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Theory and Modern Applications

Table 9 Noise immunity with a \(\pmb{7\times7}\) 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

0.9770

0.9352

0.9112

0.8528

0.7886

0.7685

Non-linear image

0.8399

0.7029

0.5816

0.5188

0.4836

0.4618

Medical image

0.8096

0.6450

0.5414

0.5034

0.4873

0.4756

Gauss

Linear image

0.3329

0.2984

0.1984

0.2002

0.1816

0.1355

Non-linear image

0.2168

0.1610

0.1409

0.1130

0.0946

0.0866

Medical image

0.3416

0.2301

0.1167

0.1014

0.0668

0.0595

S & P

Linear image

0.7577

0.6590

0.5930

0.5193

0.4242

0.3738

Non-linear image

0.7300

0.6223

0.5186

0.4388

0.3857

0.3127

Medical image

0.6902

0.5847

0.5017

0.3985

0.3274

0.2593

Speckle

Linear image

0.5638

0.4109

0.4196

0.3537

0.3592

0.3213

Non-linear image

0.6205

0.4995

0.4910

0.4148

0.3456

0.3378

Medical image

0.7696

0.7213

0.7005

0.6748

0.6673

0.6574