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Table 2 Comparison in terms of PSNR and FSIM metrics

From: CNN-IKOA: convolutional neural network with improved Kepler optimization algorithm for image segmentation: experimental validation and numerical exploration

T

IKOA

KOA

TLBO

NOA

CPSOGSA

EO

MSSA

SSA

DE

FSIM metric

 T-5

0.9019

0.8978

0.9017

0.9008

0.8941

0.8973

0.8852

0.8849

0.8941

 T-7

0.9347

0.9282

0.9350

0.9314

0.9308

0.9310

0.9194

0.9184

0.9218

 T-8

0.9463

0.9392

0.9445

0.9399

0.9400

0.9431

0.9301

0.9299

0.9334

 T-10

0.9620

0.9527

0.9596

0.9545

0.9572

0.9593

0.9475

0.9476

0.9445

 T-12

0.9715

0.9620

0.9685

0.9622

0.9680

0.9706

0.9591

0.9587

0.9536

 T-15

0.9793

0.9710

0.9770

0.9693

0.9762

0.9788

0.9718

0.9728

0.9652

 T-18

0.9839

0.9779

0.9830

0.9752

0.9833

0.9844

0.9808

0.9804

0.9709

 T-20

0.9866

0.9799

0.9851

0.9790

0.9860

0.9878

0.9842

0.9844

0.9738

 T-25

0.9920

0.9869

0.9901

0.9826

0.9906

0.9911

0.9894

0.9900

0.9800

 T-30

0.9944

0.9906

0.9928

0.9879

0.9933

0.9942

0.9930

0.9930

0.9843

PSNR metric

 T-5

21.8829

21.7525

21.8384

21.8396

21.5796

21.6041

21.1349

21.1479

21.5699

 T-7

24.3285

23.9740

24.2983

24.0920

24.0531

24.0755

23.5550

23.4417

23.6319

 T-8

25.2566

24.8445

25.1949

24.8890

24.8869

25.0859

24.3995

24.3853

24.4867

 T-10

26.9283

26.2704

26.7954

26.4204

26.5411

26.7188

25.9164

25.9121

25.7407

 T-12

28.2530

27.4573

28.0730

27.5082

27.8740

28.0575

27.2579

27.2046

26.8615

 T-15

29.8682

28.9285

29.6784

28.8450

29.4137

29.6845

28.9024

28.9886

28.3238

 T-18

31.3447

30.3176

31.0655

29.9693

30.9277

31.1303

30.4275

30.3859

29.3979

 T-20

32.2371

31.0429

31.7904

30.7317

31.7590

31.9759

31.2544

31.2630

30.0513

 T-25

34.1783

32.9337

33.5885

32.1561

33.5047

33.7189

33.0934

33.1385

31.6174

 T-30

35.6710

34.2938

34.9265

33.7634

34.9790

35.2779

34.5685

34.6315

32.8990

  1. Bold value represents the best finding