A Flexible Coding Scheme Based on Block Krylov Subspace Approximation for Light Field Displays with Stacked Multiplicative Layers
To create a realistic 3D perception on glasses-free displays, it is critical to support continuous motion parallax, greater depths of field, and wider fields of view. A new type of <i>Layered</i> or <i>Tensor</i> light field 3D display has attracted greater attention these da...
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MDPI AG
2021-07-01
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| Online Access: | https://www.mdpi.com/1424-8220/21/13/4574 |
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| author | Joshitha Ravishankar Mansi Sharma Pradeep Gopalakrishnan |
| author_facet | Joshitha Ravishankar Mansi Sharma Pradeep Gopalakrishnan |
| author_sort | Joshitha Ravishankar |
| collection | DOAJ |
| description | To create a realistic 3D perception on glasses-free displays, it is critical to support continuous motion parallax, greater depths of field, and wider fields of view. A new type of <i>Layered</i> or <i>Tensor</i> light field 3D display has attracted greater attention these days. Using only a few light-attenuating pixelized layers (e.g., LCD panels), it supports many views from different viewing directions that can be displayed simultaneously with a high resolution. This paper presents a novel flexible scheme for efficient layer-based representation and lossy compression of light fields on layered displays. The proposed scheme learns stacked multiplicative layers optimized using a convolutional neural network (CNN). The intrinsic redundancy in light field data is efficiently removed by analyzing the hidden low-rank structure of multiplicative layers on a Krylov subspace. Factorization derived from Block Krylov singular value decomposition (BK-SVD) exploits the spatial correlation in layer patterns for multiplicative layers with varying low ranks. Further, encoding with HEVC eliminates inter-frame and intra-frame redundancies in the low-rank approximated representation of layers and improves the compression efficiency. The scheme is flexible to realize multiple bitrates at the decoder by adjusting the ranks of BK-SVD representation and HEVC quantization. Thus, it would complement the generality and flexibility of a data-driven CNN-based method for coding with multiple bitrates within a single training framework for practical display applications. Extensive experiments demonstrate that the proposed coding scheme achieves substantial bitrate savings compared with pseudo-sequence-based light field compression approaches and state-of-the-art JPEG and HEVC coders. |
| first_indexed | 2024-03-10T09:50:24Z |
| format | Article |
| id | doaj.art-f1ed7c09028b43b89942757348280828 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T09:50:24Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-f1ed7c09028b43b899427573482808282023-11-22T02:51:25ZengMDPI AGSensors1424-82202021-07-012113457410.3390/s21134574A Flexible Coding Scheme Based on Block Krylov Subspace Approximation for Light Field Displays with Stacked Multiplicative LayersJoshitha Ravishankar0Mansi Sharma1Pradeep Gopalakrishnan2Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600036, IndiaDepartment of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600036, IndiaDepartment of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600036, IndiaTo create a realistic 3D perception on glasses-free displays, it is critical to support continuous motion parallax, greater depths of field, and wider fields of view. A new type of <i>Layered</i> or <i>Tensor</i> light field 3D display has attracted greater attention these days. Using only a few light-attenuating pixelized layers (e.g., LCD panels), it supports many views from different viewing directions that can be displayed simultaneously with a high resolution. This paper presents a novel flexible scheme for efficient layer-based representation and lossy compression of light fields on layered displays. The proposed scheme learns stacked multiplicative layers optimized using a convolutional neural network (CNN). The intrinsic redundancy in light field data is efficiently removed by analyzing the hidden low-rank structure of multiplicative layers on a Krylov subspace. Factorization derived from Block Krylov singular value decomposition (BK-SVD) exploits the spatial correlation in layer patterns for multiplicative layers with varying low ranks. Further, encoding with HEVC eliminates inter-frame and intra-frame redundancies in the low-rank approximated representation of layers and improves the compression efficiency. The scheme is flexible to realize multiple bitrates at the decoder by adjusting the ranks of BK-SVD representation and HEVC quantization. Thus, it would complement the generality and flexibility of a data-driven CNN-based method for coding with multiple bitrates within a single training framework for practical display applications. Extensive experiments demonstrate that the proposed coding scheme achieves substantial bitrate savings compared with pseudo-sequence-based light field compression approaches and state-of-the-art JPEG and HEVC coders.https://www.mdpi.com/1424-8220/21/13/4574light fieldlossy compressionlayered tensor 3D displaysconvolutional neural networkKrylov subspacelow-rank approximation |
| spellingShingle | Joshitha Ravishankar Mansi Sharma Pradeep Gopalakrishnan A Flexible Coding Scheme Based on Block Krylov Subspace Approximation for Light Field Displays with Stacked Multiplicative Layers Sensors light field lossy compression layered tensor 3D displays convolutional neural network Krylov subspace low-rank approximation |
| title | A Flexible Coding Scheme Based on Block Krylov Subspace Approximation for Light Field Displays with Stacked Multiplicative Layers |
| title_full | A Flexible Coding Scheme Based on Block Krylov Subspace Approximation for Light Field Displays with Stacked Multiplicative Layers |
| title_fullStr | A Flexible Coding Scheme Based on Block Krylov Subspace Approximation for Light Field Displays with Stacked Multiplicative Layers |
| title_full_unstemmed | A Flexible Coding Scheme Based on Block Krylov Subspace Approximation for Light Field Displays with Stacked Multiplicative Layers |
| title_short | A Flexible Coding Scheme Based on Block Krylov Subspace Approximation for Light Field Displays with Stacked Multiplicative Layers |
| title_sort | flexible coding scheme based on block krylov subspace approximation for light field displays with stacked multiplicative layers |
| topic | light field lossy compression layered tensor 3D displays convolutional neural network Krylov subspace low-rank approximation |
| url | https://www.mdpi.com/1424-8220/21/13/4574 |
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