Table 3 Evaluation indicators for sharpening results in Test Fig. 3.
From: A novel pansharpening method based on cross stage partial network and transformer
Method | Evaluation indicators | |||||||
|---|---|---|---|---|---|---|---|---|
Q \(\uparrow\) | ERGAS \(\downarrow\) | Q4 \(\uparrow\) | RMSE \(\downarrow\) | SID \(\downarrow\) | SAM \(\downarrow\) | RASE \(\downarrow\) | SCC \(\uparrow\) | |
BT-H | 0.8773 | 4.9081 | 0.8530 | 65.6844 | 0.0416 | 6.3666 | 15.2849 | 0.8167 |
BDSD-PC | 0.6471 | 26.1190 | 0.3806 | 345.1671 | 0.1418 | 13.3837 | 101.9327 | 0.7194 |
SR_D | 0.7456 | 7.0228 | 0.7185 | 93.6517 | 0.0552 | 7.6320 | 21.5246 | 0.5536 |
TV | 0.8762 | 5.0553 | 0.8327 | 68.9120 | 0.0444 | 7.0426 | 15.6257 | 0.7802 |
PNN | 0.9582 | 2.8243 | 0.9412 | 38.1448 | 0.0194 | 4.6863 | 8.5813 | 0.9474 |
BDPN | 0.9103 | 4.3138 | 0.8818 | 57.4421 | 0.0322 | 5.9899 | 14.6656 | 0.8606 |
MSDCNN | 0.8746 | 4.9848 | 0.8243 | 67.5287 | 0.0459 | 7.2541 | 15.6536 | 0.7952 |
DRPNN | 0.9621 | 2.6471 | 0.9423 | 35.7721 | 0.0181 | 4.5005 | 8.2106 | 0.9542 |
DiCNN1 | 0.9614 | 2.6997 | 0.9455 | 36.4425 | 0.0176 | 4.4873 | 8.2174 | 0.9542 |
FusionNet | 0.9679 | 2.4601 | 0.9522 | 33.4912 | 0.0156 | 4.1976 | 7.6316 | 0.9617 |
CSTNet | 0.9687 | 2.4042 | 0.9529 | 32.7642 | 0.0151 | 4.0695 | 7.4696 | 0.9642 |
GF-CSTNet | 0.9715 | 2.2783 | 0.9549 | 30.9701 | 0.0134 | 3.8435 | 7.2316 | 0.9697 |
