On Image based Enhancement for 3D Dense Reconstruction of Low Light Aerial Visual Inspected Environments

Proceedings of the 2019 Computer Vision Conference (CVC), Volume 2

Document identifier: oai:DiVA.org:ltu-76966
Access full text here:10.1007/978-3-030-17798-0_23
Keyword: Engineering and Technology, Electrical Engineering, Electronic Engineering, Information Engineering, Control Engineering, Teknik och teknologier, Elektroteknik och elektronik, Reglerteknik, Low-illumination image processing, 3D reconstruction, MAVs
Publication year: 2019
Relevant Sustainable Development Goals (SDGs):
SDG 3 Good health and wellbeing
The SDG label(s) above have been assigned by OSDG.ai

Abstract:

Micro Aerial Vehicles (MAV)s have been distinguished, in the last decade, for their potential to inspect infrastructures in an active manner and provide critical information to the asset owners. Inspired by this trend, the mining industry is lately focusing to incorporate MAVs in their production cycles. Towards this direction, this article proposes a novel method to enhance 3D reconstruction of low-light environments, like underground tunnels, by using image processing. More specifically, the main idea is to enhance the low light resolution of the collected images, captured onboard an aerial platform, before inserting them to the reconstruction pipeline. The proposed method is based on the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm that limits the noise, while amplifies the contrast of the image. The overall efficiency and improvement achieved of the novel architecture has been extensively and successfully evaluated by utilizing data sets captured from real scale underground tunnels using a quadrotor.

Authors

Christoforos Kanellakis

Luleå tekniska universitet; Signaler och system
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Petros Karvelis

Luleå tekniska universitet; Signaler och system
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George Nikolakopoulos

Luleå tekniska universitet; Signaler och system
Other publications >>

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