Results 11 to 20 of about 2,065,913 (297)
Super-Resolution Blind Channel Modeling [PDF]
2011 IEEE International Conference on Communications (ICC), 2011 In this work, we propose a super-resolution blind channel modeling algorithm to characterize wide-band channels comprised of disjoint frequency subbands. Since sounding signals are not available over the frequency guard bands separating adjacent subbands, conventional channel modeling methods suffer from poor performance in modeling the channel ...
Man-On Pun +3 more
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Deep Learning-Based Single-Image Super-Resolution: A Comprehensive Review
IEEE Access, 2023 High-fidelity information, such as 4K quality videos and photographs, is increasing as high-speed internet access becomes more widespread and less expensive.
Karansingh Chauhan +7 more
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Deep Blind Video Super-resolution
CoRR, 2020 Existing video super-resolution (SR) algorithms usually assume that the blur kernels in the degradation process are known and do not model the blur kernels in the restoration. However, this assumption does not hold for video SR and usually leads to over-smoothed super-resolved images.
Jinshan Pan +3 more
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Deep Blind Super-Resolution for Satellite Video
IEEE Transactions on Geoscience and Remote Sensing, 2023 Recent efforts have witnessed remarkable progress in Satellite Video Super-Resolution (SVSR). However, most SVSR methods usually assume the degradation is fixed and known, e.g., bicubic downsampling, which makes them vulnerable in real-world scenes with multiple and unknown degradations.
Yi Xiao 0003 +3 more
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Medical image blind super‐resolution based on improved degradation process
IET Image Processing, 2023 Clinical diagnosis has high requirements for the resolution of medical images, but most existing medical images super‐ resolution (SR) methods are performed under a known or specific degradation kernel.
Dangguo Shao +4 more
doaj +1 more source
AI, 2023 Despite several solutions and experiments have been conducted recently addressing image super-resolution (SR), boosted by deep learning (DL), they do not usually design evaluations with high scaling factors.
Valdivino Alexandre de Santiago Júnior
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Mathematical theory of blind super-resolution: multidimensional cases [PDF]
, 2021 Super-resolution is a fundamental problem in signal processing that concerns with extracting fine-scale data from low-resolution information. In this thesis, we focus on developing atomic norm-based algorithms for blind super-resolution. Due to the extra
Suliman, Mohamed Abdalla Elhag
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Multi-Frame Blind Super-Resolution Based on Joint Motion Estimation and Blur Kernel Estimation
Applied Sciences, 2022 Multi-frame super-resolution makes up for the deficiency of sensor hardware and significantly improves image resolution by using the information of inter-frame and intra-frame images.
Shanshan Liu +2 more
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Spatiotemporal super-resolution for low bitrate H.264 video [PDF]
, 2010 Super-resolution and frame interpolation enhance low resolution low-framerate videos. Such techniques are especially important for limited bandwidth communications. This paper proposes a novel technique to up-scale videos compressed with H.264 at low bit-
Anantrasirichai, N +3 more
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Super-Resolution Microscopy: A Virus’ Eye View of the Cell [PDF]
, 2014 It is difficult to observe the molecular choreography between viruses and host cell components, as they exist on a spatial scale beyond the reach of conventional microscopy.
Grove, J, Grove, Joe, Joe Grove
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