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Seamline Determination Based on PKGC Segmentation for Remote Sensing Image Mosaicking.

Qiang Dong1,2, Jinghong Liu3

  • 1Chinese Academy of Science, Changchun Institute of Optics Fine Mechanics and Physics, #3888 Dongnanhu Road, Changchun 130033, China. dongqiang13@mails.ucas.ac.cn.

Sensors (Basel, Switzerland)
|July 28, 2017
PubMed
Summary

This study introduces an efficient seamline determination method for remote sensing image mosaicking. The novel approach effectively bypasses obvious objects, improving accuracy and execution time compared to traditional techniques.

Keywords:
graph cutsimage mosaickingimage segmentationmulti-scale morphological gradient (MSMG)remote sensingseamline detection

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Area of Science:

  • Remote Sensing
  • Computer Vision
  • Image Processing

Background:

  • Accurate seamline determination is crucial for seamless remote sensing image mosaicking.
  • Existing methods may struggle with complex scenes containing obvious objects.

Purpose of the Study:

  • To develop a novel, efficient seamline determination method for remote sensing image mosaicking.
  • To improve seamline placement by avoiding obvious objects and reducing processing time.

Main Methods:

  • A two-level optimization strategy involving object-level and pixel-level optimization.
  • Parametric kernel graph cuts (PKGC) segmentation for region extraction (background regions - BRs, obvious regions - ORs).
  • A weighted global cost map incorporating color difference, multi-scale morphological gradient (MSMG), and texture difference, weighted by BRs.
  • Dijkstra's shortest path algorithm for pixel-level seamline optimization.

Main Results:

  • The proposed method successfully bypasses obvious objects in remote sensing images.
  • Achieved superior performance and efficiency compared to conventional mean-shift segmentation-based methods.
  • Demonstrated reduced execution time for seamline determination.

Conclusions:

  • The novel two-level optimization strategy offers an efficient and superior solution for seamline determination in remote sensing image mosaicking.
  • The method's ability to avoid obvious objects enhances the quality of mosaicked images.
  • This approach is highly suitable for applications requiring precise and rapid image mosaicking.