Results 31 to 40 of about 750,933 (209)
Remote Sensing, 2022 At present, with the advance of satellite image processing technology, remote sensing images are becoming more widely used in real scenes. However, due to the limitations of current remote sensing imaging technology and the influence of the external ...
Xuan Wang +9 more
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Super-Resolution Imaging with Graphene [PDF]
Biosensors, 2021 Super-resolution optical imaging is a consistent research hotspot for promoting studies in nanotechnology and biotechnology due to its capability of overcoming the diffraction limit, which is an intrinsic obstacle in pursuing higher resolution for conventional microscopy techniques. In the past few decades, a great number of techniques in this research
Xiaoxiao Jiang +6 more
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Super-resolution reconstruction of rock CT images based on Real-ESRGAN
Gong-kuang zidonghua, 2023 Due to factors such as image acquisition equipment and geological environment, rock CT images have low resolution and unclear details. However, existing image super-resolution reconstruction methods are prone to losing details when characterizing high ...
LI Gang +6 more
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Accurate Image Super-Resolution Using Very Deep Convolutional Networks [PDF]
Computer Vision and Pattern Recognition, 2015 We present a highly accurate single-image superresolution (SR) method. Our method uses a very deep convolutional network inspired by VGG-net used for ImageNet classification [19].
Jiwon Kim, Jung Kwon Lee, Kyoung Mu Lee
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SinSR: Diffusion-Based Image Super-Resolution in a Single Step [PDF]
Computer Vision and Pattern Recognition, 2023 While super-resolution (SR) methods based on diffusion models exhibit promising results, their practical application is hindered by the substantial number of required inference steps.
Yufei Wang +9 more
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Review and Prospect of Image Super-Resolution Technology
Jisuanji kexue yu tansuo, 2020 Image super-resolution (SR) is an important type of image processing technology for improving image and video resolution in computer vision. In recent years, thanks to the success of neural networks, image super-resolution technology based on deep ...
LIU Ying, ZHU Li, LIM Kengpang, LI Yinghua, WANG Fuping, LU Jin
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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
Wenzhe Shi +7 more
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Xi'an Gongcheng Daxue xuebao, 2022 In order to solve the problem of poor consistency between the traditional super-resolution image quality assessment (SRIQA) index and human subjective perception, this paper presents a reference free super-resolution image quality evaluation method by ...
ZHU Danni +4 more
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Guided Cascaded Super-Resolution Network for Face Image
IEEE Access, 2020 The image super-resolution algorithm can overcome the imaging system's hardware limitation and obtain higher resolution and clearer images. Existing super-resolution methods based on convolutional neural networks(CNN) can learn the mapping relationship ...
Lin Cao +4 more
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SUPER RESOLUTION FOR SINGLE SATELLITE IMAGE USING A GENERATIVE ADVERSARIAL NETWORK [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 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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