Results 21 to 30 of about 389,857 (275)
Super-resolution fluorescence imaging with single molecules [PDF]
Current Opinion in Structural Biology, 2013 The ability to detect, image and localize single molecules optically with high spatial precision by their fluorescence enables an emergent class of super-resolution microscopy methods which have overcome the longstanding diffraction barrier for far-field light-focusing optics.
Steffen J, Sahl, W E, Moerner
openaire +2 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.
K. Su +4 more
openaire +2 more sources
Super-resolution image transfer by a vortex-like metamaterial [PDF]
, 2013 We propose a vortex-like metamaterial device that is capable of transferring image along a spiral route without losing subwavelength information of the image. The super-resolution image can be guided and magnified at the same time with one single design.
Cui, Tie Jun +3 more
core +2 more sources
Deep Super-Resolution Network for Single Image Super-Resolution with Realistic Degradations [PDF]
Proceedings of the 13th International Conference on Distributed Smart Cameras, 2019 Single Image Super-Resolution (SISR) aims to generate a high-resolution (HR) image of a given low-resolution (LR) image. The most of existing convolutional neural network (CNN) based SISR methods usually take an assumption that a LR image is only bicubicly down-sampled version of an HR image. However, the true degradation (i.e.
UMER, RAO MUHAMMAD +2 more
openaire +2 more sources
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 +3 more sources
Anchored neighborhood deep network for single-image super-resolution
EURASIP Journal on Image and Video Processing, 2018 Real-time image and video processing is a challenging problem in smart surveillance applications. It is necessary to trade off between high frame rate and high resolution to meet the limited bandwidth requirement in many specific applications.
Wuzhen Shi +4 more
doaj +1 more source
Applied Sciences, 2020 The super-resolution generative adversarial network (SRGAN) is a seminal work that is capable of generating realistic textures during single image super-resolution. However, the hallucinated details are often accompanied by unpleasant artifacts.
Zetao Jiang, Yongsong Huang, Lirui Hu
doaj +1 more source
Deep coordinate attention network for single image super‐resolution
IET Image Processing, 2022 Deep learning techniques and deep networks have recently been extensively studied and widely applied to single image super‐resolution (SR). Among them, channel attention has garnered the most focus owing to its significant boost in the presentational ...
Chao Xie, Hongyu Zhu, Yeqi Fei
doaj +1 more source
Analog Image Modeling for 3D Single Image Super Resolution and Pansharpening
Frontiers in Applied Mathematics and Statistics, 2020 Image super-resolution is an image reconstruction technique which attempts to reconstruct a high resolution image from one or more under-sampled low-resolution images of the same scene.
Richard Lartey +3 more
doaj +1 more source
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
doaj +1 more source