no code implementations • 27 Apr 2024 • Hessah Albanwan
Fusion methods can process different images, modalities, and tasks and are expected to be robust and adaptive to various types of images (e. g., spectral images, classification maps, and elevation maps) and scene complexities.
no code implementations • 27 Apr 2024 • Hessah Albanwan
The newly developed filter proved that it can enhance the accuracy of classification using transfer learning by about 5%, 15%, and 2% for the three experiments respectively.
no code implementations • 16 Jan 2024 • 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, and spatio-temporally coherent images.
no code implementations • 25 Oct 2022 • Hessah Albanwan, Rongjun Qin
All DL algorithms are robust to geometric configurations of stereo pairs and are less sensitive in comparison to the Census-SGM, while learning-based cost metrics can generalize on satellite images when trained on different datasets (airborne or ground-view).
no code implementations • 31 May 2022 • Mostafa Elhashash, Hessah Albanwan, Rongjun Qin
The evolution of mobile mapping systems (MMSs) has gained more attention in the past few decades.
no code implementations • 27 May 2022 • Hessah Albanwan, Rongjun Qin
Knowing that classical stereo matching methods such as Census-based semi-global-matching (SGM) are widely adopted to process different types of stereo data, we therefore, propose a finetuning method that takes advantage of disparity maps derived from SGM on target stereo data.
no code implementations • 6 Jul 2021 • Hessah Albanwan, Rongjun Qin
Remote sensing images and techniques are powerful tools to investigate earth surface.
no code implementations • 1 Jul 2021 • Hessah Albanwan, Rongjun Qin, Xiaohu Lu, Mao Li, Desheng Liu, Jean-Michel Guldmann
The current practice in land cover/land use change analysis relies heavily on the individually classified maps of the multitemporal data set.