# Pseudo Sequence based 2-D hierarchical reference structure for Light-Field Image Compression

arXiv: https://arxiv.org/abs/1612.07309 · HTML: https://mlsanity.com/paper/1612.07309/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Dec 2016.

## Built on by (most cited first, 8 of 8)

- [A Hierarchical Coding Scheme for Glasses-free 3D Displays Based on Scalable Hybrid Layered Representation of Real-World Light Fields](https://mlsanity.com/paper/2104.09378/) (2021)
- [Learned Focused Plenoptic Image Compression with Microimage Preprocessing and Global Attention](https://mlsanity.com/paper/2305.00489/) (2023)
- [Learning Kernel-Modulated Neural Representation for Efficient Light Field Compression](https://mlsanity.com/paper/2307.06143/) (2023)
- [A Novel Hierarchical Light Field Coding Scheme Based on Hybrid Stacked Multiplicative Layers and Fourier Disparity Layers for Glasses-Free 3D Displays](https://mlsanity.com/paper/2108.12399/) (2021)
- [LFIC-DRASC: Deep Light Field Image Compression Using Disentangled Representation and Asymmetrical Strip Convolution](https://mlsanity.com/paper/2409.11711/) (2024)
- [Ray-Space Motion Compensation for Lenslet Plenoptic Video Coding](https://mlsanity.com/paper/2207.00522/) (2022)
- [A Novel Light Field Coding Scheme Based on Deep Belief Network & Weighted Binary Images for Additive Layered Displays](https://mlsanity.com/paper/2210.01447/) (2022)
- [SANR: Scene-Aware Neural Representation for Light Field Image Compression with Rate-Distortion Optimization](https://mlsanity.com/paper/2510.15775/) (2025)

## Abstract (arXiv)

In this paper, we present a novel pseudo sequence based 2-D hierarchical reference structure for light-field image compression. In the proposed scheme, we first decompose the light-field image into multiple views and organize them into a 2-D coding structure according to the spatial coordinates of the corresponding microlens. Then we mainly develop three technologies to optimize the 2-D coding structure. First, we divide all the views into four quadrants, and all the views are encoded one quadrant after another to reduce the reference buffer size as much as possible. Inside each quadrant, all the views are encoded hierarchically to fully exploit the correlations between different views. Second, we propose to use the distance between the current view and its reference views as the criteria for selecting better reference frames for each inter view. Third, we propose to use the spatial relative positions between different views to achieve more accurate motion vector scaling. The whole scheme is implemented in the reference software of High Efficiency Video Coding. The experimental results demonstrate that the proposed novel pseudo-sequence based 2-D hierarchical structure can achieve maximum 14.2% bit-rate savings compared with the state-of-the-art light-field image compression method.