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. 2022 Nov 24;8:e1160. doi: 10.7717/peerj-cs.1160

Table 2. Compare of SSIM results for proposed method and others on six images selected from different datasets.

Images Filters 10% 20% 30% 40% 50% 60% 70% 80% 90%
SSIM RESULTS Lena
512×512 		AFMF 0.9614 0.9580 .0.9499 0.9375 0.9191 0.8962 0.8634 0.8155 0.6866
ARmF 0.9912 0.9812 0.9696 0.9561 0.9393 0.9177 0.8881 0.8458 0.7744
IAWMF 0.9911 0.9812 0.9695 0.9561 0.9397 0.9200 0.8936 0.8555 0.7916
ASWMF 0.9787 0.9557 0.9314 0.9044 0.8734 0.8375 0.7903 0.7302 0.6355
AWMF 0.9822 0.9737 0.9634 0.9507 0.9344 0.9136 0.8848 0.8434 0.7730
DAMF 0.9904 0.9790 0.9655 0.9497 0.9308 0.9086 0.8794 0.8384 0.7654
IMF 0.9904 0.9798 0.9676 0.9545 0.9392 0.9206 0.8974 0.8636 0.8084
TSF 0.9904 0.9790 0.9655 0.9497 0.9308 0.9087 0.8796 0.8398 0.7723
MSCF-1 0.9905 0.9800 0.9678 0.9539 0.9369 0.9154 0.8865 0.8487 0.7924
DAMRmF 0.9912 0.9812 0.9696 0.9565 0.9405 0.9212 0.8952 0.8581 0.7958
SFT_lp 0.9914 0.9817 0.9702 0.9573 0.9415 0.9223 0.8965 0.8587 0.7935
Bilal’s Method 0.9899 0.9765 0.9602 0.9397 0.9145 0.8829 0.8414 0.7875 0.6984
NVBMF 0.9915 0.9811 0.9676 0.9513 0.9416 0.9247 0.9025 0.8698 0.8120
Cameraman
512×512 		AFMF 0.9892 0.9850 0.9788 0.9705 0.9572 0.9393 0.9127 0.8693 0.7390
ARmF 0.9972 0.9938 0.9896 0.9839 0.9752 0.9630 0.9439 0.9122 0.8459
IAWMF 0.9969 0.9937 0.9896 0.9839 0.9757 0.9646 0.9474 0.9186 0.8575
ASWMF 0.9800 0.9600 0.9363 0.9110 0.8789 0.8406 0.7886 0.7158 0.6050
AWMF 0.9884 0.9857 0.9821 0.9772 0.9693 0.9580 0.9398 0.9089 0.8434
DAMF 0.9967 0.9921 0.9859 0.9781 0.9673 0.9541 0.9355 0.9046 0.8575
IMF 0.9964 0.9921 0.9864 0.9793 0.9696 0.9558 0.9381 0.9079 0.8496
TSF 0.9967 0.9921 0.9859 0.9781 0.9673 0.9540 0.9351 0.9045 0.8393
MSCF-1 0.9966 0.9928 0.9880 0.9820 0.9728 0.9606 0.9419 0.9130 0.8567
DAMRmF 0.9971 0.9938 0.9895 0.9836 0.9748 0.9634 0.9457 0.9168 0.8563
SFT_lp 0.9972 0.9935 0.9884 0.9812 0.9706 0.9563 0.9333 0.8975 0.8279
Bilal’s method 0.9961 0.9894 0.9798 0.9665 0.9464 0.9193 0.8829 0.8285 0.7430
NVBMF 0.9978 0.9943 0.9895 0.9820 0.9736 0.9630 0.9480 0.9226 0.8664
Airplane
512×512 		AFMF 0.9731 0.9667 0.9599 0.9488 0.9321 0.9094 0.8768 0.8301 0.6990
ARmF 0.9939 0.9868 0.9786 0.9679 0.9541 0.9346 0.9070 0.8682 0.7951
IAWMF 0.9938 0.9868 0.9787 0.9683 0.9550 0.9368 0.9122 0.8771 0.8107
ASWMF 0.9774 0.9536 0.9276 0.8978 0.8621 0.8166 0.7571 0.6782 0.5561
AWMF 0.9834 0.9766 0.9693 0.9595 0.9463 0.9278 0.9011 0.8636 0.7922
DAMF 0.9932 0.9842 0.9741 0.9614 0.9455 0.9246 0.8977 0.8604 0.7858
IMF 0.9929 0.9847 0.9752 0.9638 0.9502 0.9310 0.9083 0.8745 0.8127
TSF 0.9932 0.9842 0.9741 0.9614 0.9454 0.9244 0.8970 0.8601 0.7910
MSCF-1 0.9928 0.9846 0.9754 0.9641 0.9497 0.9301 0,9034 0.8686 0.8084
DAMRmF 0.9939 0.9867 0.9785 0.9681 0.9550 0.9369 0.9118 0.8779 0.8120
SFT_lp 0.9942 0.9870 0.9781 0.9666 0.9520 0.9320 0.9048 0.8642 0.7915
Bilal’s Method 0.9924 0.9815 0.9677 0.9485 0.9233 0.8890 0.8425 0.7814 0.6848
NVBMF 0.9948 0.9877 0.9787 0.9659 0.9532 0.9369 0.9159 0.8852 0.8239
micromarket
2,336×3,504 MATLAB Library (R2020b)		 AFMF 0.9813 0.9766 0.9693 0.9586 0.9439 0.9235 0.8941 0.8484 0.7147
ARmF 0.9957 0.9908 0.9848 0.9770 0.9664 0.9512 0.9284 0.8923 0.8202
IAWMF 0.9956 0.9908 0.9849 0.9772 0.9671 0.9532 0.9329 0.9005 0.8362
ASWMF 0.9798 0.9584 0.9347 0.9071 0.8739 0.8315 0.7747 0.6922 0.5664
AWMF 0.9868 0.9822 0.9769 0.9698 0.9602 0.9457 0.9237 0.8883 0.8172
DAMF 0.9952 0.9888 0.9803 0.9694 0.9563 0.9397 0.9173 0.8823 0.8099
IMF 0.9948 0.9888 0.9815 0.9724 0.9607 0.9452 0.9233 0.8911 0.8359
TSF 0.9953 0.9889 0.9804 0.9695 0.9564 0.9399 0.9176 0.8833 0.8138
MSCF-1 0. 9950 0.9894 0.9828 0.9744 0.9635 0.9482 0.9261 0.8941 0.8362
DAMRmF 0.9952 0.9901 0.9842 0.9763 0.9663 0.9523 0.9319 0.9002 0.8380
SFT_lp 0.9665 0.9919 0.9859 0.9779 0.9671 0.9522 0.9299 0.8944 0.8273
Bilal’s method 0.9950 0.9868 0.9749 0.9581 0.9354 0.9044 0.8602 0.7957 0.6938
NVBMF 0.9964 0.9915 0.9846 0.9749 0.9661 0.9540 0.9369 0.9099 0.8533
img_600 × 600_1 × 8 bit_B01C00GRAY_apples
600×600 TESTIMAGES
dataset		 AFMF 0.9857 0.9814 0.9762 0.9687 0.9606 0.9488 0.9291 0.8982 0.7751
ARmF 0.9973 0.9943 0.9905 0.9856 0.9791 0.9695 0.9547 0.9314 0.8840
IAWMF 0.9972 0.9943 0.9905 0.9856 0.9794 0.9707 0.9580 0.9375 0.8970
ASWMF 0.9874 0.9734 0.9569 0.9364 0.9109 0.8769 0.8275 0.7526 0.6316
AWMF 0.9924 0.9897 0.9864 0.9818 0.9757 0.9667 0.9523 0.9296 0.8828
DAMF 0.9967 0.9928 0.9877 0.9813 0.9736 0.9635 0.9484 0.9242 0.8726
IMF 0.9969 0.9934 0.9892 0.9839 0.9775 0.9696 0.9577 0.9405 0.9110
TSF 0.9967 0.9928 0.9877 0.9813 0.9735 0.9634 0.9487 0.9263 0.8797
MSCF-1 0.9970 0.9936 0.9895 0.9843 0.9776 0.9680 0.9538 0.9340 0.8986
DAMRmF 0.9957 0.9920 0.9885 0.9839 0.9787 0.9707 0.9582 0.9385 0.9004
SFT_lp 0.9973 0.9942 0.9904 0.9852 0.9789 0.9702 0.9571 0.9373 0.9004
Bilal’s method 0.9962 0.9909 0.9834 0.9726 0.9584 0.9396 0.9122 0.8697 0.7899
NVBMF 0.9976 0.9945 0.9900 0.9837 0.9801 0.9734 0.9635 0.9478 0.9137
187083
321×481 Berkeley 200 sataset		 AFMF 0.9766 0.9702 0.9624 0.9504 0.9343 0.9095 0.8771 0.8287 0.6773
ARmF 0.9942 0.9869 0.9789 0.9686 0.9555 0.9358 0.9089 0.8684 0.7941
IAWMF 0.9942 0.9871 0.9793 0.9692 0.9565 0.9384 0.9143 0.8784 0.8130
ASWMF 0.9807 0.9588 0.9361 0.9086 0.8776 0.83.72 0.7828 0.7071 0.5958
AWMF 0.9859 0.9786 0.9709 0.9614 0.9491 0.9299 0.9039 0.8645 0.7917
DAMF 0.9937 0.9849 0.9743 0.9615 0.9459 0.9246 0.8979 0.8588 0.7845
IMF 0.9931 0.9849 0.9759 0.9652 0.9525 0.9351 0.9143 0.8824 0.8307
TSF 0.9937 0.9849 0.9743 0.9615 0.9459 0.9245 0.8986 0.8603 0.7906
MSCF-1 0.9933 0.9851 0.9764 0.9655 0.9520 0.9323 0.9067 0.8713 0.8135
DAMRmF 0.9942 0.9869 0.9789 0.9687 0.9561 0.9381 0.9143 0.8794 0.8168
SFT_lp 0.9951 0.9880 0.9805 0.9699 0.9569 0.9389 0.9147 0.8763 0.8097
Bilal’s method 0.9936 0.9825 0.9687 0.9505 0.9260 0.8926 0.8472 0.7796 0.6755
NVBMF 0.9951 0.9880 0.9789 0.9667 0.9558 0.9403 0.9204 0.8904 0.8332