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A New Instance Segmentation Model for High-Resolution Remote Sensing Images Based on Edge Processing

Author

Listed:
  • Xiaoying Zhang

    (School of Computer Science and Technology, Hainan University, Haikou 570228, China
    Haikou Key Laboratory of Deep Learning and Big Data Application Technology, Hainan University, Haikou 570228, China)

  • Jie Shen

    (School of Computer Science and Technology, Hainan University, Haikou 570228, China
    Haikou Key Laboratory of Deep Learning and Big Data Application Technology, Hainan University, Haikou 570228, China)

  • Huaijin Hu

    (School of Computer Science and Technology, Hainan University, Haikou 570228, China
    Haikou Key Laboratory of Deep Learning and Big Data Application Technology, Hainan University, Haikou 570228, China)

  • Houqun Yang

    (School of Computer Science and Technology, Hainan University, Haikou 570228, China
    Haikou Key Laboratory of Deep Learning and Big Data Application Technology, Hainan University, Haikou 570228, China)

Abstract

With the goal of addressing the challenges of small, densely packed targets in remote sensing images, we propose a high-resolution instance segmentation model named QuadTransPointRend Net (QTPR-Net). This model significantly enhances instance segmentation performance in remote sensing images. The model consists of two main modules: preliminary edge feature extraction (PEFE) and edge point feature refinement (EPFR). We also created a specific approach and strategy named TransQTA for edge uncertainty point selection and feature processing in high-resolution remote sensing images. Multi-scale feature fusion and transformer technologies are used in QTPR-Net to refine rough masks and fine-grained features for selected edge uncertainty points while balancing model size and accuracy. Based on experiments performed on three public datasets: NWPU VHR-10, SSDD, and iSAID, we demonstrate the superiority of QTPR-Net over existing approaches.

Suggested Citation

  • Xiaoying Zhang & Jie Shen & Huaijin Hu & Houqun Yang, 2024. "A New Instance Segmentation Model for High-Resolution Remote Sensing Images Based on Edge Processing," Mathematics, MDPI, vol. 12(18), pages 1-17, September.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:18:p:2905-:d:1480376
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