Medical Image Super-Resolution Based on Semantic Perception Transfer Learning

Ren, Siming; Guo, Kehua; Hu, Bin; Zhu, Feihong; Luo, Entao

doi:10.1109/tcbb.2022.3212343

Cited by 4 publications

(1 citation statement)

References 44 publications

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“…SISR restores high resolution frames from one low-resolution frames of the same view, MISR restores high resolution frames from two or more low-resolution frames of the same view and VSR restores high resolution video from low resolution video. There are voluminous applications like video surveillance [1], [2], medical imaging [3]- [5], astronomy [6], [7], remote sensing [8], and so on.…”

Section: Introductionmentioning

confidence: 99%

Review on Video Super Resolution: Methods and Metrics

Reshma¹,

Thomas²

2023

2023 International Conference on Control, Communication and Computing (ICCC)

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Video Super Resolution (VSR) is a wide area in image processing, where numerous research works are going on. Super Resolution (SR) means the upstaging of Low Resolution (LR) frames to High Resolution (HR) frames with minimal loss in image quality. The goal of this paper is to give the comprehensive review of various VSR methods like Convolutional Neural Network (CNN), Generative Adversarial Network (GAN), Gated Recurrent Unit (GRU), Spatial Temporal Transformer (STT), Fractional-Sine Cosine Algorithm (F-SCA), Recurrent Back-Projection Network (RBPN), Temporally-Deformable Alignment Network (TDAN). Finally, the readers will get more ideas about VSR based methods and metrics.

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