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Exploiting Diffusion Prior for Real-World Image Super-Resolution
International Journal of Computer Vision, 2023We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-to-image diffusion models for blind super-resolution. Specifically, by employing our time-aware encoder, we can achieve promising restoration results without ...
Jianyi Wang +4 more
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Image Super-Resolution Using Very Deep Residual Channel Attention Networks
European Conference on Computer Vision, 2018Convolutional neural network (CNN) depth is of crucial importance for image super-resolution (SR). However, we observe that deeper networks for image SR are more difficult to train.
Yulun Zhang +5 more
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Image Super-Resolution via Deep Recursive Residual Network
Computer Vision and Pattern Recognition, 2017Recently, Convolutional Neural Network (CNN) based models have achieved great success in Single Image Super-Resolution (SISR). Owing to the strength of deep networks, these CNN models learn an effective nonlinear mapping from the low-resolution input ...
Ying Tai, Jian Yang, Xiaoming Liu
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Second-Order Attention Network for Single Image Super-Resolution
Computer Vision and Pattern Recognition, 2019Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution (SISR) and obtained remarkable performance.
Tao Dai +4 more
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Super-resolution acoustic imaging
Applied Physics Letters, 2022This work reports a super-resolution acoustic imaging method that inverses source distribution, strength, and structure in three-dimensional space. The nonlinear coupling process between a low-frequency sound field and a high-frequency plane wave is endowed to break the resolution limit.
Wangqiao Chen, Hanbo Jiang, Xun Huang
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Super-Resolution Imaging and Plasmonics
Chemical Reviews, 2017This review describes the growing partnership between super-resolution imaging and plasmonics, by describing the various ways in which the two topics mutually benefit one another to enhance our understanding of the nanoscale world. First, localization-based super-resolution imaging strategies, where molecules are modulated between emissive and ...
Katherine A. Willets +3 more
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Image Super-Resolution with Non-Local Sparse Attention
Computer Vision and Pattern Recognition, 2021Both Non-Local (NL) operation and sparse representation are crucial for Single Image Super-Resolution (SISR). In this paper, we investigate their combinations and propose a novel Non-Local Sparse Attention (NLSA) with dynamic sparse attention pattern ...
Yiqun Mei, Yuchen Fan, Yuqian Zhou
semanticscholar +1 more source
Super-resolution in PET imaging
IEEE Transactions on Medical Imaging, 2006This paper demonstrates a super-resolution method for improving the resolution in clinical positron emission tomography (PET) scanners. Super-resolution images were obtained by combining four data sets with spatial shifts between consecutive acquisitions and applying an iterative algorithm.
John A, Kennedy +4 more
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Dual Aggregation Transformer for Image Super-Resolution
IEEE International Conference on Computer Vision, 2023Transformer has recently gained considerable popularity in low-level vision tasks, including image super-resolution (SR). These networks utilize self-attention along different dimensions, spatial or channel, and achieve impressive performance.
Zheng Chen +5 more
semanticscholar +1 more source
Super‐resolution image reconstruction using multisensors
Numerical Linear Algebra with Applications, 2004AbstractSuper‐resolution image reconstruction refers to obtaining an image at a resolution higher than that of a camera (sensor) used in recording the image. In this paper, we present a new joint minimization model in which an objective function is set up consisting of three terms: the data fitting term, the regularization terms for the reconstructed ...
Ng, MK, Yau, AC, Sze, KN, Ching, WK
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