Rate-distortion analysis of multiview coding in a DIBR framework

Rajaei, Boshra; Maugey, Thomas; Pourreza, Hamid Reza; Frossard, Pascal

doi:10.1007/s12243-013-0375-6

Cited by 10 publications

(7 citation statements)

References 28 publications

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“…In this context, a lot of research has been done in improving compression of depth maps for the goal of view synthesis [5]. This is done by modelling the distortion of a synthesized view according to changes in the depth values due to the compression process [3], [4].…”

Section: A Multiview Video Codingmentioning

confidence: 99%

Bypassing Depth Maps Transmission For Immersive Video Coding

Garus

Jung

Maugey

et al. 2019

2019 Picture Coding Symposium (PCS)

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This paper addresses several downsides of the system under development in MPEG-I for coding and transmission of immersive media. We present a solution, which enables Depth-Image-Based Rendering for immersive video applications, while lifting the requirement of transmitting depth information. Instead, we estimate the depth information on the client-side from the transmitted views. The approach leads to an impressive rate saving (37.3% in average). Preserving perceptual quality in terms of MS-SSIM of synthesized views, it yields to 24.6% rate reduction for the same quality of reconstructed views after residue transmission under the MPEG-I common test conditions. Simultaneously, the required pixel rate, i.e. the number of pixels processed per second by the decoder, is reduced by 50% for any test sequence. To the author's knowledge, this is the first time that such an approach is under consideration in the context of immersive video coding.

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Section: A Multiview Video Codingmentioning

confidence: 99%

Bypassing Depth Maps Transmission For Immersive Video Coding

Garus

Jung

Maugey

et al. 2019

2019 Picture Coding Symposium (PCS)

Self Cite

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“…In order to guarantee the opti- mality of the obtained solution, we should note that a very large number of couple has been considered by imposing a very small variations in the bitrate between each two successive trials. Furthermore, we compare these allocation methods with a prior given rate allocation which is commonly used in practice [21]. More precisely, a fraction (resp. )…”

Section: Resultsmentioning

confidence: 99%

Efficient Inter-View Bit Allocation Methods for Stereo Image Coding

Hachicha

Kaaniche

Beghdadi

et al. 2015

IEEE Trans. Multimedia

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In this paper, we present efficient bit allocation methods for stereo image coding purpose. Since the common idea behind most of the existing stereo compression schemes consists of encoding a reference and residual images as well as a disparity map, we mainly focus on the bit allocation issue between the reference and residual images. Generally, this problem is solved in an empirical manner by looking for the optimal rates leading to the minimum distortion value. Thanks to recent approximations of the entropy and distortion functions, we propose accurate and fast bit allocation schemes appropriate for the open-loop-and closed-loop-based stereo coding structures. Experimental results show the benefits which can be drawn from the proposed bit allocation methods.

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“…In [18], the RD analysis relies on some complex models for the image textures. In [19], wavelet properties are used to separate the different components of the scene and to analyze the consequence of inaccuracies in their depth values on each object. Regardless of the chosen RD model, the compression performance optimization remains complex and strongly dependent on scene content and camera settings (baseline, geometry complexity, etc.…”

Section: Related Workmentioning

confidence: 99%

Graph-Based Representation for Multiview Image Geometry

Maugey

Ortega

Frossard

2015

IEEE Trans. on Image Process.

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Abstract-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.Index Terms-Multiview image coding, 3D representation, view prediction, graph-based representation.

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Rate-distortion analysis of multiview coding in a DIBR framework

Cited by 10 publications

References 28 publications

Bypassing Depth Maps Transmission For Immersive Video Coding

Bypassing Depth Maps Transmission For Immersive Video Coding

Efficient Inter-View Bit Allocation Methods for Stereo Image Coding

Graph-Based Representation for Multiview Image Geometry

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