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A novel framework for very high resolution remote sensing image change detection

Author

Listed:
  • Jie Li
  • Ning Sun
  • Jianlong Zhang

Abstract

This paper proposes a novel framework for very high resolution remote sensing image change detection. The change detection technology is the goals or the phenomenon conditions of different time interval to the change that have analysed the recognition and computer image processing system, including judgement goal whether changes, to determine changes the region and the time and spatial distribution of pattern category and appraisal change of distinction change. Over the past few years, researchers from all over the world have devoted themselves to the research of change detection technology. Many detection methods based on remote sensing images have been developed successively. However, no change detection method has absolute superiority in present research. This paper obtains the inspiration from PSO and OTSU to propose the particle swarm optimisation segmentation jointed model to construct the optimal solution of generating change map and the PSO jointed OTSU is introduced to help obtain the optimal threshold. Numerical simulation proves that the proposed method can segment the changed regions accurately while keeping the high noise robustness.

Suggested Citation

  • Jie Li & Ning Sun & Jianlong Zhang, 2018. "A novel framework for very high resolution remote sensing image change detection," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 19(2/3/4), pages 357-372.
  • Handle: RePEc:ids:ijnvor:v:19:y:2018:i:2/3/4:p:357-372
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    Cited by:

    1. Xiaorui Sun & Henan Wu & Guang Yu & Nan Zheng, 2024. "Research on the Automatic Detection of Ship Targets Based on an Improved YOLO v5 Algorithm and Model Optimization," Mathematics, MDPI, vol. 12(11), pages 1-16, May.

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