Results 41 to 50 of about 390,825 (273)
Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network [PDF]
, 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
Aitken, AP +7 more
core +1 more source
Deep Back-ProjectiNetworks for Single Image Super-Resolution [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 Previous feed-forward architectures of recently proposed deep super-resolution networks learn the features of low-resolution inputs and the non-linear mapping from those to a high-resolution output. However, this approach does not fully address the mutual dependencies of low- and high-resolution images.
Muhammad Haris 0002 +2 more
openaire +3 more sources
IEEE Access, 2021 In this paper, we propose an independent neural network for single image super-resolution by residual recovery. The network is inspired by the observation that there still exists image residuals between the low-resolution image and the downsampled high ...
Fei Wang, Mali Gong
doaj +1 more source
Super-resolution reconstruction for a single image based on self-similarity and compressed sensing
Journal of Algorithms & Computational Technology, 2018 Super-resolution image reconstruction can achieve favorable feature extraction and image analysis. This study first investigated the image’s self-similarity and constructed high-resolution and low-resolution learning dictionaries; then, based on sparse ...
Qiang Yang, Huajun Wang
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Super-resolution reconstruction of brain magnetic resonance images via lightweight autoencoder
Informatics in Medicine Unlocked, 2021 Magnetic Resonance Imaging (MRI) is useful to provide detailed anatomical information such as images of tissues and organs within the body that are vital for quantitative image analysis. However, typically the MR images acquired lacks adequate resolution
J. Andrew +6 more
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Multi-Image Super Resolution of Remotely Sensed Images Using Residual Attention Deep Neural Networks
Remote Sensing, 2020 Convolutional Neural Networks (CNNs) consistently proved state-of-the-art results in image Super-resolution (SR), representing an exceptional opportunity for the remote sensing field to extract further information and knowledge from captured data ...
Francesco Salvetti +3 more
doaj +1 more source
4× Super‐resolution of unsupervised CT images based on GAN
IET Image Processing, 2023 Improving the resolution of computed tomography (CT) medical images can help doctors more accurately identify lesions, which is important in clinical diagnosis.
Yunhe Li +3 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
Neighborhood Issue in Single-Frame Image Super-Resolution [PDF]
2005 IEEE International Conference on Multimedia and Expo, 2005 Super-resolution is the problem of generating one or a set of high-resolution images from one or a sequence of low-resolution frames. Most methods have been proposed for super-resolution based on multiple low resolution images of the same scene, which is called multiple-frame super-resolution.
Xu (Kevin) Su +4 more
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SENext: Squeeze-and-ExcitationNext for Single Image Super-Resolution
IEEE Access, 2022 Recent research on image and video processing using convolutional neural networks has shown remarkable improvements, especially in the area of single image super-resolution(SISR). The primary target of SISR is to recover the visually appealing high-resolution (HR) output image from the original degraded low-resolution (LR) input image.
Wazir Muhammad +2 more
openaire +2 more sources