SSIM\(\uparrow\) | UCIQE\(\uparrow\) | UIQM\(\uparrow\) | |
Input | 21.3238 | 0.4653 | 0.4394 | 2.1041 | 19.1723 | 0.5539 | 0.4742 | 1.9429 |
BRUIE22 | 23.8345 | 0.5536 | 0.4415 | 2.3101 | 22.4918 | 0.6190 | 0.5386 | 2.2486 |
HLRP23 | 23.5840 | 0.5846 | 0.4731 | 2.3593 | 23.2744 | 0.6474 | 0.5417 | 2.3244 |
USUIR9 | 21.6215 | 0.5015 | 0.4375 | 2.3251 | 19.8721 | 0.5955 | 0.5301 | 2.2157 |
PUIE-Net5 | 24.3833 | 0.6830 | 0.5127 | 2.4344 | 24.8352 | 0.6322 | 0.5461 | 2.4187 |
U-shape14 | 25.4878 | 0.7100 | 0.5335 | 2.6644 | 25.3739 | 0.6743 | 0.5507 | 2.4615 |
WaterMamba18 | 25.6433 | 0.7465 | 0.5391 | 2.7744 | 25.7950 | 0.7572 | 0.5550 | 2.7379 |
UWMamba20 | 26.1438 | 0.7986 | 0.5479 | 2.8717 | 26.5655 | 0.8413 | 0.5775 | 3.0192 |
PixMamb19 | 26.5858 | 0.8719 | 0.5658 | 2.9884 | 27.5233 | 0.8833 | 0.5799 | 3.1052 |
MC-UIE | 28.0237 | 0.8901 | 0.5811 | 3.5908 | 29.0206 | 0.9402 | 0.5804 | 3.2311 |
