Cell segmentation in imaging-based spatial transcriptomics
Single-molecule spatial transcriptomics protocols based on in situ sequencing or
multiplexed RNA fluorescent hybridization can reveal detailed tissue organization. However …
multiplexed RNA fluorescent hybridization can reveal detailed tissue organization. However …
Variational Bayesian super resolution
SD Babacan, R Molina… - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
In this paper, we address the super resolution (SR) problem from a set of degraded low
resolution (LR) images to obtain a high resolution (HR) image. Accurate estimation of the …
resolution (LR) images to obtain a high resolution (HR) image. Accurate estimation of the …
Multiframe super-resolution employing a spatially weighted total variation model
Total variation (TV) has been used as a popular and effective image prior model in
regularization-based image processing fields, such as denoising, deblurring, super …
regularization-based image processing fields, such as denoising, deblurring, super …
Super-resolution mapping of wetland inundation from remote sensing imagery based on integration of back-propagation neural network and genetic algorithm
Mapping the spatio-temporal characteristics of wetland inundation has an important
significance to the study of wetland environment and associated flora and fauna. High …
significance to the study of wetland environment and associated flora and fauna. High …
Bayesian combination of sparse and non-sparse priors in image super resolution
In this paper the application of image prior combinations to the Bayesian Super Resolution
(SR) image registration and reconstruction problem is studied. Two sparse image priors, a …
(SR) image registration and reconstruction problem is studied. Two sparse image priors, a …
An adaptive subpixel mapping method based on MAP model and class determination strategy for hyperspectral remote sensing imagery
The subpixel mapping technique can specify the spatial distribution of different categories at
the subpixel scale by converting the abundance map into a higher resolution image, based …
the subpixel scale by converting the abundance map into a higher resolution image, based …
Sub-pixel flood inundation mapping from multispectral remotely sensed images based on discrete particle swarm optimization
The study of flood inundation is significant to human life and social economy. Remote
sensing technology has provided an effective way to study the spatial and temporal …
sensing technology has provided an effective way to study the spatial and temporal …
Generative and discriminative model-based approaches to microscopic image restoration and segmentation
Image processing is one of the most important applications of recent machine learning (ML)
technologies. Convolutional neural networks (CNNs), a popular deep learning-based ML …
technologies. Convolutional neural networks (CNNs), a popular deep learning-based ML …
Sub-pixel mapping based on a MAP model with multiple shifted hyperspectral imagery
Sub-pixel mapping is technique used to obtain the spatial distribution of different classes at
the sub-pixel scale by transforming fraction images to a classification map with a higher …
the sub-pixel scale by transforming fraction images to a classification map with a higher …
Spatial superresolution based on simultaneous dual PIV measurement with different magnification
Y Ozawa, H Honda, T Nonomura - Experiments in Fluids, 2024 - Springer
A reconstruction framework based on proper orthogonal decomposition and the Bayesian
estimation was designed for the spatial superresolution of a subsonic jet, and the …
estimation was designed for the spatial superresolution of a subsonic jet, and the …