Cargando…

Texture Synthesis Repair of RealSense D435i Depth Images with Object-Oriented RGB Image Segmentation

A depth camera is a kind of sensor that can directly collect distance information between an object and the camera. The RealSense D435i is a low-cost depth camera that is currently in widespread use. When collecting data, an RGB image and a depth image are acquired simultaneously. The quality of the...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Longyu, Xia, Hao, Qiao, Yanyou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7727865/
https://www.ncbi.nlm.nih.gov/pubmed/33255511
http://dx.doi.org/10.3390/s20236725
_version_ 1783621145205932032
author Zhang, Longyu
Xia, Hao
Qiao, Yanyou
author_facet Zhang, Longyu
Xia, Hao
Qiao, Yanyou
author_sort Zhang, Longyu
collection PubMed
description A depth camera is a kind of sensor that can directly collect distance information between an object and the camera. The RealSense D435i is a low-cost depth camera that is currently in widespread use. When collecting data, an RGB image and a depth image are acquired simultaneously. The quality of the RGB image is good, whereas the depth image typically has many holes. In a lot of applications using depth images, these holes can lead to serious problems. In this study, a repair method of depth images was proposed. The depth image is repaired using the texture synthesis algorithm with the RGB image, which is segmented through a multi-scale object-oriented method. The object difference parameter is added to the process of selecting the best sample block. In contrast with previous methods, the experimental results show that the proposed method avoids the error filling of holes, the edge of the filled holes is consistent with the edge of RGB images, and the repair accuracy is better. The root mean square error, peak signal-to-noise ratio, and structural similarity index measure from the repaired depth images and ground-truth image were better than those obtained by two other methods. We believe that the repair of the depth image can improve the effects of depth image applications.
format Online
Article
Text
id pubmed-7727865
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-77278652020-12-11 Texture Synthesis Repair of RealSense D435i Depth Images with Object-Oriented RGB Image Segmentation Zhang, Longyu Xia, Hao Qiao, Yanyou Sensors (Basel) Article A depth camera is a kind of sensor that can directly collect distance information between an object and the camera. The RealSense D435i is a low-cost depth camera that is currently in widespread use. When collecting data, an RGB image and a depth image are acquired simultaneously. The quality of the RGB image is good, whereas the depth image typically has many holes. In a lot of applications using depth images, these holes can lead to serious problems. In this study, a repair method of depth images was proposed. The depth image is repaired using the texture synthesis algorithm with the RGB image, which is segmented through a multi-scale object-oriented method. The object difference parameter is added to the process of selecting the best sample block. In contrast with previous methods, the experimental results show that the proposed method avoids the error filling of holes, the edge of the filled holes is consistent with the edge of RGB images, and the repair accuracy is better. The root mean square error, peak signal-to-noise ratio, and structural similarity index measure from the repaired depth images and ground-truth image were better than those obtained by two other methods. We believe that the repair of the depth image can improve the effects of depth image applications. MDPI 2020-11-24 /pmc/articles/PMC7727865/ /pubmed/33255511 http://dx.doi.org/10.3390/s20236725 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Longyu
Xia, Hao
Qiao, Yanyou
Texture Synthesis Repair of RealSense D435i Depth Images with Object-Oriented RGB Image Segmentation
title Texture Synthesis Repair of RealSense D435i Depth Images with Object-Oriented RGB Image Segmentation
title_full Texture Synthesis Repair of RealSense D435i Depth Images with Object-Oriented RGB Image Segmentation
title_fullStr Texture Synthesis Repair of RealSense D435i Depth Images with Object-Oriented RGB Image Segmentation
title_full_unstemmed Texture Synthesis Repair of RealSense D435i Depth Images with Object-Oriented RGB Image Segmentation
title_short Texture Synthesis Repair of RealSense D435i Depth Images with Object-Oriented RGB Image Segmentation
title_sort texture synthesis repair of realsense d435i depth images with object-oriented rgb image segmentation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7727865/
https://www.ncbi.nlm.nih.gov/pubmed/33255511
http://dx.doi.org/10.3390/s20236725
work_keys_str_mv AT zhanglongyu texturesynthesisrepairofrealsensed435idepthimageswithobjectorientedrgbimagesegmentation
AT xiahao texturesynthesisrepairofrealsensed435idepthimageswithobjectorientedrgbimagesegmentation
AT qiaoyanyou texturesynthesisrepairofrealsensed435idepthimageswithobjectorientedrgbimagesegmentation