Comparison and Evaluation of Light Field Image Coding Approaches

Viola, Irene; Řeřábek, Martin; Ebrahimi, Touradj

doi:10.1109/jstsp.2017.2740167

Cited by 73 publications

(51 citation statements)

References 35 publications

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“…The compression rates attained using VQ are around 10:1 to 20:1. A survey of compression schemes for LFI is presented in Viola et al [Viola et al 2017].…”

Section: Light Field Compressionmentioning

confidence: 99%

HMLFC: Hierarchical Motion‐Compensated Light Field Compression for Interactive Rendering

Pratapa

Manocha

2019

Computer Graphics Forum

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We present a new motion‐compensated hierarchical compression scheme (HMLFC) for encoding light field images (LFI) that is suitable for interactive rendering. Our method combines two different approaches, motion compensation schemes and hierarchical compression methods, to exploit redundancies in LFI. The motion compensation schemes capture the redundancies in local regions of the LFI efficiently (local coherence) and the hierarchical schemes capture the redundancies present across the entire LFI (global coherence). Our hybrid approach combines the two schemes effectively capturing both local as well as global coherence to improve the overall compression rate. We compute a tree from LFI using a hierarchical scheme and use phase shifted motion compensation techniques at each level of the hierarchy. Our representation provides random access to the pixel values of the light field, which makes it suitable for interactive rendering applications using a small run‐time memory footprint. Our approach is GPU friendly and allows parallel decoding of LF pixel values. We highlight the performance on the two‐plane parameterized light fields and obtain a compression ratio of 30–800× with a PSNR of 40–45 dB. Overall, we observe a ∼2–5× improvement in compression rates using HMLFC over prior light field compression schemes that provide random access capability. In practice, our algorithm can render new views of resolution 512 × 512 on an NVIDIA GTX‐980 at ∼200 fps.

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“…The compression rates attained using VQ are around 10:1 to 20:1. A survey of compression schemes for LFI is presented in Viola et al [Viola et al 2017].…”

Section: Light Field Compressionmentioning

confidence: 99%

HMLFC: Hierarchical Motion‐Compensated Light Field Compression for Interactive Rendering

Pratapa

Manocha

2019

Computer Graphics Forum

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“…The methodology was successfully used to evaluate how different approaches in LF compression can affect the visual quality of the content. 16 Moreover, its validity was tested against a standard passive methodology, which allowed the users to see a pre-recorded animation of the LF content, without any possibility to interact with it. …”

Section: 13mentioning

confidence: 99%

“…A new interactive assessment methodology was already introduced by the authors, 15 and it was successfully used in evaluation of quality of LF contents in presence of compression artefacts. 16 However, it was shown that the interactive methodology had less discriminative power when compared to a passive approach, and leads in general to larger confidence intervals.…”

Section: Proposed Frameworkmentioning

confidence: 99%

A new framework for interactive quality assessment with application to light field coding

Viola

Ebrahimi

2017

Applications of Digital Image Processing XL

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In recent years, light field has experienced a surge of popularity, mainly due to the recent advances in acquisition and rendering technologies that have made it more accessible to the public. Thanks to image-based rendering techniques, light field contents can be rendered in real time on common 2D screens, allowing virtual navigation through the captured scenes in an interactive fashion. However, this richer representation of the scene poses the problem of reliable quality assessments for light field contents. In particular, while subjective methodologies that enable interaction have already been proposed, no work has been done on assessing how users interact with light field contents. In this paper, we propose a new framework to subjectively assess the quality of light field contents in an interactive manner and simultaneously track users behaviour. The framework is successfully used to perform subjective assessment of two coding solutions. Moreover, statistical analysis performed on the results shows interesting correlation between subjective scores and average interacton time.

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“…In order to store, transmit, and render LFI, it is important to develop good compression algorithms. Different schemes have been proposed for compressing LFI, as surveyed in [Viola et al 2017]. The majority of these methods provide high compression rates, like standard 2D image compression methods, but they require decoding all the LFI samples into memory before rendering.…”

Section: Introductionmentioning

confidence: 99%

RLFC

Pratapa

Manocha

2019

Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games

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Figure 1: Our method (RLFC) is based on computing a hierarchy of new images: Representative Key Views (RKV) which capture the redundancies of the LF in the top levels of the hierarchy and Sparse Residual Views (SRV) that capture specific details of the LF in the bottom levels of the hierarchy. We present a visualization of the images (RKV & SRV) computed in RLFC hierarchy on a small sample grid of the LF for two datasets. RLFC achieves compression by removing the insignificant details and exploiting the sparsity of the SRV images in the hierarchy. ABSTRACTWe present a new hierarchical compression scheme for encoding light field images (LFI) that is suitable for interactive rendering. Our method (RLFC) exploits redundancies in the light field images by constructing a tree structure. The top level (root) of the tree captures the common high-level details across the LFI, and other levels (children) of the tree capture specific low-level details of the LFI. Our decompressing algorithm corresponds to tree traversal operations and gathers the values stored at different levels of the tree. Furthermore, we use bounded integer sequence encoding which provides random access and fast hardware decoding for compressing the blocks of children of the tree. We have evaluated our method for 4D two-plane parameterized light fields. The compression rates vary from 0.08 − 2.5 bits per pixel (bpp), resulting in compression ratios of around 200:1 to 20:1 for a PSNR quality of 40 to 50 dB. The decompression times for decoding the blocks of LFI are 1 − 3 microseconds per channel on an NVIDIA GTX-960 and we can render new views with a resolution of 512 × 512 at 200 fps. Our overall scheme is simple to implement and involves only bit manipulations and integer arithmetic operations. 1

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Comparison and Evaluation of Light Field Image Coding Approaches

Cited by 73 publications

References 35 publications

HMLFC: Hierarchical Motion‐Compensated Light Field Compression for Interactive Rendering

HMLFC: Hierarchical Motion‐Compensated Light Field Compression for Interactive Rendering

A new framework for interactive quality assessment with application to light field coding

RLFC

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