Layered Depth Images for Multi-View Coding

This thesis presents an advanced framework for multi-view plus depth video processing and compression based on the concept of layered depth image (LDI). Several contributions are proposed for both depth-image based rendering and LDI construction and compression. The first contribution is a novel virtual view synthesis technique called Joint Projection Filling (JPF). This technique takes as input any image plus depth content and provides a virtual view in general position and performs image warping while detecting and filling cracks and other small disocclusions. A pixel confidence measure is introduced to avoid ghosting artifacts in the rendered views. For intermediate view interpolation, JPF is used in collaboration with a floating texture realignment technique. For virtual view extrapolation, JPF is combined with a novel full-Z depth aided inpainting technique. In order to efficiently encode the proposed LDI representation, a compression scheme based on MVC/AVC standard is adapted to exploit both temporal redundancies and inter-layer redundancies in the LDI sequence. An incremental construction scheme for the LDI is proposed, called I-LDI. This construction scheme reduces the completion rate of additional layers. An object-based layer organization of the LDI is then presented which ensures spatial consistency of each layer, and thus improves compression efficiency in comparison with a standard AVC/MVC scheme in rate-constrained context. Two rendering methods are finally proposed: the first one uses the JPF method, while the second one uses a 3D mesh for real-time rendering on an eight-views auto-stereoscopic display.

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Source https://theses.hal.science/tel-00758301
Author Jantet, Vincent
Maintainer CCSD
Last Updated May 14, 2026, 11:55 (UTC)
Created May 14, 2026, 11:55 (UTC)
Identifier tel-00758301
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Digital image processing, modeling and communication (TEMICS) ; Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA) ; Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de l'Université de Rennes ; Institut National de Recherche en Informatique et en Automatique (Inria)
creator Jantet, Vincent
date 2012-11-23T00:00:00
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harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-08-12T00:00:00
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