Light Field Compression With Disparity-Guided Sparse Coding Based on Structural Key Views
Light Field Compression With Disparity-Guided Sparse Coding Based on Structural Key Views
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DOI：
10.1109/tip.2017.2750413
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发表时间：
2018-01-01
影响因子：
10.6
通讯作者：
Chau, Lap-Pui
中科院分区：
文献类型：
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作者：
Chen, Jie;Hou, Junhui;Chau, Lap-Pui
最近的成像技术正在迅速发展，以采样更丰富、更身临其境的3D世界表示。其中一项新兴技术是基于微透镜阵列的光场相机。为了记录光线的方向信息，与空间尺寸相似的常规2D图像相比，低频图像需要更大的存储空间和传输带宽。因此，低频数据的压缩成为其应用的重要组成部分。在本文中，我们提出了一种基于视差引导稀疏编码的基于选择结构关键视图(SC-SKV)的学习透视移位LF字典上的LF编解码器。稀疏编码基于有限数量的优化选择的SKV；然而，可以从编码系数中恢复整个LF。通过在编码器和解码器之间保持相同的近似值，只需要将非关键视图、视差图和SKV的残差压缩到比特流中。提出了一种优化的SKV选择方法，使大多数低频空间信息得以保留。为了达到最佳的字典效率，LF被划分为几个编码区，在这些编码区上分别进行重建。在基准的低频数据集上进行了实验和比较，结果表明，与联合探索模型相比，SC-SKV编解码器在率失真性能和视觉质量方面都得到了令人信服的压缩结果：平均降低了37.9%的BD率和1.17dBBD-PSNR，特别是在低码率场景下，BD-PSNR提高了6dB。
Recent imaging technologies are rapidly evolving for sampling richer and more immersive representations of the 3D world. One of the emerging technologies is light field (LF) cameras based on micro-lens arrays. To record the directional information of the light rays, a much larger storage space and transmission bandwidth are required by an LF image as compared with a conventional 2D image of similar spatial dimension. Hence, the compression of LF data becomes a vital part of its application. In this paper, we propose an LF codec with disparity guided Sparse Coding over a learned perspective-shifted LF dictionary based on selected Structural Key Views (SC-SKV). The sparse coding is based on a limited number of optimally selected SKVs; yet the entire LF can be recovered from the coding coefficients. By keeping the approximation identical between encoder and decoder, only the residuals of the non-key views, disparity map, and the SKVs need to be compressed into the bit stream. An optimized SKV selection method is proposed such that most LF spatial information can be preserved. To achieve optimum dictionary efficiency, the LF is divided into several coding regions, over which the reconstruction works individually. Experiments and comparisons have been carried out over benchmark LF data set, which show that the proposed SC-SKV codec produces convincing compression results in terms of both rate-distortion performance and visual quality compared with Joint Exploration Model: with 37.9% BD-rate reduction and 1.17-dB BD-PSNR improvement achieved on average, especially with up to 6-dB improvement for low bit rate scenarios.