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Table 6 Numerical results of the real QuickBird-2 dataset

From: Pansharpening based on convolutional autoencoder and multi-scale guided filter

Method Ds(0) Dλ(0) QNR(1)
Proposed 0.13935 0.081319 0.96598
PNN 0.181486 0.095215 0.96407
MSGF 0.082709 0.102 0.96379
CAE 0.19834 0.093565 0.94344
MTF-GLP 0.13929 0.092786 0.93708
Indusion 0.030669 0.087048 0.96348
SFIM 0.066346 0.14364 0.93699
PRACS 0.124 0.09274 0.9646
BDSD 0.3088 0.0974 0.9593
IHS 0.2534 0.10823 0.91008
AIHS 0.16242 0.095591 0.93691
PCA 0.28645 0.13137 0.90127