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Construction of All-in-Focus Images Assisted by Depth Sensing

Multi-focus image fusion is a technique for obtaining an all-in-focus image in which all objects are in focus to extend the limited depth of field (DoF) of an imaging system. Different from traditional RGB-based methods, this paper presents a new multi-focus image fusion method assisted by depth sen...

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Detalles Bibliográficos
Autores principales: Liu, Hang, Li, Hengyu, Luo, Jun, Xie, Shaorong, Sun, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470578/
https://www.ncbi.nlm.nih.gov/pubmed/30909388
http://dx.doi.org/10.3390/s19061409
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author Liu, Hang
Li, Hengyu
Luo, Jun
Xie, Shaorong
Sun, Yu
author_facet Liu, Hang
Li, Hengyu
Luo, Jun
Xie, Shaorong
Sun, Yu
author_sort Liu, Hang
collection PubMed
description Multi-focus image fusion is a technique for obtaining an all-in-focus image in which all objects are in focus to extend the limited depth of field (DoF) of an imaging system. Different from traditional RGB-based methods, this paper presents a new multi-focus image fusion method assisted by depth sensing. In this work, a depth sensor is used together with a colour camera to capture images of a scene. A graph-based segmentation algorithm is used to segment the depth map from the depth sensor, and the segmented regions are used to guide a focus algorithm to locate in-focus image blocks from among multi-focus source images to construct the reference all-in-focus image. Five test scenes and six evaluation metrics were used to compare the proposed method and representative state-of-the-art algorithms. Experimental results quantitatively demonstrate that this method outperforms existing methods in both speed and quality (in terms of comprehensive fusion metrics). The generated images can potentially be used as reference all-in-focus images.
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spelling pubmed-64705782019-04-26 Construction of All-in-Focus Images Assisted by Depth Sensing Liu, Hang Li, Hengyu Luo, Jun Xie, Shaorong Sun, Yu Sensors (Basel) Article Multi-focus image fusion is a technique for obtaining an all-in-focus image in which all objects are in focus to extend the limited depth of field (DoF) of an imaging system. Different from traditional RGB-based methods, this paper presents a new multi-focus image fusion method assisted by depth sensing. In this work, a depth sensor is used together with a colour camera to capture images of a scene. A graph-based segmentation algorithm is used to segment the depth map from the depth sensor, and the segmented regions are used to guide a focus algorithm to locate in-focus image blocks from among multi-focus source images to construct the reference all-in-focus image. Five test scenes and six evaluation metrics were used to compare the proposed method and representative state-of-the-art algorithms. Experimental results quantitatively demonstrate that this method outperforms existing methods in both speed and quality (in terms of comprehensive fusion metrics). The generated images can potentially be used as reference all-in-focus images. MDPI 2019-03-22 /pmc/articles/PMC6470578/ /pubmed/30909388 http://dx.doi.org/10.3390/s19061409 Text en © 2019 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
Liu, Hang
Li, Hengyu
Luo, Jun
Xie, Shaorong
Sun, Yu
Construction of All-in-Focus Images Assisted by Depth Sensing
title Construction of All-in-Focus Images Assisted by Depth Sensing
title_full Construction of All-in-Focus Images Assisted by Depth Sensing
title_fullStr Construction of All-in-Focus Images Assisted by Depth Sensing
title_full_unstemmed Construction of All-in-Focus Images Assisted by Depth Sensing
title_short Construction of All-in-Focus Images Assisted by Depth Sensing
title_sort construction of all-in-focus images assisted by depth sensing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470578/
https://www.ncbi.nlm.nih.gov/pubmed/30909388
http://dx.doi.org/10.3390/s19061409
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