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Article

Influence of Block Geometry Configuration on Multi-Image Dense Matching

1
Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze, 181/a, 43124 Parma, Italy
2
Centre for Geotechnical and Materials Modelling, The University of Newcastle, Callaghan, NSW 2308, Australia
*
Author to whom correspondence should be addressed.
Academic Editors: Valerio Baiocchi and Francesca Giannone
Remote Sens. 2022, 14(15), 3784; https://doi.org/10.3390/rs14153784
Received: 22 June 2022 / Revised: 2 August 2022 / Accepted: 2 August 2022 / Published: 6 August 2022
(This article belongs to the Special Issue New Trends in High Resolution Imagery Processing)
Digital photogrammetry is a widespread surveying technique in different fields of application due to its flexibility, versatility and cost-effectiveness. Despite its increasing automation and simplicity, a proper image block design is crucial to ensure high standards of performance and accuracy. Studies on camera network design have been largely dealt with in the scientific literature with reference to image orientation process, while they are still poor on dense matching. This paper investigates the influence of different block geometry configurations on multi-image dense matching. Starting from the same orientation solution, dense matching was performed considering different combinations of number of images and base length distance between the first and the last image within a strip. The raster Digital Elevation Models (DEM) resulting from each sequence of images were compared with a reference DEM to assess accuracy and completeness. The tests were conducted using different cameras and at various test sites to assess different survey conditions and generalize the findings. The presented results provide some operational guidance on block geometry optimization to maximize the accuracy and completeness. View Full-Text
Keywords: dense matching; MVS; block design optimization; multi-image; camera network; photogrammetry dense matching; MVS; block design optimization; multi-image; camera network; photogrammetry
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MDPI and ACS Style

Bruno, N.; Roncella, R.; Diotri, F.; Thoeni, K.; Giacomini, A. Influence of Block Geometry Configuration on Multi-Image Dense Matching. Remote Sens. 2022, 14, 3784. https://doi.org/10.3390/rs14153784

AMA Style

Bruno N, Roncella R, Diotri F, Thoeni K, Giacomini A. Influence of Block Geometry Configuration on Multi-Image Dense Matching. Remote Sensing. 2022; 14(15):3784. https://doi.org/10.3390/rs14153784

Chicago/Turabian Style

Bruno, Nazarena, Riccardo Roncella, Fabrizio Diotri, Klaus Thoeni, and Anna Giacomini. 2022. "Influence of Block Geometry Configuration on Multi-Image Dense Matching" Remote Sensing 14, no. 15: 3784. https://doi.org/10.3390/rs14153784

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