A review of remote sensing image fusion methods
H Ghassemian - Information Fusion, 2016 - Elsevier
The recent years have been marked by continuous improvements of remote sensors with
applications like monitoring and management of the environment, precision agriculture …
applications like monitoring and management of the environment, precision agriculture …
[HTML][HTML] Super-resolution: a comprehensive survey
K Nasrollahi, TB Moeslund - Machine vision and applications, 2014 - Springer
Super-resolution, the process of obtaining one or more high-resolution images from one or
more low-resolution observations, has been a very attractive research topic over the last two …
more low-resolution observations, has been a very attractive research topic over the last two …
[HTML][HTML] A systematic review and meta-analysis of Digital elevation model (DEM) fusion: Pre-processing, methods and applications
The remote sensing community has identified data fusion as one of the key challenging
topics of the 21st century. The subject of image fusion in two-dimensional (2D) space has …
topics of the 21st century. The subject of image fusion in two-dimensional (2D) space has …
[HTML][HTML] Diffusion model with detail complement for super-resolution of remote sensing
Remote sensing super-resolution (RSSR) aims to improve remote sensing (RS) image
resolution while providing finer spatial details, which is of great significance for high-quality …
resolution while providing finer spatial details, which is of great significance for high-quality …
Adjustable model-based fusion method for multispectral and panchromatic images
In this paper, an adjustable model-based image fusion method for multispectral (MS) and
panchromatic (PAN) images is developed. The relationships of the desired high spatial …
panchromatic (PAN) images is developed. The relationships of the desired high spatial …
Improved SRGAN for remote sensing image super-resolution across locations and sensors
Detailed and accurate information on the spatial variation of land cover and land use is a
critical component of local ecology and environmental research. For these tasks, high spatial …
critical component of local ecology and environmental research. For these tasks, high spatial …
Alternatively constrained dictionary learning for image superresolution
Dictionaries are crucial in sparse coding-based algorithm for image superresolution. Sparse
coding is a typical unsupervised learning method to study the relationship between the …
coding is a typical unsupervised learning method to study the relationship between the …
Super-Resolution Based on Fast Registration and Maximum a Posteriori Reconstruction
GK Chantas, NP Galatsanos… - IEEE Transactions on …, 2007 - ieeexplore.ieee.org
In this paper, we propose a maximum a posteriori framework for the super-resolution
problem, ie, reconstructing high-resolution images from shifted, rotated, low-resolution …
problem, ie, reconstructing high-resolution images from shifted, rotated, low-resolution …
Space-time super-resolution using graph-cut optimization
U Mudenagudi, S Banerjee… - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
We address the problem of super-resolution-obtaining high-resolution images and videos
from multiple low-resolution inputs. The increased resolution can be in spatial or temporal …
from multiple low-resolution inputs. The increased resolution can be in spatial or temporal …
Single‐frame image super‐resolution using learned wavelet coefficients
We propose a single‐frame, learning‐based super‐resolution restoration technique by
using the wavelet domain to define a constraint on the solution. Wavelet coefficients at finer …
using the wavelet domain to define a constraint on the solution. Wavelet coefficients at finer …