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Epipolar Rectification with Minimum Perspective Distortion for Oblique Images.

Jianchen Liu1, Bingxuan Guo2, Wanshou Jiang3

  • 1School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan 430079, China. liujianchen@whu.edu.cn.

Sensors (Basel, Switzerland)
|November 10, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a new epipolar rectification algorithm for Unmanned Aerial Vehicle (UAV) images to minimize perspective distortion. The method enhances dense matching precision by up to 30% for roofs and 22% for façades.

Keywords:
3D reconstructionUAV imagesepipolar rectificationminimum perspective distortionoblique images

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Area of Science:

  • Photogrammetry
  • Computer Vision
  • Remote Sensing

Background:

  • Epipolar rectification is crucial for 3D modeling using Unmanned Aerial Vehicle (UAV) images.
  • Existing methods often neglect perspective distortion relative to surface planes.

Purpose of the Study:

  • To propose and detail an algorithm for rectifying oblique images by minimizing perspective distortion.
  • To improve the accuracy of dense matching in photogrammetric applications.

Main Methods:

  • Formulating perspective distortion minimization as a cost function based on angle deformation.
  • Utilizing flexible reference planes (e.g., roofs, façades) for rectification.
  • Acquiring a suitable scale based on dihedral angles and cropping low-quality regions.

Main Results:

  • The proposed method significantly improves matching precision.
  • Matching precision increased by approximately 30% for roofs.
  • Matching precision improved by an average of 22% for façades parallel to the baseline.

Conclusions:

  • Eliminating perspective distortion in rectified images substantially enhances dense matching accuracy.
  • The algorithm offers flexibility in reference plane selection for improved photogrammetric results.