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Recognition and Extraction of High-Resolution Satellite Remote Sensing Image Buildings Based on Deep Learning

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DOI: 10.23977/jipta.2023.060104 | Downloads: 21 | Views: 611


Xuebo Yan 1, Shiwei Chen 1, Gang Lei 2


1 Fujian University of Technology, Fuzhou, Fujian, China
2 Fujian Guotai Construction Co., Ltd, Sanming, Fujian, China

Corresponding Author

Xuebo Yan


As the technology applications continue to emerge and create innovations, building identification and extraction by high-resolution satellite remote sensing image technology has been a challenge for scholars to overcome. And many scholars have achieved some success in this field. Space information is clear, shadows are disorderly and details are not obvious in satellite remote sensing image technology. The current remote sensing processing technology usually can not meet the requirements of high-resolution remote sensing image detail processing. This paper uses an object-oriented analysis technology based on deep learning to solve this problem. It can make full use of some characteristics of the image. Compared with the current remote sensing image processing technology, its most important feature is that it can process the smallest unit, which is composed of some similar attributes, rather than a single pixel. Finally, the identification and extraction of buildings are detected. In this paper, we compare the multi-scale segmentation algorithm and mean shift segmentation algorithm. These two methods can obtain more accurate object outlines derived at high resolution from the remote sensing satellite pictures. Results of experiments show this paper that the proposed method has better effect on the recognition as well as detection and extraction of buildings. The accuracy of recognizing as well as selecting buildings from the high definition remote sensing satellite pictures is 89.7%.


Deep Learning, Image Recognition, High-Resolution Satellite Remote Sensing Images, Target Detection


Xuebo Yan, Shiwei Chen, Gang Lei, Recognition and Extraction of High-Resolution Satellite Remote Sensing Image Buildings Based on Deep Learning. Journal of Image Processing Theory and Applications (2023) Vol. 6: 41-53. DOI:


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