Double-Constraint Inpainting Model of a Single-Depth Image

In real applications, obtained depth images are incomplete; therefore, depth image inpainting is studied here. A novel model that is characterised by both a low-rank structure and nonlocal self-similarity is proposed. As a double constraint, the low-rank structure and nonlocal self-similarity can fu...

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Main Authors: Wu Jin, Li Zun, Liu Yong
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/6/1797
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author Wu Jin
Li Zun
Liu Yong
author_facet Wu Jin
Li Zun
Liu Yong
author_sort Wu Jin
collection DOAJ
description In real applications, obtained depth images are incomplete; therefore, depth image inpainting is studied here. A novel model that is characterised by both a low-rank structure and nonlocal self-similarity is proposed. As a double constraint, the low-rank structure and nonlocal self-similarity can fully exploit the features of single-depth images to complete the inpainting task. First, according to the characteristics of pixel values, we divide the image into blocks, and similar block groups and three-dimensional arrangements are then formed. Then, the variable splitting technique is applied to effectively divide the inpainting problem into the sub-problems of the low-rank constraint and nonlocal self-similarity constraint. Finally, different strategies are used to solve different sub-problems, resulting in greater reliability. Experiments show that the proposed algorithm attains state-of-the-art performance.
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spelling doaj.art-a6516c438766422ab5f43faf9df19f7f2022-12-22T02:57:43ZengMDPI AGSensors1424-82202020-03-01206179710.3390/s20061797s20061797Double-Constraint Inpainting Model of a Single-Depth ImageWu Jin0Li Zun1Liu Yong2School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, ChinaSchool of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, ChinaSchool of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, ChinaIn real applications, obtained depth images are incomplete; therefore, depth image inpainting is studied here. A novel model that is characterised by both a low-rank structure and nonlocal self-similarity is proposed. As a double constraint, the low-rank structure and nonlocal self-similarity can fully exploit the features of single-depth images to complete the inpainting task. First, according to the characteristics of pixel values, we divide the image into blocks, and similar block groups and three-dimensional arrangements are then formed. Then, the variable splitting technique is applied to effectively divide the inpainting problem into the sub-problems of the low-rank constraint and nonlocal self-similarity constraint. Finally, different strategies are used to solve different sub-problems, resulting in greater reliability. Experiments show that the proposed algorithm attains state-of-the-art performance.https://www.mdpi.com/1424-8220/20/6/1797depth image inpaintingvariable splitting techniquelow-rank constraintnonlocal self-similarity constraint
spellingShingle Wu Jin
Li Zun
Liu Yong
Double-Constraint Inpainting Model of a Single-Depth Image
Sensors
depth image inpainting
variable splitting technique
low-rank constraint
nonlocal self-similarity constraint
title Double-Constraint Inpainting Model of a Single-Depth Image
title_full Double-Constraint Inpainting Model of a Single-Depth Image
title_fullStr Double-Constraint Inpainting Model of a Single-Depth Image
title_full_unstemmed Double-Constraint Inpainting Model of a Single-Depth Image
title_short Double-Constraint Inpainting Model of a Single-Depth Image
title_sort double constraint inpainting model of a single depth image
topic depth image inpainting
variable splitting technique
low-rank constraint
nonlocal self-similarity constraint
url https://www.mdpi.com/1424-8220/20/6/1797
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AT lizun doubleconstraintinpaintingmodelofasingledepthimage
AT liuyong doubleconstraintinpaintingmodelofasingledepthimage