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Theory and Modern Applications

Table 11 Noise immunity with a \(\pmb{9\times9}\) Canny mask at varying standard deviations (Noise SD)

From: A new construction of a fractional derivative mask for image edge analysis based on Riemann-Liouville fractional derivative

Noise type

Noise SD

20

25

30

35

40

45

Motion

Linear image

0.9714

0.9355

0.9083

0.8639

0.7971

0.7770

Non-linear image

0.8716

0.7344

0.6140

0.5439

0.5036

0.4792

Medical image

0.8199

0.6667

0.5618

0.5152

0.4919

0.4815

Gauss

Linear image

0.4364

0.2718

0.2716

0.2771

0.2089

0.1944

Non-linear image

0.3338

0.2347

0.1542

0.1469

0.1256

0.1021

Medical image

0.4525

0.2374

0.1634

0.1323

0.1140

0.0881

S & P

Linear image

0.7592

0.6748

0.6125

0.5529

0.4473

0.4384

Non-linear image

0.7285

0.6679

0.5631

0.4614

0.4139

0.3344

Medical image

0.6997

0.5756

0.4879

0.4012

0.3158

0.2577

Speckle

Linear image

0.6689

0.4865

0.5035

0.4113

0.4316

0.3536

Non-linear image

0.6958

0.5763

0.5672

0.4927

0.3948

0.3511

Medical image

0.7557

0.7328

0.7107

0.6896

0.6820

0.6588