Results 31 to 40 of about 137,048 (270)
A super- resolution feasibility study in small-animal SPECT imaging [PDF]
, 2008 Proceeding of: 2008 IEEE Nuclear Science Symposium Conference Record (NSS '08), Dresden, Germany, 19-25 Oct. 2008Lack of spatial resolution is a major drawback in small-animal SPECT imaging, particularly when parallel hole collimators are employed.
Carlos, Álvaro de +6 more
core +2 more sources
Joint Blind Super-Resolution and Shadow Removing
IEICE Transactions on Information and Systems, 2007 Most learning-based super-resolution methods neglect the illumination problem. In this paper we propose a novel method to combine blind single-frame super-resolution and shadow removal into a single operation. Firstly, from the pattern recognition viewpoint, blur identification is considered as a classification problem.
Jianping Qiao, Ju Liu, Yen-Wei Chen
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
X-ray image separation via coupled dictionary learning [PDF]
, 2016 In support of art investigation, we propose a new source sepa- ration method that unmixes a single X-ray scan acquired from double-sided paintings. Unlike prior source separation meth- ods, which are based on statistical or structural incoherence of the ...
Cornelis, Bruno +4 more
core +2 more sources
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
Boosting Degradation Representation Learning for Blind Image Super-Resolution [PDF]
Jisuanji kexue yu tansuoIn most convolutional neural networks-based super-resolution (SR) methods, the degradation assumptions are fixed and known (e.g., bicubic degradation). When applying them to real-world degraded images, the mismatch between the actual degradation and the ...
YUAN Jiang, MA Ji, ZHOU Dengwen
doaj +1 more source
Multiple Frame Splicing and Degradation Learning for Hyperspectral Imagery Super-Resolution
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral imagery (HSI) is an emerging remote sensing technology to discriminate different remote sensing objects. However, the HSI spatial resolution is relatively low due to the trade-off in restricted physical hardware and various imaging ...
Chenwei Deng, Xingshi Luo, Wenzheng Wang
doaj +1 more source
Gradient Scan Gibbs Sampler: an efficient algorithm for high-dimensional Gaussian distributions
, 2015 This paper deals with Gibbs samplers that include high dimensional conditional Gaussian distributions. It proposes an efficient algorithm that avoids the high dimensional Gaussian sampling and relies on a random excursion along a small set of directions.
Féron, Olivier +2 more
core +3 more sources
Robust Statistics for Image Deconvolution
, 2017 We present a blind multiframe image-deconvolution method based on robust statistics. The usual shortcomings of iterative optimization of the likelihood function are alleviated by minimizing the M-scale of the residuals, which achieves more uniform ...
Budavari, Tamas +3 more
core +1 more source