Rate-Distortion Optimized Graph Coarsening and Partitioning for Light Field Coding

Graph-based transforms are powerful tools for signal representation and energy compaction. However, their use for high dimensional signals such as light fields poses obvious problems of complexity. To overcome this difficulty, one can consider local graph transforms defined on supports of limited di...

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Bibliographic Details
Published in:IEEE transactions on image processing Vol. 30; p. 1
Main Authors: Rizkallah, Mira, Maugey, Thomas, Guillemot, Christine
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Subjects:
Approximation theory
Clustering
Clustering algorithms
Coarsening
Coding
Complexity
compression
Compression efficiency
Computer Science
Correlation
Distortion
Electric distortion
Encoding
Energy compaction
Graph optimization
graph partitioning
graph reduction
graph transforms
Graphic methods
Image coding
Image compression
Light fields
Low rank approximations
Optimization
Rate distortion performance
Rate-distortion
Signal and Image Processing
Signal correlation
Signal distortion
Signal representations
Spectral clustering
super-rays
Transforms
Video compression
Light fields
graph transforms
graph partitioning
compression
graph reduction
super-rays
ISSN:1057-7149, 1941-0042, 1941-0042
Online Access:Get full text
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Summary:Graph-based transforms are powerful tools for signal representation and energy compaction. However, their use for high dimensional signals such as light fields poses obvious problems of complexity. To overcome this difficulty, one can consider local graph transforms defined on supports of limited dimension, which may however not allow us to fully exploit long-term signal correlation. In this paper, we present methods to optimize local graph supports in a rate distortion sense for efficient light field compression. A large graph support can be well adapted for compression efficiency, however at the expense of high complexity. In this case, we use graph reduction techniques to make the graph transform feasible. We also consider spectral clustering to reduce the dimension of the graph supports while controlling both rate and complexity. We derive the distortion and rate models which are then used to guide the graph optimization. We describe a complete light field coding scheme based on the proposed graph optimization tools. Experimental results show rate-distortion performance gains compared to the use of fixed graph support. The method also provides competitive results when compared against HEVC-based and the JPEG Pleno light field coding schemes. We also assess the method against a homography-based low rank approximation and a Fourier disparity layer based coding method.
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ISSN:1057-7149
1941-0042
1941-0042
DOI:10.1109/TIP.2021.3085203