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A Metric for Light Field Reconstruction, Compression, and Display Quality Evaluation.

Authors :
Min, Xiongkuo
Zhou, Jiantao
Zhai, Guangtao
Le Callet, Patrick
Yang, Xiaokang
Guan, Xinping
Source :
IEEE Transactions on Image Processing; 2020, Vol. 29, p3790-3804, 15p
Publication Year :
2020

Abstract

Owning to the recorded light ray distributions, light field contains much richer information and provides possibilities of some enlightening applications, and it has becoming more and more popular. To facilitate the relevant applications, many light field processing techniques have been proposed recently. These operations also bring the loss of visual quality, and thus there is need of a light field quality metric to quantify the visual quality loss. To reduce the processing complexity and resource consumption, light fields are generally sparsely sampled, compressed, and finally reconstructed and displayed to the users. We consider the distortions introduced in this typical light field processing chain, and propose a full-reference light field quality metric. Specifically, we measure the light field quality from three aspects: global spatial quality based on view structure matching, local spatial quality based on near-edge mean square error, and angular quality based on multi-view quality analysis. These three aspects have captured the most common distortions introduced in light field processing, including global distortions like blur and blocking, local geometric distortions like ghosting and stretching, and angular distortions like flickering and sampling. Experimental results show that the proposed method can estimate light field quality accurately, and it outperforms the state-of-the-art quality metrics which may be effective for light field. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
POSSIBILITY

Details

Language :
English
ISSN :
10577149
Volume :
29
Database :
Complementary Index
Journal :
IEEE Transactions on Image Processing
Publication Type :
Academic Journal
Accession number :
170078229
Full Text :
https://doi.org/10.1109/TIP.2020.2966081