Open AccessImage enhancement comparison to improve underwater cultural heritage survey
Author(s) -
Eva Savina Malinverni,
Carlo Cerrano,
Ubaldo Pantaleo,
Corinne Andreola,
Marina Paolanti,
Stefano Chiappini,
Roberto Pierdicca
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/949/1/012102
Subject(s) - artificial intelligence , computer vision , computer science , underwater , point cloud , visibility , image quality , luminance , metric (unit) , software , image (mathematics) , geology , optics , physics , engineering , oceanography , operations management , programming language
This work aims at presenting an underwater image application to obtain an improved 3D model of cultural assets. In 2016, more than 500 images were acquired by a GoPro Camera with a low resolution of 72 dpi and focal length of 3 mm, without flash and are now used to reconstruct the 3D model of some amphoras of a Roman shipwreck found in Albenga (Italy). We have applied state-of-art image enhancement techniques, such as ACE, CLAHE, LAB and SP algorithms, to improve the quality of underwater images affected by low contrast, poor visibility conditions, not uniform lighting, colour variations, noise and blur effect. The visual quality has been evaluated through quantitative metrics, like average luminance, information entropy, average gradient of image, UCIQE and UIQM. Then, our efforts have been devoted to the dense 3D point cloud generation using a SfM-MVS software. In particular, the 3D reconstruction results are in line with the metric evaluation: in fact, the more accurate 3D objects are obtained from that enhanced dataset with the highest measured image quality.