Comparative study on four algorithms for dense matching of aerial images

Yen Ting Lee, Jaan-Rong Tsay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper investigates four algorithms for dense matching of aerial images, they are (1) Photosynth, (2) Pix4UAV, (3) the SIFT-based approach and (4) tensor voting method. The afore-mentioned four algorithms are compared with respect to their dense matching performance inclusive of four issues: (1) accuracy, (2) reliability, (3) point density and (4) computation speed. This study adopts some aerial images covering a test field with high accuracy of check points. Error detection on their matching results will be done either by bundle block adjustment or relative orientation computation. The rate of successful matching will be assessed and analyzed. After blunder detection and deletion, the accuracy of the final matching results is evaluated by means of those ground check points. Some statistical figures are used to illustrate the quality and efficiency of these four dense matching algorithms.

Original languageEnglish
Title of host publication34th Asian Conference on Remote Sensing 2013, ACRS 2013
PublisherAsian Association on Remote Sensing
Pages328-335
Number of pages8
ISBN (Print)9781629939100
Publication statusPublished - 2013 Jan 1
Event34th Asian Conference on Remote Sensing 2013, ACRS 2013 - Bali, Indonesia
Duration: 2013 Oct 202013 Oct 24

Publication series

Name34th Asian Conference on Remote Sensing 2013, ACRS 2013
Volume1

Other

Other34th Asian Conference on Remote Sensing 2013, ACRS 2013
CountryIndonesia
CityBali
Period13-10-2013-10-24

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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