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Towards a framework for agent-based image analysis of remote-sensing data.

Peter Hofmann1, Paul Lettmayer2, Thomas Blaschke1

  • 1Interfaculty Department of Geoinformatics - Z_GIS, Salzburg University , Schillerstr. 30, Salzburg 5020 , Austria.

International Journal of Image and Data Fusion
|October 11, 2016
PubMed
Summary
This summary is machine-generated.

Object-based image analysis (OBIA) shows promise, but lacks automated adaptation. This study introduces agent-based image analysis (ABIA) for self-adapting image objects, improving robustness in remote sensing.

Keywords:
agent-based image analysisagent-based systemsautomation of image analysisautonomous systemsobject-based image analysisremote sensing

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Area of Science:

  • Remote Sensing
  • Computer Vision
  • Artificial Intelligence

Background:

  • Object-based image analysis (OBIA) offers improved classification over pixel-based methods for remote sensing data.
  • Current OBIA approaches often require manual adaptation for varying image contents, conditions, and sensor characteristics, limiting robustness and transferability.
  • Automated solutions for analyzing large remote sensing archives without human interaction are scarce due to the complexity and variability of image data.

Purpose of the Study:

  • To develop an automated framework for robust and transferable object-based image analysis.
  • To enable image objects to autonomously adapt to diverse imaging conditions and sensor characteristics.
  • To integrate the agent-based paradigm with OBIA for self-adapting rule sets and image objects.

Main Methods:

  • Investigated the coupling and integration of OBIA with the agent-based paradigm.
  • Focused on developing self-adapting image objects within a novel framework.
  • Introduced a framework for agent-based image analysis (ABIA).

Main Results:

  • The proposed agent-based image analysis (ABIA) framework facilitates self-adapting image objects.
  • This approach aims to overcome the limitations of manual rule-set adaptation in OBIA.
  • The integration enables image objects to adjust to varying imaging conditions and sensor characteristics autonomously.

Conclusions:

  • Agent-based image analysis (ABIA) offers a promising direction for enhancing the robustness and transferability of OBIA.
  • Self-adapting image objects are key to automating remote sensing image analysis across diverse datasets.
  • Further development of ABIA can lead to more efficient analysis of large remote sensing image archives.