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Table 1. The results for ten objects and the parameters ranging from 10 to 100 Table 2. The results for ten objects and the parameters ranging from 1000 to 10000

Table 1 The results for ten objects and the parameters ranging from 10 to 100 Table 2. The results for ten objects and the parameters ranging from 1000 to 10000

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In the present paper, the set of all fpfs-sets over U is denoted by FPFS;(U).
In the present paper, the set of all fpfs-sets over U is denoted by FPFS;(U).
Table 5. The results for the parameters and the objects ranging from 10 to 100
Table 5. The results for the parameters and the objects ranging from 10 to 100
Table 3. The results for 10 parameters and the objects ranging from 10 to 100 Table 4. The results for 10 parameters and the objects ranging from 1000 to 10000
Table 3. The results for 10 parameters and the objects ranging from 10 to 100 Table 4. The results for 10 parameters and the objects ranging from 1000 to 10000
Fig. 3. The figure for Table 3
Fig. 3. The figure for Table 3
Table 7. The mean-PSNR results for the 20 traditional images with different SPN ratios
Table 7. The mean-PSNR results for the 20 traditional images with different SPN ratios
lable 6. The results for the parameters and the objects ranging from 100 to 1000
lable 6. The results for the parameters and the objects ranging from 100 to 1000
Table 8. The mean-SSIM results for the 20 traditional images with different SPN ratios Table 9. The mean-VIF results for the 20 traditional images with different SPN ratios
Table 8. The mean-SSIM results for the 20 traditional images with different SPN ratios Table 9. The mean-VIF results for the 20 traditional images with different SPN ratios
Assume that the success in high noise densities is more important than in the others. In that case, the values given in Table 7-9 can be represented with three fpfs-matrices as follows:
Assume that the success in high noise densities is more important than in the others. In that case, the values given in Table 7-9 can be represented with three fpfs-matrices as follows:
Assume that the success in low noise densities is more important than in the others. In that case, the values given in Table 7-9 can be represented with three fpfs-matrices as follows: The ranking orders obtained by EK15, EMK19, and expert's view are in Table 10. It must be noted that EK15 has produced the same ranking order in both cases. Besides, EK15 is not in compliance with the expert's view, yet EMK19 is. All results show that EMK19 outperforms EK15.
Assume that the success in low noise densities is more important than in the others. In that case, the values given in Table 7-9 can be represented with three fpfs-matrices as follows: The ranking orders obtained by EK15, EMK19, and expert's view are in Table 10. It must be noted that EK15 has produced the same ranking order in both cases. Besides, EK15 is not in compliance with the expert's view, yet EMK19 is. All results show that EMK19 outperforms EK15.
Table 10. The ranking orders of the filters for EK15, EMK19, and expert’s view 6. Conclusion
Table 10. The ranking orders of the filters for EK15, EMK19, and expert’s view 6. Conclusion
Table 11. The mean/max advantage and max difference values of EMK19 over EK15 Acknowledgements
Table 11. The mean/max advantage and max difference values of EMK19 over EK15 Acknowledgements
Related topics:
Soft SetsSoft MatricesSoft Decision-Makingfpfs-matrices
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