Near-Lossless Coding of Plenoptic Camera Sensor Images for Archiving Light Field Array of Views
被引:0
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作者:
论文数: 引用数:
h-index:
机构:
Palma, Emanuele
[1
]
论文数: 引用数:
h-index:
机构:
Tabus, Ioan
[1
]
机构:
[1] Tampere Univ, Informat Technol & Commun Sci, Tampere, Finland
来源:
2022 ELEVENTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA)
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2022年
关键词:
light field;
compression;
image processing;
image compression;
light field compression;
D O I:
10.1109/IPTA54936.2022.9784151
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
In this paper we propose a near-lossless encoder for sensor images acquired by plenoptic cameras, and we investigate its usage for encoding in an archive all information needed for reconstructing high quality versions of the light field (LF) array of views(AoV). The near-lossless encoding of the plenoptic camera sensor image is realized by a modified version of the recently published sparse relevant regressors and contexts (SRRC) encoder. The lossy reconstruction is obtained in two nested loops: the outer one operates over the sensor image patches (each patch corresponding to a microlens image), and the inner loop operates over the pixels in the patch. In the latter, we enforce the SRRC predictors to use the already reconstructed lossy version of the sensor image. Then, we examine the usage of the near-lossless SRRC (NL-SRRC) codec as a building block for an archiving scheme including all information needed for running the plenoptic processing pipeline and obtaining the LFAoV. Finally, we replace in the archiving scheme the NL-SRRC codec with other state of the art lossy codecs and compare the results, which show that NL-SRRC based archiving scheme achieves better performance for the range of high bitrates.