Cascaded Degradation-Aware Blind Super-Resolution [PDF]
Sensors, 2023 Image super-resolution (SR) usually synthesizes degraded low-resolution images with a predefined degradation model for training. Existing SR methods inevitably perform poorly when the true degradation does not follow the predefined degradation ...
Ding Zhang +3 more
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Blur Kernel Estimation and Non-Blind Super-Resolution for Power Equipment Infrared Images by Compressed Sensing and Adaptive Regularization [PDF]
Sensors, 2021 Infrared sensing technology is more and more widely used in the construction of power Internet of Things. However, due to cost constraints, it is difficult to achieve the large-scale installation of high-precision infrared sensors.
Hongshan Zhao +2 more
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Research on Blind Super-Resolution Technology for Infrared Images of Power Equipment Based on Compressed Sensing Theory [PDF]
Sensors, 2021 Infrared images of power equipment play an important role in power equipment status monitoring and fault identification. Aiming to resolve the problems of low resolution and insufficient clarity in the application of infrared images, we propose a blind ...
Yan Wang +3 more
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High-speed blind structured illumination microscopy via unsupervised algorithm unrolling [PDF]
Nature CommunicationsBlind structured illumination microscopy (blind-SIM) is a valuable tool for achieving super-resolution without the need for known illumination patterns.
Zachary Burns +4 more
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Blind Image Super-Resolution: A Survey and Beyond
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Blind image super-resolution (SR), aiming to super-resolve low-resolution images with unknown degradation, has attracted increasing attention due to its significance in promoting real-world applications. Many novel and effective solutions have been proposed recently, especially with the powerful deep learning techniques.
Anran Liu +4 more
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A Progressive Decoupled Network for Blind Image Super-Resolution
IEEE AccessBlind super-resolution (Blind SR) has become a popular research topic in computer vision in super-resolution, which aims to enhance low-resolution (LR) images with unknown or partially known degradation blur kernels.
Laigan Luo, Benshun Yi, Chao Zhu
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Enhancing fetal ultrasound image quality and anatomical plane recognition in low-resource settings using super-resolution models [PDF]
Scientific ReportsSuper-resolution (SR) techniques present a suitable solution to increase the image resolution acquired using an ultrasound device characterized by a low image resolution. This can be particularly beneficial in low-resource imaging settings.
Hafida Boumeridja +8 more
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Lightweight Implicit Blur Kernel Estimation Network for Blind Image Super-Resolution
Information, 2023 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.
Asif Hussain Khan +2 more
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Deep Learning-Based Single-Image Super-Resolution: A Comprehensive Review
IEEE Access, 2023 High-fidelity information, such as 4K quality videos and photographs, is increasing as high-speed internet access becomes more widespread and less expensive.
Karansingh Chauhan +7 more
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Pixel-Level Kernel Estimation for Blind Super-Resolution
IEEE Access, 2021 Throughout the past several years, deep learning-based models have achieved success in super-resolution (SR). The majority of these works assume that low-resolution (LR) images are ‘uniformly’ degraded from their corresponding high ...
Jaihyun Lew, Euiyeon Kim, Jae-Pil Heo
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