3D Information from Scattering Media Images

Laksmita Rahadianti, Laksmita Rahadianti (2021) 3D Information from Scattering Media Images. Jurnal Ilmu Komputer dan Informasi, 14 (1). pp. 73-83. ISSN e-ISSN 2502-9274

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Abstract

Haze, fog, and bad weather conditions occur often in daily life. In these scattering media environments,
micro-particles interfere with light propagation and image formation. Images captured in these conditions
will suffer from low contrast and loss of intensity, hindering many computer vision methods. Thus, many
approaches attempt to estimate the corresponding clear scene before processing the image further. However,
the image formation model in scattering media shows that the 3D distance information is encoded implicitly
in image intensities. In this paper, we provide a systematic review on methods to estimate relative depth
and explicit depth directly from scattering media images. We use a dataset consisting of synthesized
hazy images with known ground truths to establish accuracy, as well as real hazy images for a general
visual analysis. For the accuracy evaluation, we demonstrate transmission estimation using statistical
priors obtaining an average SSIM of 0.411 and MAE of 1.004; and depth map estimation using deep
networks with an average SSIM of 0.305 and MAE of 0.860. Furthermore, for additional visual analysis,
we also present the distance estimation for real hazy and underwater images of which we have no ground truth

Item Type:	Article
Uncontrolled Keywords:	scattering media, 3D depth, transmission, statistical prior, airlight
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User:	Mrs Ni Made Yunia Dwi Savitri
Date Deposited:	17 Nov 2022 01:35
Last Modified:	17 Nov 2022 01:35
URI:	http://eprints.triatmamulya.ac.id/id/eprint/1841

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