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Theory and Modern Applications

Table 1 Quantitative analysis of obtained results of FPMM and PMM for denoising the test case 1 with the Gaussian noise

From: A time-splitting local meshfree approach for time-fractional anisotropic diffusion equation: application in image denoising

 

SNR

PSNR

SSIM

MSE

Noisy image (variance 0.01)

14.5313

20.0380

0.2617

644.5915

FPMM (α = 0.9, K = 100, iteration = 20)

23.4089

29.1101

0.7721

89.6835

PMM (K = 4, iteration = 20)

22.5107

28.1970

0.7148

100.4876

Noisy image (variance 0.05)

13.2799

17.5327

0.2599

1.1476e + 03

FPMM (α = 0.9, K = 100, iteration = 32)

20.9961

26.7036

0.5994

189.9814

PMM (K = 100, iteration = 32)

20.5716

25.8288

0.7525

169.9014

Noisy image (variance 0.09)

8.5878

13.6391

0.0980

2.81e + 03

FPMM (α = 0.9, K = 105, iteration = 50)

19.4164

25.1185

0.5634

231.1342

PMM (K = 100, iteration = 50)

19.1496

24.18522

0.5023

245.7101