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Conference Publication

L-Infinite Predictive Coding of Depth

Host Publication: International Conference on Advanced Concepts for Intelligent Vision Systems

Authors: W. Chang, I. Schiopu and A. Munteanu

UsePubPlace: Poitiers, France

Publisher: Springer

Publication Date: Sep. 2018

Number of Pages: 12

ISBN: 978-3-030-01448-3


Abstract:

The paper introduces a novel L_infinite-constrained compression method for depth maps. The proposed method performs depth segmentation and depth prediction in each segment, encoding the resulting information as a base layer. The depth residuals are modeled using a Two-Sided Geometric Distribution, and distortion and entropy models for the quantized residuals are derived based on such distributions. A set of optimal quantizers is determined to ensure a fix rate budget at a minimum L_infinite distortion. A fixed-rate L_infinite codec design performing context-based entropy coding of the quantized residuals is proposed, which is able to efficiently meet user constraints on rate or distortion. Additionally, a scalable L_infinite codec extension is proposed, which enables encoding the quantized residuals in a number of enhancement layers. The experimental results show that the proposed L_infinite coding approach substantially outperforms the L_infinite coding extension of the state-of-the-art CALIC method.

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Dr. Ionut Schiopu

+32 (0)02 629 169

ischiopu@etrovub.be

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Prof. Dr. Ir. Adrian Munteanu

+32 (0)02 629 168

acmuntea@etrovub.be

more info

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