Quantitative Assessment of Single-Image Super-Resolution in Myocardial Scar Imaging [PDF]
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 with denoising diffusion GANS [PDF]
Single 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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Review of Image Super-resolution Reconstruction Algorithms Based on Deep Learning [PDF]
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]
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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Learning Curvelet-based Directional Dictionaries for Single Image Super Resolution [PDF]
Learning and reconstruction-based methods are the two main approaches to the solve single image super resolution (SISR) problem. In this paper, to exploit the advantages of both learning based and reconstruction based approaches, we propose a new SISR ...
Elhameh Mikaeli +2 more
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SUPER RESOLUTION FOR SINGLE SATELLITE IMAGE USING A GENERATIVE ADVERSARIAL NETWORK [PDF]
Inspired by the immense success of deep neural network in image processing and object recognition, learning-based image super resolution (SR) methods have been highly valued and have become the mainstream direction of super resolution research.
R. Li, W. Liu, W. Gong, X. Zhu, X. Wang
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Super-resolution microscopy based on interpolation and wide spectrum de-noising
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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Cross-View Attention Interaction Fusion Algorithm for Stereo Super-Resolution
In the process of stereo super-resolution reconstruction, in addition to the richness of the extracted feature information directly affecting the texture details of the reconstructed image, the texture details of the corresponding pixels between stereo ...
Yaru Zhang +3 more
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Skip-Concatenated Image Super-Resolution Network for Mobile Devices
Single-image super-resolution technology has been widely studied in various applications to improve the quality and resolution of degraded images acquired from noise-sensitive low-resolution sensors.
Ganzorig Gankhuyag +8 more
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Single Image Super Resolution via Multi-Attention Fusion Recurrent Network
Deep convolutional neural networks have significantly enhanced the performance of single image super-resolution in recent years. However, the majority of the proposed networks are single-channel, making it challenging to fully exploit the advantages of ...
Qiqi Kou +5 more
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