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Table 6 Comparison of the F1 measure applied on the RIDB

From: A novel approach to extracting useful information from noisy TFDs using 2D local entropy measures

SNRProposed methodLocal entropy-based algorithmRICI TFD threshold10%15%20%
Signal 1
−3 dBF1= 0.685F1= 0.577F1= 0.667F1= 0.648F1= 0.675F1= 0.658
0 dBF1= 0.756F1= 0.665F1= 0.757F1= 0.723F1= 0.677F1= 0.617
3 dBF1= 0.845F1= 0.772F1= 0.791F1= 0.794F1= 0.722F1= 0.66
6 dBF1= 0.915F1= 0.81F1= 0.823F1= 0.495F1= 0.495F1= 0.495
10 dBF1= 0.928F1= 0.827F1= 0.92F1= 0.495F1= 0.495F1= 0.495
Signal 2
−3 dBF1= 0.688F1= 0.553F1= 0.769F1= 0.608F1= 0.634F1= 0.621
0 dBF1= 0.778F1= 0.649F1= 0.721F1= 0.693F1= 0.691F1= 0.654
3 dBF1= 0.834F1= 0.782F1= 0.813F1= 0.768F1= 0.722F1= 0.659
6 dBF1= 0.869F1= 0.826F1= 0.863F1= 0.479F1= 0.479F1= 0.479
10 dBF1= 0.885F1= 0.868F1= 0.827F1= 0.479F1= 0.479F1= 0.479