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DiffusionSat: A Generative Foundation Model for Satellite Imagery
International Conference on Learning Representations, 2023Diffusion models have achieved state-of-the-art results on many modalities including images, speech, and video. However, existing models are not tailored to support remote sensing data, which is widely used in important applications including ...
Samar Khanna +7 more
semanticscholar +1 more source
Road Extraction From Satellite Imagery by Road Context and Full-Stage Feature
IEEE Geoscience and Remote Sensing Letters, 2023Road extraction from satellite imagery is vital in a broad range of applications. However, extracting complete roads is challenging due to road occlusions caused by the surroundings. This letter proposed an improved encoder–decoder network via extracting
Zhigang Yang +4 more
semanticscholar +1 more source
CoANet: Connectivity Attention Network for Road Extraction From Satellite Imagery
IEEE Transactions on Image Processing, 2021Extracting roads from satellite imagery is a promising approach to update the dynamic changes of road networks efficiently and timely. However, it is challenging due to the occlusions caused by other objects and the complex traffic environment, the pixel-
J. Mei +3 more
semanticscholar +1 more source
A Global Context-aware and Batch-independent Network for road extraction from VHR satellite imagery
, 2021Road extraction is to automatically label the pixels of roads in satellite imagery with specific semantic categories based on the extraction of the topographical meaningful features.
Qiqi Zhu +7 more
semanticscholar +1 more source
IEEE Transactions on Geoscience and Remote Sensing, 2019
The application of the convolutional neural network has shown to greatly improve the accuracy of building extraction from remote sensing imagery.
Shunping Ji, Shiqing Wei, Meng Lu
semanticscholar +1 more source
The application of the convolutional neural network has shown to greatly improve the accuracy of building extraction from remote sensing imagery.
Shunping Ji, Shiqing Wei, Meng Lu
semanticscholar +1 more source
Remote Sensing in Ecology and Conservation, 2021
Coastal wetland biomass is an important indicator of wetland productivity, carbon storage, health, and vulnerability to climate change. The ability to estimate aboveground biomass (AGB) in wetlands at ecologically relevant scales is complicated by the ...
Cheryl L. Doughty +3 more
semanticscholar +1 more source
Coastal wetland biomass is an important indicator of wetland productivity, carbon storage, health, and vulnerability to climate change. The ability to estimate aboveground biomass (AGB) in wetlands at ecologically relevant scales is complicated by the ...
Cheryl L. Doughty +3 more
semanticscholar +1 more source
Unsupervised Denoising for Satellite Imagery Using Wavelet Directional CycleGAN
IEEE Transactions on Geoscience and Remote Sensing, 2021Multispectral satellite imaging sensors acquire various spectral band images and have a unique spectroscopic property in each band. Unfortunately, image artifacts from imaging sensor noise often affect the quality of scenes and have a negative impact on ...
Joonyoung Song +5 more
semanticscholar +1 more source
On the deconvolution of satellite imagery
IEEE International Geoscience and Remote Sensing Symposium, 2003This paper presents an investigation on the deconvolution problem for remotely sensed imagery and compares the results of three different methods. An important element in this image restoration is the knowledge of the point spread function. Therefore various techniques for estimating the system's characteristic are identified and their impact on the ...
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2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018
Road extraction is a fundamental task in the field of remote sensing which has been a hot research topic in the past decade. In this paper, we propose a semantic segmentation neural network, named D-LinkNet, which adopts encoderdecoder structure, dilated
Lichen Zhou, Chuang Zhang, Ming Wu
semanticscholar +1 more source
Road extraction is a fundamental task in the field of remote sensing which has been a hot research topic in the past decade. In this paper, we propose a semantic segmentation neural network, named D-LinkNet, which adopts encoderdecoder structure, dilated
Lichen Zhou, Chuang Zhang, Ming Wu
semanticscholar +1 more source