Super-resolution imaging

Super-resolution imaging (SR) is a class of techniques that enhance the resolution of an imaging system. In some SR techniques—termed optical SR—the diffraction limit of systems is transcended, while in others—geometrical SR—the resolution of digital imaging sensors is enhanced.

In some radar and sonar imaging applications (e.g., magnetic resonance imaging (MRI), high-resolution computed tomography), subspace decomposition-based methods (e.g., MUSIC) and compressed sensing-based algorithms (e.g., SAMV) are employed to achieve SR over standard periodogram algorithm.

Super-resolution imaging techniques are used in general image processing and in super-resolution microscopy.

Categories

• Exploiting Diffusion Prior for Real-World Image Super-Resolution (StableSR)
• Zoomed LQ images
• SUPIR

See also

• Deep learning

Favorite site

• Wikipedia (en) Super-resolution imaging
• [추천] SlideShare - Deep learning super resolution (딥러닝 Super Resolution, 어디까지 왔니?)
• [추천] HOYA012'S RESEARCH BLOG - Single Image Super Resolution using Deep Learning Overview ¹

References