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Found 4 papers, 2 papers with code
Super-Resolution-based Snake Model -- An Unsupervised Method for Large-Scale Building Extraction using Airborne LiDAR Data and Optical Image
This paper presents an efficient snake model to overcome such challenge, called Super-Resolution-based Snake Model (SRSM).
Coarse-to-Fine Registration of Airborne LiDAR Data and Optical Imagery on Urban Scenes
Firstly, a coarse registration involves extracting and matching of buildings from LiDAR data and optical imagery.
Unsupervised Automatic Building Extraction Using Active Contour Model on Unregistered Optical Imagery and Airborne LiDAR Data
Automatic extraction of buildings in urban scenes has become a subject of growing interest in the domain of photogrammetry and remote sensing, particularly with the emergence of LiDAR systems since mid-1990s.
Robust Building-based Registration of Airborne LiDAR Data and Optical Imagery on Urban Scenes
The motivation of this paper is to address the problem of registering airborne LiDAR data and optical aerial or satellite imagery acquired from different platforms, at different times, with different points of view and levels of detail.
