Rate Distortion Optimized Graph Partitioning for Omnidirectional Image Coding

Abstract : Omnidirectional images are spherical signals captured by cameras with 360-degree field of view. In order to be compressed using existing encoders, these signals are mapped to planar domain. A commonly used planar representation is the equirectangular one, which corresponds to a non uniform sampling pattern on the spherical surface. This particularity is not explored in traditional image compression schemes, which treat the input signal as a classical perspective image. In this work, we build a graph-based coder adapted to the spherical surface. We build a graph directly on the sphere. Then, to have computationally feasible graph transforms, we propose a rate-distortion optimized graph partitioning algorithm to achieve an effective trade-off between the distortion of the reconstructed signals, the smoothness of the signal on each subgraph, and the cost of coding the graph partitioning description. Experimental results demonstrate that our method outperforms JPEG coding of planar equirectangular images.
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https://hal.inria.fr/hal-01807613
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Submitted on : Monday, June 4, 2018 - 10:20:07 PM
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Mira Rizkallah, Francesca de Simone, Thomas Maugey, Christine Guillemot, Pascal Frossard. Rate Distortion Optimized Graph Partitioning for Omnidirectional Image Coding. EUSIPCO 2018 - 26th European Signal Processing Conference, Sep 2018, Rome, Italy. pp.1-5. ⟨hal-01807613⟩

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