A novel light field compression framework with hybrid residue transform mechanism

A novel light field compression framework with hybrid residue transform mechanism
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一种具有混合残差变换机制的新型光场压缩框架

DOI:
10.1049/ell2.12395
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发表时间:
2021-12
期刊:
Electron. Lett.
影响因子:
--
通讯作者:
Liquan Shen
Liquan Shen
中科院分区:
其他
文献类型:
--
作者:
Xinpeng Huang;Ping An;Chao Yang;Liquan Shen

文献摘要

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相似文献

为了应对压缩海量光场数据的挑战,许多基于预测的算法都取得了令人满意的结果。虽然这些算法通过角度预测去除了大部分冗余,但它们很少为预测残差开发出合适的去相关解决方案,导致在更高的压缩性能方面存在很大差距。因此,本文提出了一种混合残差变换(HRT)机制,以充分利用预测残差中的相关性进行三层分层光场压缩。具体地说,预测残差是根据作者的三层结构分层生成的。此外,考虑到光场残差的高维特性,交替使用了高维变换,包括三维和四维离散余弦变换,使残差的能量更加紧凑。实验结果表明,该方法的性能优于现有的方法。
To meet the challenge of compressing the vast light field data, many prediction‐based algorithms achieve satisfactory results. Although these algorithms remove most redundancy through angular prediction, they rarely develop the suitable de‐correlation solutions for the prediction residue, leading to a large gap for higher compression performance. Therefore, this letter proposes a hybrid residue transform (HRT) mechanism to fully exploit the correlations in prediction residue for a three‐layer hierarchical light field compression. Specifically, the prediction residue is hierarchically generated from the authors' three‐layer structure. Besides, considering the high‐dimensional feature of light field residue, the high‐dimensional transforms, including 3D and 4D discrete cosine transforms, are alternately utilized to make the energy of the residue more compact. Experimental results demonstrate that the proposed method outperforms the state‐of‐the‐art methods.
DOI: 10.1049/el.2017.4560
发表时间: 2018-03
影响因子: 1.1
作者:
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通讯作者: Yu Liu;Ce Zhu;Min Mao
具有几何和内容一致性的低比特率光场压缩
DOI: 10.1109/tmm.2020.3046860
发表时间: 2022-01-01
影响因子: 7.3
作者:
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通讯作者: Shen, Liquan
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发表时间: 2023
期刊: Seminal Graphics Papers: Pushing the Boundaries, Volume 2
影响因子: --
作者:
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