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Development of a refined illumination and reflectance approach for optimal construction site interior image enhancement

Johnny Kwok Wai Wong (School of Built Environment, Faculty of Design, Architecture and Building, University of Technology Sydney, Sydney, Australia)
Mojtaba Maghrebi (Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran)
Alireza Ahmadian Fard Fini (School of Built Environment, Faculty of Design, Architecture and Building, University of Technology Sydney, Sydney, Australia)
Mohammad Amin Alizadeh Golestani (Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran)
Mahdi Ahmadnia (Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran)
Michael Er (School of Built Environment, Faculty of Design, Architecture and Building, University of Technology Sydney, Sydney, Australia)

Construction Innovation

ISSN: 1471-4175

Article publication date: 8 September 2022

Issue publication date: 13 February 2024

92

Abstract

Purpose

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

Design/methodology/approach

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

Findings

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

Originality/value

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

Keywords

Acknowledgements

This research was supported by the 5D BIM Lab Research Fund and the Research Seed Funding Scheme by the Faculty of Design, Architecture and Building, at the University of Technology Sydney. The authors thank Biyanka Ekanayake for her assistance with the research background of this study.

Citation

Wong, J.K.W., Maghrebi, M., Ahmadian Fard Fini, A., Alizadeh Golestani, M.A., Ahmadnia, M. and Er, M. (2024), "Development of a refined illumination and reflectance approach for optimal construction site interior image enhancement", Construction Innovation, Vol. 24 No. 2, pp. 470-491. https://doi.org/10.1108/CI-02-2022-0044

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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