The method for extracting rural residential areas from remote sensing images based on improved YOLOv8

Jie Rui; Meilin Li; Fei Jin; Yuzhun Lin; Shuxiang Wang; Xibing Zuo; Aimei Huo

doi:10.1117/12.3017343

15 December 2023 The method for extracting rural residential areas from remote sensing images based on improved YOLOv8

Jie Rui, Meilin Li, Fei Jin, Yuzhun Lin, Shuxiang Wang, Xibing Zuo, Aimei Huo

Author Affiliations +

Proceedings Volume 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023); 129710Q (2023) https://doi.org/10.1117/12.3017343
Event: Third International Conference on Optics and Communication Technology (ICOCT 2023), 2023, Changchun, China

Abstract

Rapid, accurate extraction of rural residential areas is of great significance to rural planning and urbanization. On the basis of the improved YOLOv8 object detection algorithm, this paper puts forward a technical method for accurately extracting rural residential areas from multi-scale remote sensing images. The rapid extraction of rural blocks comes true via improving the retrieval mechanism of YOLOv8 algorithm: First, the feature extraction module based on ECA local crosschannel interaction attention mechanism is designed to deeply dig the detailed features with inconsistent scales in the detection of residential areas. Efficient channel interaction pays more attention to the positive sample feature information in the feature map, and meanwhile, it reduces the complexity of the model. Second, Swish activation function is proposed to avoid gradient disappearance and poor activation effect caused by over-fitting. Third, DIoU loss is introduced to accurately show the real distance error between two predicted residential areas and enhance the performance of multitarget detection. In the end, ablation experiments and comparative experiments are conducted on CBDV1.0 building data set. The experimental results show that this method can extract rural residential areas from multi-scale remote sensing images, which provides support for large-scale remote sensing image mapping of rural residential areas.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jie Rui, Meilin Li, Fei Jin, Yuzhun Lin, Shuxiang Wang, Xibing Zuo, and Aimei Huo "The method for extracting rural residential areas from remote sensing images based on improved YOLOv8", Proc. SPIE 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023), 129710Q (15 December 2023); https://doi.org/10.1117/12.3017343

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KEYWORDS

Feature extraction

Remote sensing

Object detection

Detection and tracking algorithms

Education and training

Ablation

Convolution

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