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Survey of single image super‐resolution reconstruction [PDF]
IET Image Processing, 2020 Image super‐resolution reconstruction refers to a technique of recovering a high‐resolution (HR) image (or multiple images) from a low‐resolution (LR) degraded image (or multiple images).
Kai Li +4 more
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Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal, 2019 Super-Resolution (SR) of a single image is a classic problem in computer vision. The goal of image super-resolution is to produce a high-resolution image from a low-resolution image. This paper presents a popular model, super-resolution convolutional neural network (SRCNN), to solve this problem. This paper also examines an improvement to SRCNN using a
Yujing Song
core +5 more sources
Pyramidal dense attention networks for single image super‐resolution
IET Image Processing, 2022 Recently, residual and dense networks have effectively promoted the development of image super‐resolution (SR). However, most dense networks based SR methods do not make full use of dense feature information.
Huapeng Wu +4 more
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Quantitative Assessment of Single-Image Super-Resolution in Myocardial Scar Imaging [PDF]
IEEE Journal of Translational Engineering in Health and Medicine, 2014 Single-image super resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super resolution has been demonstrated to improve image quality in scaled down images in the image ...
Hiroshi Ashikaga +4 more
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Single Image Super-resolution using Deformable Patches. [PDF]
Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit, 2014 We proposed a deformable patches based method for single image super-resolution. By the concept of deformation, a patch is not regarded as a fixed vector but a flexible deformation flow. Via deformable patches, the dictionary can cover more patterns that do not appear, thus becoming more expressive.
Zhu Y, Zhang Y, Yuille AL.
europepmc +4 more sources
Single image super-resolution with denoising diffusion GANS [PDF]
Scientific ReportsSingle image super-resolution (SISR) refers to the reconstruction from the corresponding low-resolution (LR) image input to a high-resolution (HR) image. However, since a single low-resolution image corresponds to multiple high-resolution images, this is
Heng Xiao +6 more
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Single image super-resolution by approximated Heaviside functions [PDF]
Information Sciences, 2016 Image super-resolution is a process to enhance image resolution. It is widely used in medical imaging, satellite imaging, target recognition, etc. In this paper, we conduct continuous modeling and assume that the unknown image intensity function is defined on a continuous domain and belongs to a space with a redundant basis.
Liang-Jian Deng +2 more
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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
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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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A comprehensive review of deep learning-based single image super-resolution.
PeerJ Comput Sci, 2021 Bashir SMA, Wang Y, Khan M, Niu Y.
europepmc +2 more sources