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作者:

Wang, Yu-Ping (Wang, Yu-Ping.) | Wang, Li-Chun (Wang, Li-Chun.) (学者:王立春) | Kong, De-Hui (Kong, De-Hui.) (学者:孔德慧) | Yin, Bao-Cai (Yin, Bao-Cai.) (学者:尹宝才)

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Scopus SCIE

摘要:

Acquiring light field with larger angular resolution and higher spatial resolution in low cost is the goal of light field capture. Combining or modifying traditional optical cameras is a usual method for designing light field capture equipment, among which most models should deliberate trade-off between angular and spatial resolution, but augmenting coded aperture avoids this consideration by multiplexing information from different views. On the basis of coded aperture, this paper suggests an improved light field camera model that has double measurements and one mask. The two compressive measurements are respectively realized by a coded aperture and a random convolution CMOS imager, the latter is used as imaging sensor of the camera. The single mask design permits high light efficiency, which enables the sampling images to have high clarity. The double measurement design keeps more correlation information, which is conductive to enhancing the reconstructed light field. The higher clarity and more correlation of samplings mean higher quality of rebuilt light field, which also means higher resolution under condition of a lower PSNR requirement for rebuilt light field. Experimental results have verified advantage of the proposed design: compared with the representative mask-based light field camera models, the proposed model has the highest reconstruction quality and a higher light efficiency.

关键词:

compressive sensing Light field coded aperture random convolution CMOS

作者机构:

  • [ 1 ] [Wang, Yu-Ping]Beijing Univ Technol, Coll Metropolitan Transportat, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China
  • [ 2 ] [Wang, Li-Chun]Beijing Univ Technol, Coll Metropolitan Transportat, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China
  • [ 3 ] [Kong, De-Hui]Beijing Univ Technol, Coll Metropolitan Transportat, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China
  • [ 4 ] [Yin, Bao-Cai]Beijing Univ Technol, Coll Metropolitan Transportat, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China

通讯作者信息:

  • 王立春

    [Wang, Li-Chun]Beijing Univ Technol, Coll Metropolitan Transportat, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China

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来源 :

IEEE TRANSACTIONS ON IMAGE PROCESSING

ISSN: 1057-7149

年份: 2015

期: 12

卷: 24

页码: 5609-5618

1 0 . 6 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:174

JCR分区:1

中科院分区:2

被引次数:

WoS核心集被引频次: 8

SCOPUS被引频次: 8

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