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Table 4 Performance comparison of the proposed and the well-known SR algorithms in term in term of SSIM

From: An iterative enhanced super-resolution system with edge-dominated interpolation and adaptive enhancements

Images

Resolution

NNI

Bilinear

Bi-cubic

Learn

IBP

NBP

Proposed method

N1

2,048 × 2,560

0.87807

0.87695

0.89103

0.89878

0.92988

0.92936

0.93357

N2

2,048 × 2,560

0.79524

0.79704

0.81697

0.83103

0.87577

0.87184

0.88535

N5

2,048 × 2,560

0.86975

0.86842

0.87793

0.88466

0.90397

0.90015

0.90851

N4

2,560 × 2,048

0.87034

0.87128

0.88325

0.89372

0.91185

0.90992

0.918056

N6

2,560 × 2,048

0.94077

0.94292

0.94631

0.94561

0.95827

0.95437

0.95806

N7

2,560 × 2,048

0.76907

0.76136

0.77935

0.79448

0.82491

0.81377

0.83420

N8

2,560 × 2,048

0.76006

0.74829

0.77434

0.79841

0.83508

0.82489

0.84462

QFHD_P01

3,840 × 2,160

0.95470

0.96237

0.96766

0.96913

0.98298

0.97873

0.98348

QFHD_P03

3,840 × 2,160

0.84092

0.84207

0.86495

0.88436

0.91576

0.90496

0.92390

QFHD_P04

3,840 × 2,160

0.94705

0.95413

0.96020

0.96187

0.97881

0.97246

0.97839

world_satellite

6,000 × 4,190

0.84918

0.84998

0.86774

0.88021

0.91977

0.90765

0.92557

Average

0.86138

0.86135

0.87543

0.88566

0.91246

0.90619

0.91761