Year: 2021
Type: conference-paper
Abstract: In recent years, there are many researches on calculating the height of buildings by extracting the shadow of buildings, but this method is difficult to be realized in the case of dense buildings or complex ground. To solve this problem, we can use the side information of the building to retrieve the height of the building. In this paper, Otsu Algorithm and LVQ neural network are used to extract the side information of buildings from high-resolution remote sensing images, calculate its length, and then calculate the height of the building according to the physical model of imaging. Compared with the measured building height, the calculation results of this method can meet the accuracy requirements of building height calculation, and this method can complement the results of shadow extraction method. Finally, the height information of most buildings in the area can be obtained.
Authors: Hao Tang, Linlin Du, Chun Wang, Pengfei Li, Shuangquan Ge, Dezhuang Meng
Institution: China Academy of Engineering Physics
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3179736637