8 papers
Deep Learning Meets Satellite Images -- An Evaluation on Handcrafted and Learning-based Features for Multi-date Satellite Stereo Images
Shuang Song, Luca Morelli, Xinyi Wu +3
A critical step in the digital surface models(DSM) generation is feature matching. Off-track (or multi-date) satellite stereo images, in particular, can challenge the performance o…
Remote Sensing Image Enhancement through Spatiotemporal Filtering
Hessah Albanwan
The analysis of time-sequence satellite images is a powerful tool in remote sensing; it is used to explore the statics and dynamics of the surface of the earth. Usually, the qualit…
Spatial, Temporal, and Geometric Fusion for Remote Sensing Images
Hessah Albanwan
Remote sensing (RS) images are important to monitor and survey earth at varying spatial scales. Continuous observations from various RS sources complement single observations to im…
Image Fusion in Remote Sensing: An Overview and Meta Analysis
Hessah Albanwan, Rongjun Qin, Yang Tang
Image fusion in Remote Sensing (RS) has been a consistent demand due to its ability to turn raw images of different resolutions, sources, and modalities into accurate, complete, an…
A Comparative Study on Deep-Learning Methods for Dense Image Matching of Multi-angle and Multi-date Remote Sensing Stereo Images
Hessah Albanwan, Rongjun Qin
Deep learning (DL) stereo matching methods gained great attention in remote sensing satellite datasets. However, most of these existing studies conclude assessments based only on a…
A Review of Mobile Mapping Systems: From Sensors to Applications
Mostafa Elhashash, Hessah Albanwan, Rongjun Qin
The evolution of mobile mapping systems (MMSs) has gained more attention in the past few decades. MMSs have been widely used to provide valuable assets in different applications. T…
Spatiotemporal Fusion in Remote Sensing
Hessah Albanwan, Rongjun Qin
Remote sensing images and techniques are powerful tools to investigate earth surface. Data quality is the key to enhance remote sensing applications and obtaining a clear and noise…
3D Iterative Spatiotemporal Filtering for Classification of Multitemporal Satellite Data Sets
Hessah Albanwan, Rongjun Qin, Xiaohu Lu +3
The current practice in land cover/land use change analysis relies heavily on the individually classified maps of the multitemporal data set. Due to varying acquisition conditions…