Research Article

Edge Preserved Speckle Noise Reduction Using Integrated Fuzzy Filters

Table 1

Comparison of IQM for fuzzy, geometric-fuzzy, and integrated fuzzy filters.

NoiseMethodFoMSSIMIQISNRPSNRMSE

0.01F10.75140.86590.49170.07550.996643.2527.28121.56
GF10.82590.86970.49470.09310.996643.3827.34119.84
GWF10.86710.89050.54310.15180.996843.8227.57113.81
F20.75900.87500.55300.30160.998449.9430.6256.31
GF20.79320.88350.56520.32840.998550.5730.9452.35
GWF20.88190.92020.61630.45520.998852.1631.7343.62
F30.90660.92210.60020.08070.998248.6229.9765.51
GF30.90990.92280.60020.07010.998248.8730.0963.66
GWF30.86890.91060.59180.06750.998047.8629.5971.50

0.05F10.44350.69300.36460.00800.993135.1623.24308.48
GF10.45630.69930.36650.00010.993336.0023.65280.30
GWF10.55970.78160.42930.02840.995641.0126.16157.29
F20.40230.67810.39900.13150.994639.2425.28192.90
GF20.42390.68450.40490.13740.995039.9625.64177.63
GWF20.51490.77070.47550.23840.997044.3527.83107.16
F30.54650.79500.46470.08880.996841.1826.25154.31
GF30.53830.80210.47040.08780.996942.4626.89133.17
GWF30.59900.80320.47620.09100.996944.2627.79108.27

0.1F10.36270.56710.28690.02300.986427.3619.34757.23
GF10.36590.57570.29240.01520.986928.3419.83676.50
GWF10.44190.68650.3661āˆ’0.00030.993236.9224.12252.01
F20.36930.56910.32650.08540.989833.5322.42372.49
GF20.36600.57760.33410.08600.990434.3222.81340.12
GWF20.45350.67280.40670.16700.994839.7325.52182.38
F30.40400.68210.38330.07640.994033.3522.33380.09
GF30.40200.69270.39030.07320.994334.7523.03323.62
GWF30.46340.71630.41480.08680.995340.2225.77172.35

0.2F10.31640.39170.18510.01740.962617.4214.362380.26
GF10.31410.40380.19320.01760.965418.4114.862124.11
GWF10.37500.56110.29520.01800.987230.7321.02513.91
F20.32830.44950.25180.05820.979427.0919.20781.68
GF20.32940.45490.25640.05520.980227.7919.55721.01
GWF20.37980.56430.33810.11620.990634.4922.90333.25
F30.33990.50720.26950.04740.983322.7817.051283.26
GF30.34790.51720.27520.04860.984724.0417.671110.79
GWF30.38450.59520.33760.07250.991234.0422.67351.27