Research Article

Edge Preserved Speckle Noise Reduction Using Integrated Fuzzy Filters

Table 4

Comparison of edge preserving parameters.

ReferenceMethodFoMIQISSIMPSNRMSESNR

[2, 31]Kaun0.86010.54250.916631.260.998648.6051.22
[2, 20]Lee0.87380.53790.914031.140.998650.0550.96
[2, 19]Frost0.80340.59700.904631.640.998744.5351.98
[10]DPAD0.62900.57500.872129.610.998271.2247.90
[2, 7]SRAD0.77630.58220.883425.700.9960174.8540.10
[2, 8]PMAD0.59160.44680.839627.040.9964128.6042.76
[9]CED0.60020.48960.812626.380.9958149.6141.45
[30]hmedian0.66680.53320.866229.600.998071.3247.88
[25]PPB0.86550.64110.953533.990.999325.9556.67
[22]AFTV0.52190.50950.820927.140.9965125.6042.97
[24]NLM0.88810.63770.940325.440.9971185.7639.57
[15]GLM0.82180.58460.930932.150.998939.6252.99
[13]ProbShrink0.83770.56780.897029.010.997781.6946.71
[14]MPT0.50450.50870.772626.800.9962135.7242.30
[26]RNLA0.78690.51250.888429.950.998165.7248.59
[16]OWT0.63770.47140.808625.710.9951174.5940.11
[17]MBR0.76340.55600.900127.060.9964127.8542.81
[3]PSBE0.52810.47020.807025.670.9951176.1640.03
[32]Curvelets0.62110.47070.806825.660.9950176.6640.01
[23]FBL0.78040.54460.908730.540.998457.4549.76
[21]ATV0.84770.58560.930932.330.998938.0351.22
ProposedGW0.77050.60010.906527.570.998844.5743.82
GF30.90990.60020.922830.090.998263.6652.14
GWF10.86710.54310.890527.570.9968113.8147.89
GWF20.88190.61630.920231.730.998843.6251.35

SRAD: speckle reducing anisotropic diffusion, PMAD: Perona and Malik AD, CED: coherence enhancing diffusion, hmedian: hybrid median, AFTV: adaptive fidelity total variation, GLM: generalized likelihood method, ProbShrink: probability based shrinkage, MPT: multiscale product thresholding, RNLA: Ripplet with nonlinear approximation, OWT: orthogonal wavelet thresholding, MBR: m-band ridgelet, PSBE: posterior sampling based estimation, FBL: fast bilateral, ATV: anisotropic total variation.