Results 31 to 40 of about 4,917 (234)
Multispectral Pansharpening Based on Multisequence Convolutional Recurrent Neural Network
Multispectral (MS) pansharpening is defined as the fusion of spatial information in panchromatic (PAN) image and spectral information in MS image. In this work, we propose an MS pansharpening based on multisequence convolutional recurrent neural network (
Peng Wang +5 more
doaj +1 more source
Antarctic Landfast Sea Ice: A Review of Its Physics, Biogeochemistry and Ecology
Abstract Antarctic landfast sea ice (fast ice) is stationary sea ice that is attached to the coast, grounded icebergs, ice shelves, or other protrusions on the continental shelf. Fast ice forms in narrow (generally up to 200 km wide) bands, and ranges in thickness from centimeters to tens of meters. In most regions, it forms in autumn, persists through
A. D. Fraser +22 more
wiley +1 more source
Deep learning in remote sensing: a review [PDF]
Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich +6 more
core +4 more sources
Abstract The Mackenzie River Delta (MRD) has been recognized as an important host of river‐derived wood deposits, and Mackenzie River wood has been found across the Arctic Ocean. Nevertheless, we lack estimates of the amount of carbon stored as wood and its age in the delta, representing a gap in carbon cycle estimates.
Alicia Sendrowski +4 more
wiley +1 more source
Quality assessment by region in spot images fused by means dual-tree complex wavelet transform [PDF]
This work is motivated in providing and evaluating a fusion algorithm of remotely sensed images, i.e. the fusion of a high spatial resolution panchromatic image with a multi-spectral image (also known as pansharpening) using the dual-tree complex wavelet
Arquero Hidalgo, Águeda +2 more
core +2 more sources
The objective of this work is to develop an algorithm for pansharpening of very high resolution (VHR) satellite imagery that reduces the spectral distortion of the pansharpened images and enhances their spatial clarity with minimal computational costs ...
Jaewan Choi +4 more
doaj +1 more source
Content-Adaptive Non-Local Convolution for Remote Sensing Pansharpening [PDF]
Currently, machine learning-based methods for remote sensing pansharpening have progressed rapidly. However, existing pansharpening methods often do not fully exploit differentiating regional information in non-local spaces, thereby limiting the ...
Yule Duan +3 more
semanticscholar +1 more source
QNR Optimization based Pansharpening [PDF]
Quality Without Reference (QNR) index can be used to globally assess the quality of pansharpened images without the need of a reference high resolution multispectral (MS) image. The QNR index relies on local calculation of the Q4 index. Exploiting the local Q4 calculation property of the QNR index, we propose an injection model for pansharpening.
Khan M. M. +2 more
openaire +1 more source
Effects of Pansharpening on Vegetation Indices
This study evaluated the effects of image pansharpening on Vegetation Indices (VIs), and found that pansharpening was able to downscale single-date and multi-temporal Landsat 8 VI data without introducing significant distortions in VI values.
Brian Johnson
doaj +1 more source
PCDRN: Progressive Cascade Deep Residual Network for Pansharpening
Pansharpening is the process of fusing a low-resolution multispectral (LRMS) image with a high-resolution panchromatic (PAN) image. In the process of pansharpening, the LRMS image is often directly upsampled by a scale of 4, which may result in the loss ...
Yong Yang +3 more
doaj +1 more source

