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Combination of Single and Multi-frame Image Super-resolution: An Analytical Perspective

arXiv 2303.03212 ↗First posted 6 Mar 2023cs.CV eess.IVcited by 0

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Abstract (arXiv)

Super-resolution is the process of obtaining a high-resolution image from one or more low-resolution images. Single image super-resolution (SISR) and multi-frame super-resolution (MFSR) methods have been evolved almost independently for years. A neglected study in this field is the theoretical analysis of finding the optimum combination of SISR and MFSR. To fill this gap, we propose a novel theoretical analysis based on the iterative shrinkage and thresholding algorithm. We implement and compare several approaches for combining SISR and MFSR, and simulation results support the finding of our theoretical analysis, both quantitatively and qualitatively.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 22 of its 64 references that are in the map. First posted on arXiv 6 Mar 2023.

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22 of 64 references.

References · 22

  1. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,694
  2. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,908
  3. 2021Image Super-Resolution via Iterative Refinementcited by 1,511
  4. 2018ESRGAN: Enhanced Super-Resolution Generative Adversarial Networkscited by 1,254
  5. 2014Image Super-Resolution Using Deep Convolutional Networkscited by 1,224
  6. 2015Accurate Image Super-Resolution Using Very Deep Convolutional Networkscited by 903
  7. 2018Residual Dense Network for Image Super-Resolutioncited by 799
  8. 2014Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognitioncited by 720
  9. 2019Deep Learning for Image Super-resolution: A Surveycited by 369
  10. 2020SRFlow: Learning the Super-Resolution Space with Normalizing Flowcited by 209
  11. 2014Part-based R-CNNs for Fine-grained Category Detectioncited by 109
  12. 2019Handheld Multi-Frame Super-Resolutioncited by 85
10 more
  1. 2021Deep Burst Super-Resolutioncited by 83
  2. 2020HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagerycited by 42
  3. 2019DeepSUM: Deep neural network for Super-resolution of Unregistered Multitemporal imagescited by 30
  4. 2020Multi-image Super Resolution of Remotely Sensed Images using Residual Feature Attention Deep Neural Networkscited by 22
  5. 2021Structure-Preserving Image Super-Resolutioncited by 18
  6. 2019Deep Learning for Multiple-Image Super-Resolutioncited by 15
  7. 2021Toward Real-World Super-Resolution via Adaptive Downsampling Modelscited by 14
  8. 2021Exploiting Raw Images for Real-Scene Super-Resolutioncited by 12
  9. 2022Bayesian Image Super-Resolution with Deep Modeling of Image Statisticscited by 11
  10. 2021Transitional Learning: Exploring the Transition States of Degradation for Blind Super-resolutioncited by 4

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