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作者:

Wang, Chen (Wang, Chen.) | Qi, Na (Qi, Na.) | Zhu, Qing (Zhu, Qing.) (学者:朱青)

收录:

CPCI-S

摘要:

Light field is a kind of 4D signal that contains rich information about position and angle of light, which can express the scene more accurately. Light field is easily affected by noise for the hardware sensitivity. This paper utilizes the intrinsic tensor sparsity model and integrates super-resolution(SR) into a unified light field denoising method based on tensor operation. Avoiding vectorization, we make full use of correlation of light field. By exploiting SR method, we avoid sub-pixel mis-alignment in the searching process of similar patch. Experimental results validate that our proposed method outperforms the state-of-art methods in terms of both objective and subjective quality on the HCI light field old dataset.

关键词:

image denoising Light field super-resolution tensor sparsity

作者机构:

  • [ 1 ] [Wang, Chen]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 2 ] [Qi, Na]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 3 ] [Zhu, Qing]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

通讯作者信息:

  • [Wang, Chen]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

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来源 :

2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)

ISSN: 1522-4880

年份: 2020

页码: 1078-1082

语种: 英文

被引次数:

WoS核心集被引频次: 1

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

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中文被引频次:

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