| 基于多视点伪序列的光场图像压缩 |
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| 引用本文： | 马晓辉,曾焕强,陈婧,朱建清,蔡灿辉.基于多视点伪序列的光场图像压缩[J].信号处理,2019,35(3):378-385. |
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| 作者姓名： | 马晓辉 曾焕强 陈婧 朱建清 蔡灿辉 |
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| 作者单位： | 华侨大学信息科学与工程学院,厦门市移动多媒体通信重点实验室 |
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| 基金项目： | 国家自然科学基金项目(61871434, 61802136, 61602191)；福建省自然科学基金项目(2019J06017, 2017J05103,2016J01308)；泉州市高层次人才创新创业项目(2017G027)；华侨大学中青年教师科研提升资助计划(ZQN-YX403, ZQN-PY418)；华侨大学高层次人才资助项目(14BS201,14BS204, 16BS709)；华侨大学研究生科研创新能力培育计划资助项目(17014082024)
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| 摘 要： | 近年来,作为一种能够提供更富有沉浸感的多媒体媒质,光场图像(Light Field Image,LFI)引起广泛的关注。针对光场图像数据量巨大的问题,本文提出了一种基于多视点伪序列的光场图像高效压缩方案。在编码端,所提方法首先将光场相机捕获得到的原始光场图像根据相机的微透镜阵列分解成子孔径图像。接着根据子孔径图像存在较强视点内和视点间相关性,选取部分子孔径图像进行多视点伪序列构建,基于MV-HEVC设计适用于多视点伪序列的预测编码结构进行编码。在解码端,所提方法基于已解码多视点伪序列通过视频帧插值方法重建出未编码传输的子孔径视图,从而重建出全部光场图像。实验结果表明本文所提算法优于现有基于视差引导稀疏编码的光场图像压缩方法,BD-rate平均节约18.5%,BD-PSNR平均提高1.28 dB。
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| 关 键 词： | 光场图像 图像压缩 多视点伪序列 预测结构 |
| 收稿时间： | 2018-12-31 |
Light Field Image Compression Based on Multi-view Pesudo Sequence |
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| Ma Xiaohui,Zeng Huanqiang,Chen Jing,Zhu Jianqing,Cai Canhui.Light Field Image Compression Based on Multi-view Pesudo Sequence[J].Signal Processing,2019,35(3):378-385. |
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| Authors: | Ma Xiaohui Zeng Huanqiang Chen Jing Zhu Jianqing Cai Canhui |
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| Affiliation: | (School of Information Science and Engineering,Huaqiao University,Xiamen Key Laboratory of Mobile Multimedia Communications,Xiamen,Fujian 361021,China) |
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| Abstract: | In recent years, Light Field Image (LFI) that can provide more immersive multimedia experience has attracted extensive attentions. Considering that the LFI has huge amount of data, this paper proposes an efficient light field image compression scheme based on multi-view pesudo sequence. In the encoder side, the raw image captured by the light field camera is firstly decomposed into sub-aperture images (SAIs) according to the lenslet array of the camera. Since the SAIs have strong intra-view and inter-view correlations, some SAIs are selected to construct the multi-view pseudo sequence, which is encoded based on MV-HEVC via the proposed prediction structure. In the decoder side, the un-encoded SAIs are interpolated based on the decoded multi-view pseudo-sequence through the video frame interpolation method, thereby restoring all light field images. Experimental results have demonstrated the proposed method outperforms the state-of-the-art LFI compression scheme based on disparity guided sparse coding, with 18.5% BD-rate reduction and 1.28 dB BD-PSNR improvement on average. |
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| Keywords: | light field image image compression multi-view pesudo sequence prediction structure |
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