Results 51 to 60 of about 1,135,244 (321)
Parallel super-resolution imaging [PDF]
Nature Methods, 2013 Massive parallelization of scanning-based super-resolution imaging allows fast imaging of large fields of view.
Yew, Elijah Y S +2 more
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Image Super-Resolution Using Generative Adversarial Networks with Learned Degradation Operators [PDF]
MATEC Web of Conferences, 2022 Image super-resolution is a research endeavour that has gained notoriety in computer vision. The research goal is to increase the spatial dimensions of an image using corresponding low-resolution and high-resolution image pairs to enhance the perceptual ...
Molefe Molefe, Klein Richard
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Lightweight Image Super-Resolution with Information Multi-distillation Network [PDF]
ACM Multimedia, 2019 In recent years, single image super-resolution (SISR) methods using deep convolution neural network (CNN) have achieved impressive results. Thanks to the powerful representation capabilities of the deep networks, numerous previous ways can learn the ...
Zheng Hui +3 more
semanticscholar +1 more source
FRESH – FRI-based single-image super-resolution algorithm [PDF]
, 2016 In this paper, we consider the problem of single image super-resolution and propose a novel algorithm that outperforms state-of-the-art methods without the need of learning patches pairs from external data sets.
Dragotti, P, Wei, X
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Deep Learning for Image Super-Resolution: A Survey [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning techniques ...
Zhihao Wang, Jian Chen, S. Hoi
semanticscholar +1 more source
Feedback Network for Image Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2019 Recent advances in image super-resolution (SR) explored the power of deep learning to achieve a better reconstruction performance. However, the feedback mechanism, which commonly exists in human visual system, has not been fully exploited in existing ...
Z. Li +5 more
semanticscholar +1 more source
Correction to: Single Image Super-Resolution via a Holistic Attention Network [PDF]
European Conference on Computer Vision, 2020 Informative features play a crucial role in the single image super-resolution task. Channel attention has been demonstrated to be effective for preserving information-rich features in each layer.
Ben Niu +8 more
semanticscholar +1 more source
Image Super-resolution Reconstruction Based on Sparse Representation and Guided Filtering [PDF]
Jisuanji gongcheng, 2018 In view of the fact that the image super-resolution reconstruction method cannot effectively reconstruct more high frequency image information in the process of image processing and storage,this paper proposes an image super-resolution reconstruction ...
ZHANG Wanxu,SHI Jianxiong,CHEN Xiaoxuan,WANG Lin,ZHAO Ming,ZHOU Yan,NIU Jinping
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Super-resolution microscopy based on interpolation and wide spectrum de-noising
Компьютерная оптика, 2023 In the conventional single-molecule localizations and super-resolution microscopy, the pixel size of a raw image is approximately equal to the standard deviation of the point spread function.
T. Cheng, T. Chenchen
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Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Despite that convolutional neural networks (CNN) have recently demonstrated high-quality reconstruction for single-image super-resolution (SR), recovering natural and realistic texture remains a challenging problem.
Xintao Wang +3 more
semanticscholar +1 more source