Results 41 to 50 of about 216,992 (320)
IET Image Processing, 2021 The current super‐resolution (SR) deep network is mainly applied to the common image and pays little attention to the image with noise. The remote sensing image contains much noise, so that the SR reconstruction effect is not satisfactory.
Xin Yang +3 more
doaj +1 more source
Blind fluorescence structured illumination microscopy: A new reconstruction strategy [PDF]
, 2016 In this communication, a fast reconstruction algorithm is proposed for fluorescence \textit{blind} structured illumination microscopy (SIM) under the sample positivity constraint.
Allain, M. +6 more
core +4 more sources
Unsupervised Blur Kernel Estimation and Correction for Blind Super-Resolution
IEEE Access, 2022 Blind super-resolution (blind-SR) is an important task in the field of computer vision and has various applications in real-world. Blur kernel estimation is the main element of blind-SR along with the adaptive SR networks and a more accurately estimated ...
Youngsoo Kim +3 more
doaj +1 more source
Blind-Depth Light Field Super-Resolution
Journal of Physics: Conference Series, 2020 Abstract Light field cameras have drawn much attention due to the ability of post-capture adjustments such as refocusing and 3D reconstruction. However, the low resolution has been the bottleneck of them and limits their further application.
Lei Zhang, Jianpeng Fan, Jungang Yang
openaire +1 more source
Blind Fusion of Hyperspectral Multispectral Images Based on Matrix Factorization
Remote Sensing, 2021 The fusion of low spatial resolution hyperspectral images and high spatial resolution multispectral images in the same scenario is important for the super-resolution of hyperspectral images.
Jian Long, Yuanxi Peng
doaj +1 more source
Structured illumination microscopy with unknown patterns and a statistical prior [PDF]
, 2017 Structured illumination microscopy (SIM) improves resolution by down-modulating high-frequency information of an object to fit within the passband of the optical system.
Tian, Lei, Waller, Laura, Yeh, Li-Hao
core +2 more sources
Computational structured illumination for high-content fluorescent and phase microscopy [PDF]
, 2019 High-content biological microscopy targets high-resolution imaging across large fields-of-view (FOVs). Recent works have demonstrated that computational imaging can provide efficient solutions for high-content microscopy.
Chowdhury, Shwetadwip +2 more
core +2 more sources
Blind Super-Resolution via Meta-Learning and Markov Chain Monte Carlo Simulation [PDF]
IEEE Transactions on Pattern Analysis and Machine IntelligenceLearning based approaches have witnessed great successes in blind single image super-resolution (SISR) tasks, however, handcrafted kernel priors and learning based kernel priors are typically required. In this paper, we propose a meta-learning and Markov
Jingyuan Xia +6 more
semanticscholar +1 more source
Self-FuseNet: Data Free Unsupervised Remote Sensing Image Super-Resolution
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Real-world degradations deviate from ideal degradations, as most deep learning-based scenarios involve the ideal synthesis of low-resolution (LR) counterpart images by popularly used bicubic interpolation. Moreover, supervised learning approaches rely on
Divya Mishra, Ofer Hadar
doaj +1 more source
Neutrino hierarchy from CP-blind observables with high density magnetized detectors [PDF]
, 2007 High density magnetized detectors are well suited to exploit the outstanding purity and intensities of novel neutrino sources like Neutrino Factories and Beta Beams. They can also provide independent measurements of leptonic mixing parameters through the
A. Cervera +60 more
core +2 more sources