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Yaru Zhang, Jiantao Liu, Tong Zhang and Zhibiao Zhao
In the process of stereo super-resolution reconstruction, in addition to the richness of the extracted feature information directly affecting the texture details of the reconstructed image, the texture details of the corresponding pixels between stereo i...
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Valdivino Alexandre de Santiago Júnior
Despite several solutions and experiments have been conducted recently addressing image super-resolution (SR), boosted by deep learning (DL), they do not usually design evaluations with high scaling factors. Moreover, the datasets are generally benchmark...
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Asif Hussain Khan, Christian Micheloni and Niki Martinel
Blind image super-resolution (Blind-SR) is the process of leveraging a low-resolution (LR) image, with unknown degradation, to generate its high-resolution (HR) version. Most of the existing blind SR techniques use a degradation estimator network to expl...
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Zhihang Liu, Pengfei He and Feifei Wang
Image super-resolution reconstruction technology can boost image resolution and aid in the discovery of PCB flaws. The traditional SRGAN algorithm produces reconstructed images with great realism, but it also has the disadvantages of insufficient feature...
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Ryeonhui Kim, Kyuseok Kim and Youngjin Lee
Ultrasound imaging is widely used as a noninvasive lesion detection method in diagnostic medicine. Improving the quality of these ultrasound images is very important for accurate diagnosis, and deep learning-based algorithms have gained significant atten...
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