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Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification
Danfeng Hong, Xin Wu, Pedram Ghamisi +3
Up to the present, an enormous number of advanced techniques have been developed to enhance and extract the spatially semantic information in hyperspectral image processing and ana…
Online Structured Sparsity-based Moving Object Detection from Satellite Videos
Junpeng Zhang, Xiuping Jia, Jiankun Hu +1
Inspired by the recent developments in computer vision, low-rank and structured sparse matrix decomposition can be potentially be used for extract moving objects in satellite video…
Learning Shared Cross-modality Representation Using Multispectral-LiDAR and Hyperspectral Data
Danfeng Hong, Jocelyn Chanussot, Naoto Yokoya +2
Due to the ever-growing diversity of the data source, multi-modality feature learning has attracted more and more attention. However, most of these methods are designed by jointly…
An Introduction to Deep Morphological Networks
Keiller Nogueira, Jocelyn Chanussot, Mauro Dalla Mura +1
The recent impressive results of deep learning-based methods on computer vision applications brought fresh air to the research and industrial community. This success is mainly due…
Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection
Xin Wu, Danfeng Hong, Jocelyn Chanussot +3
Geospatial object detection of remote sensing imagery has been attracting an increasing interest in recent years, due to the rapid development in spaceborne imaging. Most of previo…
Spectral Variability Aware Blind Hyperspectral Image Unmixing Based on Convex Geometry
Lucas Drumetz, Jocelyn Chanussot, Christian Jutten +2
Hyperspectral image unmixing has proven to be a useful technique to interpret hyperspectral data, and is a prolific research topic in the community. Most of the approaches used to…
Unsupervised and Unregistered Hyperspectral Image Super-Resolution with Mutual Dirichlet-Net
Ying Qu, Hairong Qi, Chiman Kwan +2
Hyperspectral images (HSI) provide rich spectral information that contributed to the successful performance improvement of numerous computer vision tasks. However, it can only be a…
Spectral Unmixing: A Derivation of the Extended Linear Mixing Model from the Hapke Model
Lucas Drumetz, Jocelyn Chanussot, Christian Jutten
In hyperspectral imaging, spectral unmixing aims at decomposing the image into a set of reference spectral signatures corresponding to the materials present in the observed scene a…
ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features
Xin Wu, Danfeng Hong, Jiaojiao Tian +3
With the rapid development of spaceborne imaging techniques, object detection in optical remote sensing imagery has drawn much attention in recent decades. While many advanced work…
Learnable Manifold Alignment (LeMA) : A Semi-supervised Cross-modality Learning Framework for Land Cover and Land Use Classification
Danfeng Hong, Naoto Yokoya, Nan Ge +2
In this paper, we aim at tackling a general but interesting cross-modality feature learning question in remote sensing community --- can a limited amount of highly-discrimin-ative…