Review of the pansharpening methods for remote sensing images based on the idea of meta-analysis: Practical discussion and challenges
In this paper, the development of pansharpening methods from traditional understanding to
the current understanding is comprehensively reviewed. Furthermore, the performance of …
the current understanding is comprehensively reviewed. Furthermore, the performance of …
A survey on region based image fusion methods
Image fusion has been emerging as an important area of research. It has attracted many
applications such as surveillance, photography, medical diagnosis, etc. Image fusion …
applications such as surveillance, photography, medical diagnosis, etc. Image fusion …
Multi-fusion algorithms for detecting land surface pattern changes using multi-high spatial resolution images and remote sensing analysis
Abstract Producing accurate Land-Use and Land-Cover (LU/LC) maps using low-spatial-
resolution images is a difficult task. Pan-sharpening is crucial for estimating LU/LC patterns …
resolution images is a difficult task. Pan-sharpening is crucial for estimating LU/LC patterns …
An integrated framework for the spatio–temporal–spectral fusion of remote sensing images
Remote sensing satellite sensors feature a tradeoff between the spatial, temporal, and
spectral resolutions. In this paper, we propose an integrated framework for the spatio …
spectral resolutions. In this paper, we propose an integrated framework for the spatio …
HD-Net: High-resolution decoupled network for building footprint extraction via deeply supervised body and boundary decomposition
The extraction of building footprints, as a highly challenging task in remote sensing (RS)
image-based geospatial object detection and recognition, holds significant importance. Due …
image-based geospatial object detection and recognition, holds significant importance. Due …
The fusion of panchromatic and multispectral remote sensing images via tensor-based sparse modeling and hyper-Laplacian prior
In this paper, we propose a tensor-based non-convex sparse modeling approach for the
fusion of panchromatic and multispectral remote sensing images, and this kind of fusion is …
fusion of panchromatic and multispectral remote sensing images, and this kind of fusion is …
Spatial–spectral fusion by combining deep learning and variational model
In the field of spatial–spectral fusion, the variational model-based methods and the deep
learning (DL)-based methods are state-of-the-art approaches. This paper presents a fusion …
learning (DL)-based methods are state-of-the-art approaches. This paper presents a fusion …
Pansharpening for cloud-contaminated very high-resolution remote sensing images
The optical remote sensing images not only have to make a fundamental tradeoff between
the spatial and spectral resolutions, but also are inevitable to be polluted by the clouds; …
the spatial and spectral resolutions, but also are inevitable to be polluted by the clouds; …
Multispectral and SAR image fusion based on Laplacian pyramid and sparse representation
Complementary information from multi-sensors can be combined to improve the availability
and reliability of stand-alone data. Typically, multispectral (MS) images contain plentiful …
and reliability of stand-alone data. Typically, multispectral (MS) images contain plentiful …
Application of fractional-order differentiation in multispectral image fusion
A Azarang, H Ghassemian - Remote sensing letters, 2018 - Taylor & Francis
In this letter, a novel pansharpening method is proposed using component substitution (CS)
framework. In order to inject the spatial details into the low resolution multispectral (MS) …
framework. In order to inject the spatial details into the low resolution multispectral (MS) …