Entropy, 2023 When traditional super-resolution reconstruction methods are applied to infrared thermal images, they often ignore the problem of poor image quality caused by the imaging mechanism, which makes it difficult to obtain high-quality reconstruction results ...
Yichun Jiang +3 more
doaj +2 more sources
Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network [PDF]
Computer Vision and Pattern Recognition, 2016 Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resolution (LR) input image is upscaled
Aitken, AP +7 more
core +5 more sources
Review of Image Super-resolution Reconstruction Algorithms Based on Deep Learning [PDF]
Jisuanji kexue yu tansuo, 2022 The essence of image super-resolution reconstruction technology is to break through the limitation of hardware conditions, and reconstruct a high-resolution image from a low-resolution image which contains less infor-mation through the image super ...
YANG Caidong, LI Chengyang, LI Zhongbo, XIE Yongqiang, SUN Fangwei, QI Jin
doaj +1 more source
Review of Super-Resolution Image Reconstruction Algorithms [PDF]
Jisuanji kexue yu tansuo, 2022 In human visual perception system, high-resolution (HR) image is an important medium to clearly express its spatial structure, detailed features, edge texture and other information, and it has a very wide range of practical value in medicine, criminal ...
ZHONG Mengyuan, JIANG Lin
doaj +1 more source
Image Super-Resolution Reconstruction Method Based on Embeddable Network Structure [PDF]
Jisuanji gongcheng, 2021 The existing Super-Resolution(SR) image reconstruction models based on Convolutional Neural Networks(CNN) have multiple deficiencies,such as instable model training process and low convergence speed.To address the problem,this paper proposes an ...
QIANG Baohua, PANG Yuanchao, YANG Minghao, ZENG Kun, ZHENG Hong, XIE Wu, MO Ye
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Remote sensing image Super-resolution reconstruction by fusing multi-scale receptive fields and hybrid transformer. [PDF]
Sci RepTo enhance high-frequency perceptual information and texture details in remote sensing images and address the challenges of super-resolution reconstruction algorithms during training, particularly the issue of missing details, this paper proposes an ...
Liu D, Zhong L, Wu H, Li S, Li Y.
europepmc +2 more sources
Dual-Diffusion: Dual Conditional Denoising Diffusion Probabilistic Models for Blind Super-Resolution Reconstruction in RSIs [PDF]
IEEE Geoscience and Remote Sensing Letters, 2023 Previous super-resolution (SR) reconstruction works are always designed on the assumption that the degradation operation is fixed, such as bicubic downsampling.
Mengze Xu, Jie Ma, Yuanyuan Zhu
semanticscholar +1 more source
Super-resolution reconstruction based on two-stage residual neural network
Machine Learning with Applications, 2021 With the constant update of deep learning technology, the super-resolution reconstruction technology based on deep learning has also attained a significant breakthrough. This paper primarily discusses the integration of deep learning and super-resolution
Lin Dong, Kohei Inoue
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Joint Image Reconstruction and Super-Resolution for Accelerated Magnetic Resonance Imaging
Bioengineering, 2023 Magnetic resonance (MR) image reconstruction and super-resolution are two prominent techniques to restore high-quality images from undersampled or low-resolution k-space data to accelerate MR imaging. Combining undersampled and low-resolution acquisition
Wei Xu +6 more
doaj +1 more source
Iterative Back Projection Network Based on Deformable 3D Convolution
IEEE Access, 2023 Video super-resolution technology enhances the display quality of videos by obtaining high-resolution videos from low-resolution videos. Unlike single-image super-resolution, utilizing information between adjacent video frames is crucial in video super ...
Chengzhi Luo, Bing Li, Feng Liu
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