3.2k citations · 10k across the 87 of their papers we have counts for
25 papers · 1 filter
CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences
Danfeng Hong, Naoto Yokoya, Jocelyn Chanussot +1
With a large amount of open satellite multispectral imagery (e.g., Sentinel-2 and Landsat-8), considerable attention has been paid to global multispectral land cover classification…
Non-Local Compressive Sensing Based SAR Tomography
Yilei Shi, Xiao Xiang Zhu, Richard Bamler
Tomographic SAR (TomoSAR) inversion of urban areas is an inherently sparse reconstruction problem and, hence, can be solved using compressive sensing (CS) algorithms. This paper pr…
An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing
Danfeng Hong, Naoto Yokoya, Jocelyn Chanussot +1
Hyperspectral imagery collected from airborne or satellite sources inevitably suffers from spectral variability, making it difficult for spectral unmixing to accurately estimate ab…
Fusion of TanDEM-X and Cartosat-1 Elevation Data Supported by NeuralNetwork-Predicted Weight Maps
Hossein Bagheri, Michael Schmitt, Xiao Xiang Zhu
Recently, the bistatic SAR interferometry mission TanDEM-X provided a global terrain map with unprecedented accuracy. However, visual inspection and empirical assessment of TanDEM-…
A Framework for SAR-Optical Stereogrammetry over Urban Areas
Hossein Bagheri, Michael Schmitt, Pablo d'Angelo +1
Currently, numerous remote sensing satellites provide a huge volume of diverse earth observation data. As these data show different features regarding resolution, accuracy, coverag…
Fusion of Urban TanDEM-X raw DEMs using variational models
Hossein Bagheri, Michael Schmitt, Xiao Xiang Zhu
Recently, a new global Digital Elevation Model (DEM) with pixel spacing of 0.4 arcseconds and relative height accuracy finer than 2m for flat areas (slopes < 20%) and better than 4…
Building Footprint Generation Using Improved Generative Adversarial Networks
Yilei Shi, Qingyu Li, Xiao Xiang Zhu
Building footprint information is an essential ingredient for 3-D reconstruction of urban models. The automatic generation of building footprints from satellite images presents a c…
R-Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos
Qingpeng Li, Lichao Mou, Qizhi Xu +2
Vehicle detection is a significant and challenging task in aerial remote sensing applications. Most existing methods detect vehicles with regular rectangle boxes and fail to offer…
Buildings Detection in VHR SAR Images Using Fully Convolution Neural Networks
Muhammad Shahzad, Michael Maurer, Friedrich Fraundorfer +2
This paper addresses the highly challenging problem of automatically detecting man-made structures especially buildings in very high resolution (VHR) synthetic aperture radar (SAR)…
Spaceborne Staring Spotlight SAR Tomography - A First Demonstration with TerraSAR-X
Nan Ge, Fernando Rodriguez Gonzalez, Yuanyuan Wang +2
With the objective of exploiting hardware capabilities and preparing the ground for the next-generation X-band synthetic aperture radar (SAR) missions, TerraSAR-X and TanDEM-X are…
The SEN1-2 Dataset for Deep Learning in SAR-Optical Data Fusion
Michael Schmitt, Lloyd Haydn Hughes, Xiao Xiang Zhu
While deep learning techniques have an increasing impact on many technical fields, gathering sufficient amounts of training data is a challenging problem in remote sensing. In part…
Recurrently Exploring Class-wise Attention in A Hybrid Convolutional and Bidirectional LSTM Network for Multi-label Aerial Image Classification
Yuansheng Hua, Lichao Mou, Xiao Xiang Zhu
Aerial image classification is of great significance in remote sensing community, and many researches have been conducted over the past few years. Among these studies, most of them…
A Nonlocal InSAR Filter for High-Resolution DEM Generation from TanDEM-X Interferograms
Gerald Baier, Cristian Rossi, Marie Lachaise +2
This paper presents a nonlocal InSAR filter with the goal of generating digital elevation models of higher resolution and accuracy from bistatic TanDEM-X strip map interferograms t…
Vehicle Instance Segmentation from Aerial Image and Video Using a Multi-Task Learning Residual Fully Convolutional Network
Lichao Mou, Xiao Xiang Zhu
Object detection and semantic segmentation are two main themes in object retrieval from high-resolution remote sensing images, which have recently achieved remarkable performance b…
RiFCN: Recurrent Network in Fully Convolutional Network for Semantic Segmentation of High Resolution Remote Sensing Images
Lichao Mou, Xiao Xiang Zhu
Semantic segmentation in high resolution remote sensing images is a fundamental and challenging task. Convolutional neural networks (CNNs), such as fully convolutional network (FCN…
A fast and accurate basis pursuit denoising algorithm with application to super-resolving tomographic SAR
Yilei Shi, Xiao Xiang Zhu, Wotao Yin +1
regularization is used for finding sparse solutions to an underdetermined linear system. As sparse signals are widely expected in remote sensing, this type of regularization…
Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery
Lichao Mou, Lorenzo Bruzzone, Xiao Xiang Zhu
Change detection is one of the central problems in earth observation and was extensively investigated over recent decades. In this paper, we propose a novel recurrent convolutional…
IM2HEIGHT: Height Estimation from Single Monocular Imagery via Fully Residual Convolutional-Deconvolutional Network
Lichao Mou, Xiao Xiang Zhu
In this paper we tackle a very novel problem, namely height estimation from a single monocular remote sensing image, which is inherently ambiguous, and a technically ill-posed prob…
Towards Automatic SAR-Optical Stereogrammetry over Urban Areas using Very High Resolution Imagery
Chunping Qiu, Michael Schmitt, Xiao Xiang Zhu
In this paper we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do th…
Building Instance Classification Using Street View Images
Jian Kang, Marco Körner, Yuanyuan Wang +2
Land-use classification based on spaceborne or aerial remote sensing images has been extensively studied over the past decades. Such classification is usually a patch-wise or pixel…
Non-local tensor completion for multitemporal remotely sensed images inpainting
Teng-Yu Ji, Naoto Yokoya, Xiao Xiang Zhu +1
Remotely sensed images may contain some missing areas because of poor weather conditions and sensor failure. Information of those areas may play an important role in the interpreta…
Identifying Corresponding Patches in SAR and Optical Images with a Pseudo-Siamese CNN
Lloyd H. Hughes, Michael Schmitt, Lichao Mou +2
In this letter, we propose a pseudo-siamese convolutional neural network (CNN) architecture that enables to solve the task of identifying corresponding patches in very-high-resolut…
Automatic Detection and Positioning of Ground Control Points Using TerraSAR-X Multi-Aspect Acquisitions
Sina Montazeri, Christoph Gisinger, Michael Eineder +1
Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GC…
The SARptical Dataset for Joint Analysis of SAR and Optical Image in Dense Urban Area
Yuanyuan Wang, Xiao Xiang Zhu
The joint interpretation of very high resolution SAR and optical images in dense urban area are not trivial due to the distinct imaging geometry of the two types of images. Especia…