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A Unified Framework for Street-View Panorama Stitching.

Li Li1, Jian Yao2, Renping Xie3

  • 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China. li.li@whu.edu.cn.

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|December 28, 2016
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Summary
This summary is machine-generated.

This study presents a new framework for creating high-quality street-view panoramas by stitching multiple images. The method effectively corrects geometric and color inconsistencies for seamless results.

Keywords:
color correctiongraph cutsimage blendingimage parallaximage warpingpanorama stitchingseam line detection

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Area of Science:

  • Computer Vision
  • Image Processing
  • Computational Photography

Background:

  • Stitching multiple images into a panorama is challenging due to geometric and photometric inconsistencies.
  • Mobile platforms capture street-view images with varying projection centers and depth differences, complicating alignment.

Purpose of the Study:

  • To develop a unified framework for generating high-quality street-view panoramas from multiple images.
  • To address challenges in geometric misalignment and photometric inconsistencies during image stitching.

Main Methods:

  • Image warping using dense optical flow to correct geometric misalignment.
  • Color correction via histogram extreme point matching to reduce photometric inconsistencies.
  • Optimal seam line detection using graph cut energy minimization.
  • Image blending with Laplacian pyramid for artifact elimination.

Main Results:

  • The proposed framework successfully generates pleasant and high-quality street-view panoramas.
  • Experimental results demonstrate effectiveness on challenging real-world street-view images.
  • The system significantly suppresses influences of large geometric misalignment and illumination variations.

Conclusions:

  • The unified framework provides a robust solution for street-view panorama generation.
  • The combination of proposed methods effectively handles complex real-world imaging conditions.
  • The system is capable of producing visually appealing and artifact-free panoramic images.