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multiview image coding Using Depth Layers and an Optimized Bit Allocation

IEEE TRANSACTIONS ON image PROCESSING 2012年第9期21卷 4092-4105页

作者： Gelman, Andriy Dragotti, Pier Luigi Velisavljevic, Vladan Univ London Imperial Coll Sci Technol & Med Dept Elect & Elect Engn London SW7 2AZ England Deutsch Telekom Labs D-10587 Berlin Germany

In this paper, we present a novel wavelet-based compression algorithm for multiview images. This method uses a layer-based representation, where the 3-D scene is approximated by a set of depth planes with their associated constant disparities. The layers are extracted from a collection of images captured at multiple viewpoints and transformed using the 3-D discrete wavelet transform (DWT). The DWT consists of the 1-D disparity compensated DWT across the viewpoints and the 2-D shape-adaptive DWT across the spatial dimensions. Finally, the wavelet coefficients are quantized and entropy coded along with the layer contours. To improve the rate-distortion performance of the entire coding method, we develop a bit allocation strategy for the distribution of the available bit budget between encoding the layer contours and the wavelet coefficients. The achieved performance of our proposed scheme outperforms the state-of-the-art codecs for several data sets of varying complexity.

关键词： Bit rate allocation compression multiview image coding wavelet transforms

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multiview image coding USING GRAPH-BASED APPROACH

MULTIVIEW IMAGE CODING USING GRAPH-BASED APPROACH

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IEEE 11th IVMSP Workshop - 3D image/Video Technologies and Applications

作者： Maugey, Thomas Ortega, Antonio Frossard, Pascal Ecole Polytech Fed Lausanne CH-1015 Lausanne Switzerland Univ So Calif Los Angeles CA 90089 USA

ISBN: (纸本)9781467358583

In this paper, we design a new approach for coding the geometry information in a multiview image scenario. As an alternative to depth-based schemes, we propose a representation that captures the dependencies between pixels in different frames in the form of connections in a graph. In our approach it is possible to directly perform compression by simplifying the graph, which provides a more direct control of the effect of coding on geometry representation. Our method leads to more accurate view synthesis, when compared to conventional lossy coding of depth maps operating at the same bit rate.

关键词： Graph representation multiview image coding depth maps

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A FAST LAYER-BASED multiview image coding ALGORITHM

A FAST LAYER-BASED MULTIVIEW IMAGE CODING ALGORITHM

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20th European Signal Processing Conference (EUSIPCO)

作者： Gelman, Andriy Onativia, Jon Dragotti, Pier Luigi Univ London Imperial Coll Sci Technol & Med Commun & Signal Proc Grp London England

ISBN: (纸本)9781467310680

In [1,2] we presented a multiview image coding scheme. The approach is based on extracting depth layers from multiview images. Each layer is related to an object in the scene and is highly redundant. We exploit this redundancy by using a properly disparity compensated Wavelet Transform, followed by quantisation and entropy coding of the transform coefficients. In addition, to reconstruct the data we encode a 2D contour associated with each layer. In this paper we describe extensions to this coding scheme aimed at reducing the complexity of the algorithm, while retaining its rate-distortion (RD) performance. In particular, we propose a novel low-complexity scheme to encode the layer contours. Simulation results show that the approach remains competitive with the original method. In addition we show that the reduced complexity algorithm still outperforms H.264/AVC.

关键词： multiview image coding wavelet transform image-based rendering contour encoding

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3D GEOMETRY REPRESENTATION USING multiview coding OF image TILES

3D GEOMETRY REPRESENTATION USING MULTIVIEW CODING OF IMAGE T...

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IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Gao, Yu Cheung, Gene Maugey, Thomas Frossard, Pascal Liang, Jie Simon Fraser Univ Burnaby BC V5A 1S6 Canada Natl Inst Informat Tokyo Japan Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (纸本)9781479928934

Compression of dynamic 3D geometry obtained from depth sensors is challenging, because noise and temporal inconsistency inherent in acquisition of depth data means there is no one-to-one correspondence between sets of 3D points in consecutive time instants. In this paper, instead of coding 3D points (or meshes) directly, we propose to represent an object's 3D geometry as a collection of tile images. Specifically, we first place a set of image tiles around an object. Then, we project the object's 3D geometry onto the tiles that are interpreted as 2D depth images, which we subsequently encode using a modified multiview image codec tuned for piecewise smooth signals. The crux of the tile image framework is the "optimal" placement of image tiles-one that yields the best tradeoff in rate and distortion. We show that if only planar and cylindrical tiles are considered, then the optimal placement problem for.. tiles can be mapped to a tractable piecewise linear approximation problem. We propose an efficient dynamic programming algorithm to find an optimal solution to the piecewise linear approximation problem. Experimental results show that optimal tiling outperforms naive tiling by up to 35% in rate reduction, and graph transform can further exploit the smoothness of the tile images for coding gain.

关键词： 3D geometry compression multiview image coding

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Reference View Selection in DIBR-Based multiview coding

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IEEE TRANSACTIONS ON image PROCESSING 2016年第4期25卷 1808-1819页

作者： Maugey, Thomas Petrazzuoli, Giovanni Frossard, Pascal Cagnazzo, Marco Pesquet-Popescu, Beatrice Inst Rech Informat & Syst Alcatoires Inst Natl Rech Informat & Automat SIROCCO Project Team F-35042 Rennes France Inst Mines Telecom Dept Image & Signal Proc F-75634 Paris France CNRS Lab Commun & Proc Informat F-75016 Paris France Ecole Polytech Fed Lausanne Inst Elect Engn Signal Proc Lab CH-1015 Lausanne Switzerland

Augmented reality, interactive navigation in 3D scenes, multiview video, and other emerging multimedia applications require large sets of images, hence larger data volumes and increased resources compared with traditional video services. The significant increase in the number of images in multiview systems leads to new challenging problems in data representation and data transmission to provide high quality of experience on resource-constrained environments. In order to reduce the size of the data, different multiview video compression strategies have been proposed recently. Most of them use the concept of reference or key views that are used to estimate other images when there is high correlation in the data set. In such coding schemes, the two following questions become fundamental: 1) how many reference views have to be chosen for keeping a good reconstruction quality under coding cost constraints? And 2) where to place these key views in the multiview data set? As these questions are largely overlooked in the literature, we study the reference view selection problem and propose an algorithm for the optimal selection of reference views in multiview coding systems. Based on a novel metric that measures the similarity between the views, we formulate an optimization problem for the positioning of the reference views, such that both the distortion of the view reconstruction and the coding rate cost are minimized. We solve this new problem with a shortest path algorithm that determines both the optimal number of reference views and their positions in the image set. We experimentally validate our solution in a practical multiview distributed coding system and in the standardized 3D-HEVC multiview coding scheme. We show that considering the 3D scene geometry in the reference view, positioning problem brings significant rate-distortion improvements and outperforms the traditional coding strategy that simply selects key frames based on the distance between cameras.

关键词： multiview distributed coding key view positioning inter-view correlation view synthesis multiview image coding

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Multiterminal source coding for multiview images under wireless fading channels

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MULTIMEDIA TOOLS AND APPLICATIONS 2010年第3期48卷 457-470页

作者： Khirallah, Chadi Stankovic, Vladimir Stankovic, Lina Cheng, Samuel Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Lanark Scotland Univ Oklahoma Sch Elect & Comp Engn Schusterman Ctr Tulsa OK 74135 USA

This paper addresses the problem of wireless transmission of a captured scene from multiple cameras, which do not communicate among each other, to a joint decoder. Correlation among different camera views calls for distributed source coding for efficient multiview image compression. The fact that cameras are placed within a short range of each other results in a high level of interference, multipath fading, and noise effects during communications. We develop a novel two-camera system, that employs multiterminal source coding and complete complementary data spreading, so that while the former technique exploits the statistical correlation between camera views, and performs joint compression to reduce transmission rates, the spreading technique will protect transmitted data by mitigating the effects of wireless fading channels. Our results indicate that the proposed system is competitive when compared to two independently JPEG encoded streams at low to medium transmission rates.

关键词： multiview image coding Distributed source coding Slepian-Wolf coding Spread spectrum Complete complementary sequences

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GRAPH-BASED REPRESENTATION AND coding OF multiview GEOMETRY

GRAPH-BASED REPRESENTATION AND CODING OF MULTIVIEW GEOMETRY

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Maugey, Thomas Ortega, Antonio Frossard, Pascal Ecole Polytech Fed Lausanne CH-1015 Lausanne Switzerland Univ Southern Calif Los Angeles CA 90007 USA

ISBN: (纸本)9781479903566

We propose a new approach for describing the geometry information of multiview image representations. Rather than transmitting the raw geometry of the scene, under the form of depth information, we build a graph that represents the connections between corresponding pixels in different views in a multiview image set. The graph starts with the reference image and recursively represents the next levels (i.e., images) by storing the new pixels (those that cannot be derived from the previous image) and their connections to the lower level. The decoder uses these connections to recover the multiple images. In addition to being natural and more easily controlled, the proposed graph-based representation can be compressed more efficiently than depth images. This new representation offers promising perspectives for effective and flexible coding in multiview imaging.

关键词： Graph representation multiview image coding depth maps

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Graph-Based Representation for multiview image Geometry

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IEEE TRANSACTIONS ON image PROCESSING 2015年第5期24卷 1573-1586页

作者： Maugey, Thomas Ortega, Antonio Frossard, Pascal INRIA IRISA F-35042 Rennes France Swiss Fed Inst Technol Lausanne Inst Elect Engn Signal Proc Lab CH-1015 Lausanne Switzerland Univ So Calif Dept Elect Engn Los Angeles CA 90089 USA

In this paper, we propose a new geometry representation method for multiview image sets. Our approach relies on graphs to describe the multiview geometry information in a compact and controllable way. The links of the graph connect pixels in different images and describe the proximity between pixels in 3D space. These connections are dependent on the geometry of the scene and provide the right amount of information that is necessary for coding and reconstructing multiple views. Our multiview image representation is very compact and adapts the transmitted geometry information as a function of the complexity of the prediction performed at the decoder side. To achieve this, our graph-based representation (GBR) carefully selects the amount of geometry information needed before coding. This is in contrast with depth coding, which directly compresses with losses the original geometry signal, thus making it difficult to quantify the impact of coding errors on geometry-based interpolation. We present the principles of this GBR and we build an efficient coding algorithm to represent it. We compare our GBR approach to classical depth compression methods and compare their respective view synthesis qualities as a function of the compactness of the geometry description. We show that GBR can achieve significant gains in geometry coding rate over depth-based schemes operating at similar quality. Experimental results demonstrate the potential of this new representation.

关键词： multiview image coding 3D representation view prediction graph-based representation

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GRAPH-BASED REPRESENTATION AND coding OF multiview GEOMETRY

GRAPH-BASED REPRESENTATION AND CODING OF MULTIVIEW GEOMETRY

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Thomas Maugey Antonio Ortega Pascal Frossard Ecole Polytechnique Fédérale de Lausanne (EPFL) University of Southern California

ISBN: (纸本)9781479903573

关键词： Graph representation multiview image coding depth maps Graph representations STRUCTURE MAP Information geometry geometry images image representation multiple image Societies Connections pixel

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