基于纹理图像和深度图一致性的有效孔填充和深度增强

Ting-An Chang, Jung-Ping Kuo, J. Yang
{"title":"基于纹理图像和深度图一致性的有效孔填充和深度增强","authors":"Ting-An Chang, Jung-Ping Kuo, J. Yang","doi":"10.1109/APCCAS.2016.7803930","DOIUrl":null,"url":null,"abstract":"Structured-light RGB-D cameras are commonly used to capture depth images, which convey the per-pixel depth information in a scene. However, these cameras often produce regions with missing pixels. The missing pixel regions, which refer to holes, will not contain any depth information for the depth image. This reason would lead the performance to degrade seriously in modern-day three-dimensional (3D) video applications. Therefore, how to effectively utilize image information and depth maps become more and more important. In this paper, we propose adaptive texture-similarity-based hole filling (ATSHF) and adaptive texture-similarity-based depth enhancement (ATSDE). The proposed system, which is used for the enhancement of depth maps, is achieved by suppressing the noise, filling holes and sharpening object edges simultaneously. Experimental results demonstrate that the proposed method provides a superior performance, especially around the object boundary. Beside, we compare with the other state-of-the-art methods about the image and the depth map enhancement.","PeriodicalId":6495,"journal":{"name":"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","volume":"33 1","pages":"192-195"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Efficient hole filling and depth enhancement based on texture image and depth map consistency\",\"authors\":\"Ting-An Chang, Jung-Ping Kuo, J. Yang\",\"doi\":\"10.1109/APCCAS.2016.7803930\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Structured-light RGB-D cameras are commonly used to capture depth images, which convey the per-pixel depth information in a scene. However, these cameras often produce regions with missing pixels. The missing pixel regions, which refer to holes, will not contain any depth information for the depth image. This reason would lead the performance to degrade seriously in modern-day three-dimensional (3D) video applications. Therefore, how to effectively utilize image information and depth maps become more and more important. In this paper, we propose adaptive texture-similarity-based hole filling (ATSHF) and adaptive texture-similarity-based depth enhancement (ATSDE). The proposed system, which is used for the enhancement of depth maps, is achieved by suppressing the noise, filling holes and sharpening object edges simultaneously. Experimental results demonstrate that the proposed method provides a superior performance, especially around the object boundary. Beside, we compare with the other state-of-the-art methods about the image and the depth map enhancement.\",\"PeriodicalId\":6495,\"journal\":{\"name\":\"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)\",\"volume\":\"33 1\",\"pages\":\"192-195\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCCAS.2016.7803930\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCCAS.2016.7803930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

结构光RGB-D相机通常用于捕获深度图像,它传达场景中的每像素深度信息。然而,这些相机经常产生缺少像素的区域。缺失的像素区域(指孔)将不包含深度图像的任何深度信息。在现代三维(3D)视频应用中,这个原因会导致性能严重下降。因此,如何有效地利用图像信息和深度图变得越来越重要。本文提出了基于纹理相似度的自适应钻孔填充(ATSHF)和基于纹理相似度的自适应深度增强(ATSDE)。该系统通过抑制噪声、填充孔洞和锐化物体边缘来实现深度图的增强。实验结果表明,该方法具有较好的性能,特别是在目标边界附近。此外,我们还比较了目前最先进的图像增强方法和深度图增强方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient hole filling and depth enhancement based on texture image and depth map consistency
Structured-light RGB-D cameras are commonly used to capture depth images, which convey the per-pixel depth information in a scene. However, these cameras often produce regions with missing pixels. The missing pixel regions, which refer to holes, will not contain any depth information for the depth image. This reason would lead the performance to degrade seriously in modern-day three-dimensional (3D) video applications. Therefore, how to effectively utilize image information and depth maps become more and more important. In this paper, we propose adaptive texture-similarity-based hole filling (ATSHF) and adaptive texture-similarity-based depth enhancement (ATSDE). The proposed system, which is used for the enhancement of depth maps, is achieved by suppressing the noise, filling holes and sharpening object edges simultaneously. Experimental results demonstrate that the proposed method provides a superior performance, especially around the object boundary. Beside, we compare with the other state-of-the-art methods about the image and the depth map enhancement.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信